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Processes of the Earth’s surface occur at different scales of time and intensity. Climate in particular determines the activity and seasonal development of vegetation. These dynamics are predominantly driven by temperature in the humid mid-latitudes and by the availability of water in semi-arid regions. Human activities are a modifying parameter for many ecosystems and can become the prime force in well-developed regions with an intensively managed environment. Accounting for these dynamics, i.e. seasonal dynamics of ecosystems and short- to long-term changes in land-cover composition, requires multiple measurements in time. With respect to the characterization of the Earth surface and its transformation due to global warming and human-induced global change, there is a need for appropriate data and methods to determine the activity of vegetation and the change of land cover. Space-borne remote sensing is capable of monitoring the activity and development of vegetation as well as changes of the land surface. In many instances, satellite images are the only means to comprehensively assess the surface characteristics of large areas. A high temporal frequency of image acquisition, forming a time series of satellite data, can be employed for mapping the development of vegetation in space and time. Time series allow for detecting and assessing changes and multi-year transformation processes of high and low intensity, or even abrupt events such as fire and flooding. The operational processing of satellite data and automated information-extraction techniques are the basis for consistent and continuous long-term product generation. This provides the potential for directly using remote-sensing data and products for analyzing the land surface in relation to global warming and global change, including deforestation and land transformation. This study aims at the development of an advanced approach to time-series generation using data-quality indicators. A second goal focuses on the application of time series for automated land-cover classification and update, using fractional cover estimates to accommodate for the comparatively coarse spatial resolution. Requirements of this study are the robustness and high accuracy of the approaches as well as the full transferability to other regions and datasets. In this respect, the developments of this study form a methodological framework, which can be filled with appropriate modules for a specific sensor and application. In order to attain the first goal, time-series compilation, a stand-alone software application called TiSeG (Time Series Generator) has been developed. TiSeG evaluates the pixel-level quality indicators provided with each MODIS land product. It computes two important data-availability indicators, the number of invalid pixels and the maximum gap length. Both indices are visualized in time and space, indicating the feasibility of temporal interpolation. The level of desired data quality can be modified spatially and temporally to account for distinct environments in a larger study area and for seasonal differences. Pixels regarded as invalid are either masked or interpolated with spatial or temporal techniques.
This study presents new petrological results obtained from high-grade metamorphic rocks of the Beit Bridge, Mahalapye and Phikwe Complexes, which constitute the Central Zone of the Limpopo Belt in southern Africa. These results provide detailed information about the prograde and retrograde pressure-temperature (P-T) evolution of the three investigated complexes and, in concert with geochronological data, form the basis for the development of a coherent geodynamic model for the evolution of the Limpopo’s Central Zone. The P-T paths were inferred by the thorough investigation of silica-saturated and silica- undersaturated metapelitic and metabasic rocks, comprising six sillimanite-garnet-cordierite gneisses, four (garnet)-biotite-plagioclase gneisses, two garnet-orthopyroxene-biotite-Kfeldspar-plagioclase gneisses, one garnet- cordierite-orthoamphibole fels, one garnet-biotite amphibolite, and one garnet-clinopyroxene amphibolite. P-T points and P-T evolutions were derived by the application of conventional geothermobarometers, and quantitative phase diagrams in the systems Na2O - CaO - K2O - FeO - MgO - Al2O3 - SiO2 - H2O - TiO2 - O (NCKFMASHTiO), and MnO - TiO2 - Na2O - CaO - K2O - FeO - MgO - Al2O3 - SiO2 - H2O (MnTiNCKFMASH) - using the computer software THERMOCALC and THERIAK-DOMINO. The petrological information, in particular those obtained by comparison between observed and thermodynamically calculated mineral assemblages, zonations and modes, in combination with new and existing geochronological data provide evidence that rocks from the three investigated complexes underwent slightly different P-T evolutions at different times. The samples from the Bulai Pluton area (Beit Bridge Complex) provide evidence for a Neoarchean high-grade metamorphic event at ~2.64 Ga (M2), with peak P-T conditions of ~850°C at 8-9 kbar, and a decompression-cooling path to ~750°C at 5-6 kbar. This metamorphic evolution perhaps took place in a magmatic arc setting. In contrast, samples from the Mahalapye and Phikwe Complex document a Palaeoproterozoic event at ~2.03-2.05 Ga (M3), and were subject to different styles of prograde metamorphism. Metamorphic rocks from the Mahalapye Complex experienced a high-temperature low-pressure (HT-LP) metamorphic overprint, accompanied by the emplacement of voluminous granite bodies between 2.06 and 2.02 Ga, and provide evidence for a slightly prograde decompression from ~650°C/7 kbar to ~800°C/5.5 kbar. In contrast, the metamorphic rocks from the Phikwe Complex provide evidence for a simultaneous pressure and temperature increase from ~600°C/6 kbar to ~750°C/8 kbar, in the absence of significant Palaeoproterozoic magmatism. The HT-LP metamorphic evolution of the Mahalapye Complex is interpreted to be initiated by the underplating of hot mafic melts, either formed in response to SE-subduction during the Kheis-Magondi orogeny, and/or by contemporaneous mantle plume activities related to the formation of the Bushveld Complex. In contrast, the prograde pressure and temperature increase reflected by the rocks from the Phikwe Complex rather reflects successive crustal stacking at ~2.03 Ga. This stacking, which is also reported from many other units throughout the Limpopo Belt, is interpreted to result from the final convergence between the Kaapvaal and Zimbabwe Cratons, perhaps caused by SE-directed compression in response to the Kheis-Magondi orogeny between ~2.06 and 1.90 Ga.
The study investigates the water resources and aquifer dynamics of the igneous fractured aquifer-system of the Troodos Mountains in Cyprus, using a coupled, finite differences water balance and groundwater modelling approach. The numerical water balance modelling forms the quantitative framework by assessing groundwater recharge and evapotranspiration, which form input parameters for the groundwater flow models. High recharge areas are identified within the heavily fractured Gabbro and Sheeted Dyke formations in the upper Troodos Mountains, while the impervious Pillow Lava promontories - with low precipitation and high evapotranspiration - show unfavourable recharge conditions. Within the water balance studies, evapotranspiration is split into actual evapotranspiration and the so called secondary evapotranspiration, representing the water demand for open waters, moist and irrigated areas. By separating the evapotranspiration of open waters and moist areas from the one of irrigated areas, groundwater abstraction needs are quantified, allowing the simulation of single well abstraction rates in the groundwater flow models. Two sets of balanced groundwater models simulate the aquifer dynamics in the presented study: First, the basic groundwater percolation system is investigated using two-dimensional vertical flow models along geological cross-sections, depicting the entire Troodos Mountains up to a depth of several thousands of metres. The deeply percolating groundwater system starts in the high recharge areas of the upper Troodos, shows quasi stratiform flow in the Gabbro and Sheeted Dyke formations, and rises to the surface in the vicinity of the impervious Pillow Lava promontories. The residence times mostly yield less than 25 years, the ones of the deepest fluxes several hundreds of years. Moreover, inter basin flow and indirect recharge of the Circum Troodos Sedimentary Succession are identified. In a second step, the upper and most productive part of the fractured igneous aquifer-system is investigated in a regional, horizontal groundwater model, including management scenarios and inter catchment flow studies. In a natural scenario without groundwater abstractions, the recovery potential of the aquifer is tested. Predicted future water demand is simulated in an increased abstraction scenario. The results show a high sensitivity to well abstraction rate changes in the Pillow Lava and Basal Group promontories. The changes in groundwater heads range from a few tens of metres up to more than one hundred metres. The sensitivity in the more productive parts of the aquifer-system is lower. Inter-catchment flow studies indicate that - besides the dominant effluent conditions in the Troodos Mountains - single reaches show influent conditions and are sub-flown by groundwater. These fluxes influence the local water balance and generate inter catchment flow. The balanced groundwater models form thus a comprehensive modelling system, supplying future detail models with information concerning boundary conditions and inter-catchment flow, and allowing the simulation of impacts of landuse or climate change scenarios on the dynamics and water resources of the Troodos aquifer-system.
The taphonomic and paleoecologic aspects of the Upper Hauterivian to Lower Barremian Agua de la Mula Member of the Agrio Formation (Neuquén Basin, Argentina) were studied in the frame of the sequence stratigraphic paradigm. The Agua de la Mula Member, a ca. 600 m thick succession of highly cyclic marine sediments was surveyed at two localities. Detailed bed-by-bed sedimentologic, stratigraphic, ichnologic, taphonomic and paleoecologic data collection allowed a precise paleoenvironmental, stratigraphic, taphonomic and synecologic interpretation, in a controlled sequence stratigraphic framework. The main architectural stratigraphic component is the Starvation-Dilution Sequence, interpreted as a the effect of a sixth-order, Milankovitch precession-driven cycle. Dilution hemisequences are siliciclastic-dominated and show evidence of depth changes. Starvation hemisequences show a diverse variation of mixed carbonate-siliciclastic facies that is linked to sequence stratigraphy. Ammonite-based biostratigraphy was revised and new knowledge proposed. The stratigraphic framework was improved by combining biostratigraphy, sequence stratigraphy and event stratigraphy. Nine main sequences were described, linked to other stratigraphic markers and correlated with other sequence stratigraphic charts. Several orders of cyclicity were inferred. Third- and fourth-order sequences are the major sequences, not subordinated to higher hierarchies (lower order). Precession, obliquity, and short and long eccentricity cycles of the Milankovitch band are proposed. Among the different sequence stratigraphic models the transgression-regression model fits the majority of the sequences described in this work. The depositional-sequence model could be applied only to the first third-order sequence, in which the true sequence boundary is identifiable. Starvation-dilution sequences, however, are composed by to components that are not completely explained by those models. Starvation hemisequences developed in intermediate to deep settings record the transgressive phase as well as the earLy regressive one without visible stratigraphic boundaries. 112 samples with 22,572 individuals were grouped into fifteen fossil associations and one assemblage that reflect the interaction of different factors: age, position in major, medium and starvation dilution sequences and, linked to sequence stratigraphy, depth, oxygen availability, rate of terrigenous input, water agitation, and substrate conditions. Temporary possible reduction in oxygen content is inferred based on all sources of available evidence. Organic buildups are briefly described and their development interpreted in terms of the sequence stratigraphic framework. Vertical patterns of replacement of fossil associations are described and related to sequence stratigraphy. Five types of skeletal concentrations represent the diversity of coquinas decribed in this study. Type 1, 2, 4 and 5 correspond to starvation hemisequences deposited in progressively shallower settings, from basin to inner ramp. Type 3 is embedded into dilution hemisequences and inferred to be linked to shell bed type I of Kidwell (1985). Types 1 and 2 correspond to transgression, maximum flooding and early regression without distinction. Type 4A as well as Type 5 are interpreted as onlap shell beds (Kidwell 1991a) or early TST shell beds (Fürsich and Pandey 2003). Type 4B corresponds to the MFZ shell bed (Fürsich and Pandey 2003) or mid-cycle shell bed (Abbott 1997), while Type 4C to the downlap shell bed (Kidwell 1991a). Time-averaging of shell beds was assessed with precision as the time involved in the deposition of the starvation hemisequences could be inferred. All shell beds comprise within-habitat assemblages forming within a few thousand years, with little environmental condensation. The fossilization of the marine calcareous shells is modelled as a series of steps called windows: environmental, destructional, burial and diagenetic. The “diagenetic window” is the most relevant. Connected to this it is proposed that carbonate dissolution is the primary control on the development of shell beds, as has been proposed before (Fürsich 1982; Fürsich and Pandey 2003). The interpretative power resulting from combining several lines of evidence, e.g., facies analysis, sequence stratigraphy, biostratigraphy, trace fossil analysis, paleoecology and taphonomy, and unravelling their multiple relationships, are the most relevant conclusions of this study.
The main purpose of volcano-seismology concerns the qualitative and quantitative description of one or more unknown seismic source(s) located at some unknown depth beneath a volcano. Even if many different volcanoes show similar seismic signal characteristics, up to now it was not possible to find a standard seismic source model for volcanoes, as the double-couple in earthquake seismology. Volcanoes with a continuous activity, like Stromboli (Italy), represent for the volcano seismologist a perfect natural laboratory to address this question. This thesis treats the study of explosion-quakes and volcanic tremor recorded on Stromboli in a broadband frequency range, and discusses the location and the possible mechanisms of the seismic source(s). Seismic and infrasonic recordings of explosion-quake from Stromboli showed that the high-frequency phase propagates with a velocity of approximately 330 m/s. The seismic source can be explained as an explosion at the top of the magma column generated by rising gas bubbles. The seismic P-wave and the air-wave are both generated in the same point at the same time. The different path lengths and velocities for the seismic wave and the air-wave result in a difference in arrival times dt, that could be used to deduce the magma level and sound speed in the eruption column inside the conduit. Stations installed near the active crater reveal that infrasonic and seismic recordings of the short-period tremor (> 1 Hz) share the same spectral content and show similar energy fluctuations. Therefore, the short-period volcanic tremor at Stromboli originates from the continuous out-bursting of small gas bubbles in the upper part of the magmatic column. The spectrum of the long-period tremor recorded at Stromboli consists of three main peaks with periods at 4.8 s, 6 s and 10 s, and amplitudes varying with the regional meteorological situation. Hence, they are not generated by a close volcanic source but rather by ocean microseisms (OMS). The passage of a local cyclone seems to be the seismic source for spectral energy at 4.8 s and 10 s, which represent the Double Frequency and the Primary Frequency of the OMS, respectively. Concerning the 6 s peak, a cyclone near the British Isles could act as a seismic source. Seismic data from the first broadband array deployed on Stromboli showed surprisingly simple waveforms, indicating an initially contracting source mechanism. The analysis of particle motion and the application of seismic array techniques allowed the location of a seismic source in the shallow part of the volcano. Eruption parameters and seismic source characteristics of the April 5, 2003 Stromboli eruption have been estimated using different inversion approaches. The paroxysm was triggered by a shallow slow thrust-faulting dislocation event with a moment magnitude of Mw = 3.0 and possibly associated with a crack that formed previously by dike extrusion. At least one blow-out phase during the paroxysmal explosion could be identified from seismic signals with an equivalent moment magnitude of Mw = 3.7. It can be represented by a vertical linear vector dipole and two weaker horizontal linear dipoles in opposite direction, plus a vertical force. Seismic measurements performed during controlled and reproducible blow-out experiments with a gas volume entrapped in basaltic melt revealed the following: Monochromatic seismic signals suggest a blow-out in a more ductile regime, whereas broader frequency content indicates rupture in a more brittle environment. The longer the crucible, the weaker the seismic signals. An increase in pressure results in a stronger fragmentation, but not in a higher ejection velocity of the plug neither in a higher seismic amplitude. Even if the very long period observations like the tilt signal could not be simulated in the laboratory, the blow-out experiments simulate very well the short-period seismic signals recorded at Stromboli volcano.
The Upper Bajocian-Bathonian Kashafrud Formation is a thick package of siliciclastic sediments that crops out in NE Iran from the southeast, near the Afghanistan border, to north- northwestern areas around the city of Mashhad. The thickness ranges from less than 300 m in a deltaic succession (Kuh-e-Radar) to more than 2500 m in the Maiamay area, but the normal thickness in Ghal-e-Sangi, Kol-e-Malekabad, and Fraizi areas is about 1200-1300 m. It is the fill of an elongated basin, which extended for more than 200 km in NW-SE direction and a width of at least 50 km along the southern margin of the Koppeh Dagh. Prior to this study, little information existed about the sedimentary environments and other characters, especially the geometry of the basin. Exact biostratigraphic data from the top of the Kashafrud Formation were rare. Based on the macrofauna from the lower part of the overlying Chamanbid Formation the upper boundary of the Kashafrud Formation had been attributed to the Late Bathonian and/or Early Callovian, but now the upper limit of the Kashafrud Formation is defined as Late Bathonian in age, based on ammonite biostratigraphy. Except for chapter one, which deals with the introduction and related sub-titles, in the following chapters, step by step, field observations and data were surveyed according to the questions to solve. In order to reconstruct the facies architecture and the geometry of the basin, a number of sections have been logged in detail (see chapter 3, “The sections”). The exact biostratigraphic setting is discussed in chapter 4 (“Biostratigraphy”). Sedimentary environments range from non-marine alluvial fans and braided rivers in the basal part of the succession to deltas, storm-dominated shelf, slope and deep-marine basin. The latter comprises the largest part of the basin fill, consisting of monotonous mudstones, siltstones and proximal to distal turbidities. The only continuous carbonate unit (~30 m) locally formed at Tappenader. Other localities in which thin fossil-bearing carbonate strata occur are Torbat-e-Jam (benthic fauna) and, to a lesser extent, Ghal-e-Sangi. These rare shallow-water carbonates, which also contain corals, represent only short intervals (see chapter 5,” Facies association and sedimentary environments”). Relative changes in sea level were reconstructed on the basis of deepening- and shallowing-upward trends. Sequence boundaries and parasequences have been distinguished and analyzed in chapter 6 (“Sequence stratigraphy”). In most areas, the basin rapidly evolved from a shallow marine, transgressive succession to a deep-marine, basinal succession. The only area where shallow conditions persisted from the Late Bajocian to the Late Bathonian, and even into the Early Callovian is the Kuh-e-Radar area which corresponds to a fan-delta setting. A trace fossil analysis has been carried out to obtain additional evidence on the bathymetry of the basin (see chapter 7, “Ichnology”). Altogether 29 ichnospecies belonging to 15 ichnogenera have been identified, as well as 10 ichnogenera, which were determined only at genus level. They can be grouped in the well-known “Seilacherian ichnofacies”. Very high subsidence rates and strong lateral thickness variations suggest that the Kashafrud Formation is a rift related basin that formed as the eastern extension of the South Caspian Basin. The basin evolution is reviewed, the eastern and western continuations of the basin were checked in the field and also in the literature (see chapter 8, “Basin evolution”). In all, the present study provided new insights into the development of the Kashafrud Formation, e.g. more biostratigraphic data from the base and the top of the succession, a relatively complete picture of the trace fossil associations, a better recognition and reconstruction of the sedimentary environments in different parts of the basin. Finally this research project will be a good basis for further investigations, especially towards the west, as parts of the Kashafrud Formation are source rocks of a hydrocarbon reservoir in NE Iran.
Four sections of the Galala and Maghra El Hadida formations on the footwalls of the slopes of the northern and southern Galala plateaus in Wadi Araba (Eastern Desert) have been measured and sampled in great detail. The Galala Formation is ranging in thickness from 55 to 95 meters. It unconformably overlies the Malha Formation which forms the base of the studied sections. The upper boundary of the Galala Formation is characterized by a major unconformity which separates it from the overlying the Maghra El Hadida Formation. The Galala Formation can be subdivided into five shallowing-upward cycles, each cycle starting with deep-lagoonal, marly-silty deposits at the base and grading into highly fossiliferous shallow-lagoonal limestones at the top. Only the basal part of the Galala Formation consists of unfossiliferous, greenish sandy siltstones intercalated with thin cross-bedded, bioturbated, fine- to medium-grained sandstones. Despite the lack of biostratigraphic markers in that lower part, its age can be assigned to the late Middle Cenomanian, since the conformably overlying strata contain the ammonite Neolobites vibrayeanus (D’ORBIGNY), the index marker of the early Upper Cenomanian which extends into the top of the formation. The measured thickness of the overlying Maghra El Hadida Formation is ranging from 59 to 118 meters. This formation starts with the Ghonima Member, introduced in this work to distinguish a brown, fine- to medium-grained calcareous sandstone unit in its lower part. The Ghonima Member is erosionally incised into the Galala Formation, explaining its strong lateral variability in thickness, ranging from 3 to 21 meters. It is mostly unfossiliferous except for irregular bioturbation in its upper part. The Ghonima Member is assigned to the middle Upper Cenomanian, based on its stratigraphic position between the lower Upper Cenomanian Neolobites vibrayeanus Zone and the overlying upper Upper Cenomanian Metoicoceras geslinianum and Vascoceras cauvini zones. This means that the lower part of the Maghra El Hadida Formation, about 20 – 30 m thick, accumulated during the latest Cenomanian and that the base of the formation does not coincide with the base of the Turonian as commonly believed. The overlying succession of the Maghra El Hadida Formation is characterized by an increase of carbonate content, represented by yellow, soft marls intercalated with fine-grained wacke- to packstones containing a highly fossiliferous ammonite assemblage of the upper Upper Cenomanian and Lower Turonian (zones of Vascoceras proprium, Choffaticeras spp., and Wrightoceras munieri). The Middle Turonian part of the Maghra El Hadida Formation consists of poorly fossiliferous, thick-bedded yellowish marls with upward-increasing silt content, showing occasional intercalations of medium- to coarse-grained sandstones with hummocky cross-stratification. The topmost part of the Maghra El Hadida Formation consists of brownish, medium-grained sandstones topped by fossiliferous marly limestones yielding the Upper Turonian zonal ammonite Coilopoceras requienianum (D’ORBIGNY). Based on sequence stratigraphic analyses, four complete 3rd order depositional sequences and the lower part of a fifth one, each bounded by major unconformities, can be recognized: depositional sequence DS WA 1 (upper Middle – lower Upper Cenomanian) includes the entire Galala Formation, while the Maghra El Hadida Formation comprises all the overlying depositional sequences: DS WA 2 (upper Upper Cenomanian – Lower Turonian) reaches from the base of the Metoicoceras geslinianum Zone to the top of Wrightoceras munieri Zone, DS WA 3 and DS WA 4 comprise the Middle Turonian, while Upper Turonian sequence DS WA 5 is not complete. The stratigraphic positions of the recognized sequence 2 boundaries SB WA 1 to SB WA 5 match well with contemporaneous sequence boundaries known from Europe and elsewhere. The stacking pattern of the basic cycles and bundles of the Galala Formation (5:1) and the Maghra El Hadida Formation (4:1) strongly suggest an orbital forcing by MILANKOVITCH periodicities. The Galala Formation is composed of five 5th-order bundles which equal to ~500 kyr, each bundle equals to ~100 kyr (short eccentricity). Every bundle has five basic (6th-order) cycles, each one representing ~20 kyr (precession). Based on this precession-short eccentricity syndrome, the accumulation rate of the Galala Formation therefore accounts for about 19 cm/kyr. The rate of sea-level fall at sequence boundary SB WA 2 (equivalent to the quasi-global mid-Late Cenomanian SB Ce V) estimated is with 35 cm/kyr which can be explained only by glacio-eustasy. The Upper Cenomanian and Lower Turonian part of the Maghra El Hadida Formation is considered to equal to ~1200 kyr, based on the existence of three 4th-order bundles with an inferred duration of ~400 kyr for each bundle (long eccentricity of the MILANKOVITCH Band). Every bundle consists of four basic cycles with a duration of ~100 kyr. This means that the upper Cenomanian part of the Maghra El Hadida Formation is equivalent to ~400 kyr, while the Lower Turonian (consisting of the two upper bundles) lasted 800 kyr. This matches well with the recently proposed 785 kyr duration of the Early Turonian (SAGEMAN et al., 2006; VOIGT et al., 2008) and contradicts the 1300 kyr according to the standard time scale of GRADSTEIN et al. (2004). According to this temporal constrains, the accumulation rate of the Maghra El Hadida Formation is about 4.25 cm/kyr. In addition, based on the cyclostratigraphic analysis, the range of the Early Turonian genus Choffaticeras (HYATT) is equivalent to ~325 kyr and morphological changes within its lineage can be quantified. The macrobenthos (bivalves, gastropods, echinoids) and cephalopods of the Galala and Maghra El Hadida formations were identified and illustrated in 24 figures. The ammonite taxonomy and palaeobiogeographic distribution is discussed in detail. Four genera and eight ammonite species are recorded from Egypt for the first time. The microfloral and -faunal assemblage identified in thin sections revealed two species of dasycladalean algae, two species of udoteacean algae, five species of benthic foraminifera, and two species of crustacean microcoprolites. The six facies types of the upper Middle – Upper Cenomanian Galala Formation document largely open-lagoonal, warm water conditions, while the depositional environment of the Upper Cenomanian – Turonian Maghra El Hadida Formation (16 facies types) is suggested to range from a deep-subtidal to intertidal.
Glacier outlines during the ‘Little Ice Age’ maximum in Jotunheimen were mapped by using remote sensing techniques (vertical aerial photos and satellite imagery), glacier outlines from the 1980s and 2003, a digital terrain model (DTM), geomorphological maps of individual glaciers, and field-GPS measurements. The related inventory data (surface area, minimum and maximum altitude) and several other variables (e.g. slope, range) were calculated automatically by using a geographical information system. The length of the glacier flowline was mapped manually based on the glacier outlines at the maximum of the ‘Little Ice Age’ and the DTM. The glacier data during the maximum of the ‘Little Ice Age’ were compared with the Norwegian glacier inventory of 2003. Based on the glacier inventories during the maximum of the ‘Little Ice Age’, the 1980s and 2003, a simple parameterization after HAEBERLI & HOELZLE (1995) was performed to estimate unmeasured glacier variables, as e.g. surface velocity or mean net mass balance. Input data were composed of surface glacier area, minimum and maximum elevation, and glacier length. The results of the parameterization were compared with the results of previous parameterizations in the European Alps and the Southern Alps of New Zealand (HAEBERLI & HOELZLE 1995; HOELZLE et al. 2007). A relationship between these results of the inventories and of the parameterization and climate and climate changes was made.
Wetlands in West Africa are among the most vulnerable ecosystems to climate change. West African wetlands are often freshwater transfer mechanisms from wetter climate regions to dryer areas, providing an array of ecosystem services and functions. Often wetland-specific data in Africa is only available on a per country basis or as point data. Since wetlands are challenging to map, their accuracies are not well considered in global land cover products. In this paper we describe a methodology to map wetlands using well-corrected 250-meter MODIS time-series data for the year 2002 and over a 360,000 km2 large study area in western Burkina Faso and southern Mali (West Africa). A MODIS-based spectral index table is used to map basic wetland morphology classes. The index uses the wet season near infrared (NIR) metrics as a surrogate for flooding, as a function of the dry season chlorophyll activity metrics (as NDVI). Topographic features such as sinks and streamline areas were used to mask areas where wetlands can potentially occur, and minimize spectral confusion. 30-m Landsat trajectories from the same year, over two reference sites, were used for accuracy assessment, which considered the area-proportion of each class mapped in Landsat for every MODIS cell. We were able to map a total of five wetland categories. Aerial extend of all mapped wetlands (class “Wetland”) is 9,350 km2, corresponding to 4.3% of the total study area size. The classes “No wetland”/“Wetland” could be separated with very high certainty; the overall agreement (KHAT) was 84.2% (0.67) and 97.9% (0.59) for the two reference sites, respectively. The methodology described herein can be employed to render wide area base line information on wetland distributions in semi-arid West Africa, as a data-scarce region. The results can provide (spatially) interoperable information feeds for inter-zonal as well as local scale water assessments.
The overarching goal of this research was to explore accurate methods of mapping irrigated crops, where digital cadastre information is unavailable: (a) Boundary separation by object-oriented image segmentation using very high spatial resolution (2.5–5 m) data was followed by (b) identification of crops and crop rotations by means of phenology, tasselled cap, and rule-based classification using high resolution (15–30 m) bi-temporal data. The extensive irrigated cotton production system of the Khorezm province in Uzbekistan, Central Asia, was selected as a study region. Image segmentation was carried out on pan-sharpened SPOT data. Varying combinations of segmentation parameters (shape, compactness, and color) were tested for optimized boundary separation. The resulting geometry was validated against polygons digitized from the data and cadastre maps, analysing similarity (size, shape) and congruence. The parameters shape and compactness were decisive for segmentation accuracy. Differences between crop phenologies were analyzed at field level using bi-temporal ASTER data. A rule set based on the tasselled cap indices greenness and brightness allowed for classifying crop rotations of cotton, winter-wheat and rice, resulting in an overall accuracy of 80 %. The proposed field-based crop classification method can be an important tool for use in water demand estimations, crop yield simulations, or economic models in agricultural systems similar to Khorezm.
Mapping Bushfire Distribution and Burn Severity in West Africa Using Remote Sensing Observations
(2010)
Fire has long been considered to be the main ecological factor explaining the origin and maintenance of West African savannas. It has a very high occurrence in these savannas due to high human pressure caused by strong demographic growth and, concomitantly, is used to transform natural savannas into farmland and is also used as a provider of energy. This study was carried out with the support of the BIOTA project funded by the German ministry for Research and Education. The objective of this study is to establish the spatial and temporal distribution of bushfires during a long observation period from 2000 to 2009 as well as to assess fire impact on vegetation through mapping of the burn severity; based on remote sensing and field data collections. Remote sensing was used for this study because of the advantages that it offers in collecting data for long time periods and on different scales. In this case, the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument at 1km resolution is used to assess active fires, and understand the seasonality of fire, its occurrence and its frequency within the vegetation types on a regional scale. Landsat ETM+ imagery at 30 m and field data collections were used to define the characteristics of burn severity related to the biomass loss on a local scale. At a regional scale, the occurrence of fires and rainfall per month correlated very well (R2 = 0.951, r = -0.878, P < 0.01), which shows that the lower the amount of rainfall, the higher the fire occurrence and vice versa. In the dry season, four fire seasons were determined on a regional scale, namely very early fires, which announce the beginning of the fires, early and late fires making up the peak of fire in December/January and very late fires showing the end of the fire season and the beginning of the rainy season. Considerable fire activity was shown to take place in the vegetation zones between the Forest and the Sahel areas. Within these zones, parts of the Sudano-Guinean and the Guinean zones showed a high pixel frequency, i.e. fires occurred in the same place in many years. This high pixel frequency was also found in most protected areas in these zones. As to the kinds of land cover affected by fire, the highest fire occurrence is observed within the Deciduous woodlands and Deciduous shrublands. Concerning the burn severity, which was observed at a local scale, field data correlated closely with the ΔNBR derived from Landsat scenes of Pendjari National Park (R2 = 0.76). The correlation coefficient according to Pearson is r = 0.84 and according to Spearman-Rho, the correlation coefficient is r = 0.86. Very low and low burn severity (with ΔNBR value from 0 to 0.40) affected the vegetation weakly (0-35 percent of biomass loss) whereas moderate and high burn severity greatly affected the vegetation, leading to up to 100 percent of biomass loss, with the ΔNBR value ranging from 0.41 to 0.99. It can be seen from these results that remotely sensed images offer a tool to determine the fire distribution over large regions in savannas and that the Normalised Burn Ratio index can be applied to West Africa savannas. The outcomes of this thesis will hopefully contribute to understanding and, eventually, improving fire regimes in West Africa and their response to climate change and changes in vegetation diversity.
The urban micro climate has been increasingly recognised as an important aspect for urban planning. Therefore, urban planners need reliable information on the micro climatic characteristics of the urban environment. A suitable spatial scale and large spatial coverage are important requirements for such information. This thesis presents a conceptual framework for the use of airborne hyperspectral data to support urban micro climate characterisation, taking into account the information needs of urban planning. The potential of hyperspectral remote sensing in characterising the micro climate is demonstrated and evaluated by applying HyMap airborne hyperspectral and height data to a case study of the German city of Munich. The developed conceptual framework consists of three parts. The first is concerned with the capabilities of airborne hyperspectral remote sensing to map physical urban characteristics. The high spatial resolution of the sensor allows to separate the relatively small urban objects. The high spectral resolution enables the identification of the large range of surface materials that are used in an urban area at up to sub-pixel level. The surface materials are representative for the urban objects of which the urban landscape is composed. These spatial urban characteristics strongly influence the urban micro climate. The second part of the conceptual framework provides an approach to use the hyperspectral surface information for the characterisation of the urban micro climate. This can be achieved by integrating the remote sensing material map into a micro climate model. Also spatial indicators were found to provide useful information on the micro climate for urban planners. They are commonly used in urban planning to describe building blocks and are related to several micro climatic parameters such as temperature and humidity. The third part of the conceptual framework addresses the combination and presentation of the derived indicators and simulation results under consideration of the planning requirements. Building blocks and urban structural types were found to be an adequate means to group and present the derived information for micro climate related questions to urban planners. The conceptual framework was successfully applied to a case study in Munich. Airborne hyperspectral HyMap data has been used to derive a material map at sub-pixel level by multiple endmember linear spectral unmixing. This technique was developed by the German Research Centre for Geosciences (GFZ) for applications in Dresden and Potsdam. A priori information on building locations was used to support the separation between spectrally similar materials used both on building roofs and non-built surfaces. In addition, surface albedo and leaf area index are derived from the HyMap data. The sub-pixel material map supported by object height data is then used to derive spatial indicators, such as imperviousness or building density. To provide a more detailed micro climate characterisation at building block level, the surface materials, albedo, leaf area index (LAI) and object height are used as input for simulations with the micro climate model ENVI-met. Concluding, this thesis demonstrated the potential of hyperspectral remote sensing to support urban micro climate characterisation. A detailed mapping of surface materials at sub-pixel level could be performed. This provides valuable, detailed information on a large range of spatial characteristics relevant to the assessment of the urban micro climate. The developed conceptual framework has been proven to be applicable to the case study, providing a means to characterise the urban micro climate. The remote sensing products and subsequent micro climatic information are presented at a suitable spatial scale and in understandable maps and graphics. The use of well-known spatial indicators and the framework of urban structural types can simplify the communication with urban planners on the findings on the micro climate. Further research is needed primarily on the sensitivity of the micro climate model towards the remote sensing based input parameters and on the general relation between climate parameters and spatial indicators by comparison with other cities.
This work presents a new method to measure model independent viscosities of inhomogeneous materials at high temperatures. Many mechanisms driving volcanic eruptions are strongly influenced by the viscous properties of the participating materials. Since an eruption takes place at temperatures at which these materials (predominantly silicate melts) are not completely molten, typically inhomogeneities, like e.g. equilibrium and non-equilibrium crystals, are present in the system. In order to incorporate such inhomogeneities into objective material parameters the viscosity measurement is based on a rotational viscometer in a wide gap Couette setup. The gap size between the two concentric cylinders was designed as large as possible in order to account for the inhomogeneities. The emerging difficulties concerning the model independent data reduction from measured values to viscosities are solved using an appropriate interpolation scheme. The method was applied to a material representative for the majority of volcanic eruptions on earth: a typical continental basaltic rock (Billstein/Rhön/Germany). The measured viscosities show a strong shear rate dependency, which surprises, because basaltic melt has been, until now, assumed to behave as a Newtonian fluid. Since a non-Newtonian material shows a very different relaxation behavior in the Couette motion compared to a Newtonian one (which, ultimately, does not show any), and a strong relaxation signal was recorded during viscosity measurements, the equations of Couette motion were investigated. The time dependent stress distribution in a material due to a quasi step-like velocity change at the inner Couette radius (i.e. the spindle) was considered. The results show that a material combining a linear shear modulus and a Newtonian viscosity -- a Maxwell material -- cannot quantify the relaxation behavior. This could be considered as a hint, that the widely used Maxwell relaxation times cannot be applied as a 1:1 mapping from microscopic considerations to macroscopic situations.
Taxonomy and palaeoecology of the Cenomanian-Turonian macro-invertebrate from eastern Sinai, Egypt
(2010)
The present study concerened with taxonomy and palaeoecology of the Cenomanian-Turonian macrobenthic fauna which includes bivalves, gastropods, echinoids, and coral. In addtion, cephalopods are also taken in consideration. 144 taxa are identified and systematically described. Palaeoecological and taphonomic anylsis of the statistically sampled macrobenthos are also discussed. The biostratigraphic sequences along the Cenomanian-Turonian rocks were carried out on the basis of ammonites and other macrobenthic fauna such as corals and bivalves. In order to reconstruct benthic association, 41 statistically sampled were subjected to cluster ananlysis by using Past Programm (Hammer et al., 2001). 10 association and three assemblages were described in order to reconstruct the different depositional enviroments.
Surveys by the Universities of Wuerzburg and Berlin, starting in the 1970´s have revealed the existence of palaeolakes in remote areas in Niger. Initial research has shown that the sediments found are suitable for reconstructing its late quaternary palaeoenvironment. Although a high number of investigations focused on the succession of climatological conditions in the Central Sahara, some uncertainties still exist as the results show discontinuities and mostly are of low temporal and spatial
resolution.
Two expeditions in 2005 and 2006 headed to the northeastern parts of Niger to investigate the known remains of palaeolakes and search some new and undetected ones. Samples were taken at several study sites in order to receive a complete picture of the Late Quaternary environmental settings and to produce high-resolution proxies for palaeoclimate modelling.
The most valuable and best-investigated study site is the sebkha of Seggedim, where a core of 15 meters length could be extracted which revealed a composition of high-resolution sections. Stratigraphical, structural and geochemical investigations as well as the analysis of thin sections allow the characterization of different environmental conditions from Early to Mid Holocene. Driven by climate and hydrogeological influence, the water body developed from a water pond of several metres depth within a stable, grass and shrub vegetated landscape, to an alternating freshwater lake in a more dynamic environmental setting. Radiocarbon dates set the beginning of the stage at about 10.6 ka cal BP, with an exceptionally stable regime to 6.6 ka cal BP (at 12.6 metres’ depth), when a major change in the sedimentation regime of the basin is recorded in the core. Increased erosion, likely due to decreased vegetation cover within the basin, led to the siltation/filling of the lake within a few hundred years and the subsequent development of a sebkha/salt pan due to massive evaporation. Due to the lack of dateable material in the upper core section, the termination of the lake stage and the onset of the subsequent sebkha stage cannot be determined precisely but can be narrowed to a period around 6 ka BP.
The results obtained from the core are compared with those from terrestrial and lacustrine sediments from outside the depression, situated a few hundred kilometres further to the north. These supplementary study sites are required to validate the information obtained from the coring. Within the plateau landscape of Djado, Mangueni and Tchigai, two depressions and a valley containing lacustrine deposits, were investigated for palaeoenvironmental reconstruction. Depending on modifying local factors, these sediment archives were of shorter existence than IX the lake, but reveal additional information about the landscape dynamics from Early to Mid Holocene.
A damming situation within a small tributary at Enneri Achelouma led to lacustrine sedimentation conditions at Early Holocene in the upper reaches of the valley. The remnants of the lacustrine accumulations show distinct changes in the environmental conditions within the small catchment, as the archive immediately responded to local climate-induced changes of precipitation. Radiocarbon dating of the deposited sediments revealed ages from 8780 ± 260 cal a BP to 9480 ± 80 cal a BP.
The sites of Yoo Ango and Fabérgé show a completely different sedimentation milieu as they consist of basins within the foothills of the Tchigai. The study sites show increased catchment sizes, probably extending towards the Tchigai massif and are most likely influenced by groundwater charge. The widespread occurrence of wind shaped relicts and the limited amount of lacustrine remnants indicate a generally high aeolian activity in both areas. Only in wind sheltered spots, parts of the lacustrine sequences were preserved, that show ages spanning from Early to Mid Holocene (9440 ± 140 cal a BP – 6810 ±140 cal a BP) and give additional evidence of fires from pre-LGM periods. Although intensively weathered, all profiles indicate distinct changes in the sedimentation conditions by alternating geochemical values and the mineralogical composition.
The information obtained from the records investigated in this work confirms the heterogeneity of reconstructed environmental succession in the Central Sahara. The Mid Holocene rapid (within decades) and uniform development from more humid to extremely arid environmental conditions cannot be confirmed for the Central Sahara. In addition, a division of Early and Mid Holocene wet periods cannot be confirmed, either. Actually, the evidences obtained from the palaeoenvironmental reconstructions revealed major variations in the timing and extend of lacustrine and aeolian periods. Evidently, a transitional time has existed between 7 to 5 ka BP where alternating influences prevailed. This is indicated by the varying sedimentation conditions in the Seggedim depression as well as the evidence of soil properties on a fossil dune, with a time of deposition dated to 6200 ± 400 cal a BP and the removal of lacustrine Sediments at the Seeterrassental at Mid Holocene. In respect to provide a complete picture of landscape succession and to avoid misinterpretation, the investigation of several dissimilar spots within a designated study area is prerequisite for further investigations.
Understanding the mechanisms of fragmentation within silicate melts is of great interest not only for material science, but also for volcanology, particularly regarding molten fuel coolant-interactions (MFCIs). Therefore edge-on hammer impact experiments (HIEs) have been carried out in order to analyze the fracture dynamics in well defined targets by applying a Cranz-Schardin highspeed camera technique. This thesis presents the corresponding results and provides a thorough insight into the dynamics of fragmentation, particularly focussing on the processes of energy dissipation. In HIEs two main classes of cracks can be identified, characterized by completely different fracture mechanisms: Shock wave induced “damage cracks” and “normal cracks”, which are exclusively caused by shear-stresses. This dual fracture situation is taken into account by introducing a new concept, according to which the crack class-specific fracture energies are linearly correlated with the corresponding fracture areas. The respective proportionality constants - denoted “fracture surface energy densities” (FSEDs) - have been quantified for all studied targets under various constraints. By analyzing the corresponding high speed image sequences and introducing useful dynamic parameters it has been possible to specify and describe in detail the evolution of fractures and, moreover, to quantify the energy dissipation rates during the fragmentation. Additionally, comprehensive multivariate statistical analyses have been carried out which have revealed general dependencies of all relevant fracture parameters as well as characteristics of the resulting particles. As a result, an important principle of fracture dynamics has been found, referred to as the “local anisotropy effect”: According to this principle, the fracture dynamics in a material is significantly affected by the location of directed stresses. High local stress gradients cause a more stable crack propagation and consequently a reduction of the energy dissipation rates. As a final step, this thesis focusses on the volcanological conclusions which can be drawn on the basis of the presented HIE results. Therefore fragments stemming from HIEs have been compared with natural and experimental volcanic ash particles of basaltic Grimsvötn and rhyolitic Tepexitl melts. The results of these comparative particle analyses substantiate HIEs to be a very suitable method for reproducing the MFCI loading conditions in silicate melts and prove the FSED concept to be a model which is well transferable to volcanic fragmentation processes.
Climate change assessment in Southeast Asia and implications for agricultural production in Vietnam
(2011)
For many years, the study of climatic changes and variations has become the main objective of climatic research, as has been appreciated in the IPCC's reports and several publications regarding climatic evolution on different space-time scales. Since the 80's, many research groups have generated the extensive database from which the analysis of temperature, precipitation and other climatic parameters has been performed on a global scale (Jones et al., 1986; Hansen and Lebedeff, 1987, 1988; Vinnikov et al., 1987, 1990). The most important result of these research projects is the evidence of global warming during the 20th century, especially in the last two decades. However, numerous challenges still exist about the structure and dimension of the climatic change on a considerable scale. Therefore, it is necessary to carry out studies on a local and regional scale that allow for a more precise evaluation of the global warming phenomenon. A statistical analysis approach was developed to identify systematic differences between large-scale climatic variable from the General Circulation Models (GCM), NCEP, CRU re-analysis data set and climatic parameters (temperature and precipitation data). Models are able to satisfactorily reproduce the spatial patterns of the regional temperature and precipitation field. The response of the climate system to various emission scenario simulated by the GCM was used to analyze and predict the local climate change. The main objective of this study is to analysis the time evolution of the annual and seasonal temperature and precipitation during the 21st century and in order to contribute to our knowledge of temperature and precipitation trends over the century on a regional scale, not only in Southeast Asia but also in Vietnam; the study focuses to develop a dynamical – statistical model describing the relationship between the major climate variation and agricultural production in Vietnam. This study will be an important contribution to the present-day assessment of climate change impacts in the low latitudes. Regional scenarios of climate change, including both rainfall and mean temperature were then used to assess the impact of climate change on crop production in the region in order to evaluate the vulnerability of the system to global warming. Climate change has adverse impacts on the socio - economic development of all nations. But the degree of the impact will vary across nations. It is expected that changes in the earth's climate will impact on developing countries like Vietnam, in particular, hardest because their economies are strongly dependent on crude forms of natural resources and their economic structure is less flexible to adjust to such drastic changes. In Chapter 1: Introduction and background I describe in general terms climate, climate change, climate change model with benefits and problems. Chapter 2: methodology discusses the methods including interpolation, validation, clustering, correlation and regression which were applied in the study. Chapter 3 and chapter 4 describe the database and study area. The most important is chapter 5 Results. The last is chapter 6 Conclusion and outlook followed by the reference list and an appendix.
The present study concerned mainly on the source, facies, and sedimentary environments of the Middle to Upper Jurassic strata in the Kerman and Tabas areas, east-central Iran. The composition of sandstones, and heavy mineral analysis point to pre-existing sedimentary, low, middle to upper rank metamorphic, and plutonic rocks of the Kalmard, Posht-e-Badam, Bayazeh, and Zarand-Kerman areas as the source rocks. According to the diagram of WELTJE et al. (1998), most samples from the Middle-Upper Jurassic rocks suggest a moderate to high elevation of the source area, and indicate a semi-arid and mediterranean to sub-humid climate. In the Qt-F-L ternary diagrams of DICKINSON et al. (1983), most point counting data from the Lower Siliciclastic Member and the top of the Hojedk Formation plot in the recycled orogen (Quartzose recycled) area of the diagram. The sandstones in this area can be interpreted as being derived from the Mid-Cimmerian Movements. Sixteen different types of siliciclastic-carbonate, and evaporatic sedimentary environments have been recognized. Thirty-nine macroinvertebrate taxa have been identified. Ten ichnotaxa have been taxonomically described from the Middle to Upper Jurassic rocks. Quite likely, before rotation of CEIM which were associated with counterclockwise block-rotation, equivalent rocks of the Bidou Formation occurred along the tectonic zone between the Yazd and the Tabas blocks (probably during the Middle Jurassic to Lower Cretaceous). However, from the Cretaceous onwards, most of the Bidou Formation has been removed by a combination of strike-slip and reverse movements of the Kashmar-Kerman tectonic zone. Roughly, these block-rotation movements occurred after the Cretaceous. During the Middle to Upper Jurassic, the tectonic activities were vertical movements producing the sedimentary pattern in the CEIM.
Estimating flood risks and managing disasters combines knowledge in climatology, meteorology, hydrology, hydraulic engineering, statistics, planning and geography - thus a complex multi-faceted problem. This study focuses on the capabilities of multi-source remote sensing data to support decision-making before, during and after a flood event. With our focus on urbanized areas, sample methods and applications show multi-scale products from the hazard and vulnerability perspective of the risk framework. From the hazard side, we present capabilities with which to assess flood-prone areas before an expected disaster. Then we map the spatial impact during or after a flood and finally, we analyze damage grades after a flood disaster. From the vulnerability side, we monitor urbanization over time on an urban footprint level, classify urban structures on an individual building level, assess building stability and quantify probably affected people. The results show a large database for sustainable development and for developing mitigation strategies, ad-hoc coordination of relief measures and organizing rehabilitation.
This study aimed to optimise the application, efficiency and interpretability of quasi-3D resistivity imaging for investigating the heterogeneous permafrost distribution at mountain sites by a systematic forward modelling approach. A three dimensional geocryologic model, representative for most mountain permafrost settings, was developed. Based on this geocryologic model quasi-3D models were generated by collating synthetic orthogonal 2D arrays, demonstrating the effects of array types and electrode spacing on resolution and interpretability of the inversion results. The effects of minimising the number of 2D arrays per quasi-3D grid were tested by enlarging the spacing between adjacent lines and by reducing the number of perpendicular tie lines with regard to model resolution and loss of information value. Synthetic and measured quasi-3D models were investigated with regard to the lateral and vertical resolution, reliability of inverted resistivity values, the possibility of a quantitative interpretation of resistivities and the response of the inversion process on the validity of quasi-3D models. Results show that setups using orthogonal 2D arrays with electrode spacings of 2 m and 3 m are capable of delineating lateral heterogeneity with high accuracy and also deliver reliable data on active layer thickness. Detection of permafrost thickness, especially if the permafrost base is close to the penetration depth of the setups, and the reliability of absolute resistivity values emerged to be a weakness of the method. Quasi-3D imaging has proven to be a promising tool for investigating permafrost in mountain environments especially for delineating the often small-scale permafrost heterogeneity, and therefore provides an enhanced possibility for aligning permafrost distribution with site specific surface properties and morphological settings.
Increasing urbanisation is one of the biggest pressures to vegetation in the City of Cape Town. The growth of the city dramatically reduced the area under indigenous Fynbos vegetation, which remains in isolated fragments. These are subject to a number of threats including atmospheric deposition, atypical fire cycles and invasion by exotic plant and animal species. Especially the Port Jackson willow (Acacia saligna) extensively suppresses the indigenous Fynbos vegetation with its rapid growth.
The main objective of this study was to investigate indicators for a quick and early prediction of the health of the remaining Fynbos fragments in the City of Cape Town with help of remote sensing.
First, the productivity of the vegetation in response to rainfall was determined. For this purpose, the Enhanced Vegetation Index (EVI), derived from Terra MODIS data with a spatial resolution of 250m, and precipitation data of 19 rainfall stations for the period from 2000 till 2008 were used. Within the scope of a flexible regression between the EVI data and the precipitation data, different lags of the vegetation response to rainfall were analysed. Furthermore, residual trends (RESTREND) were calculated, which result from the difference between observed EVI and the one predicted by precipitation. Negative trends may suggest a degradation of the habitats. In addition, the so-called Rain-use Efficiency (RUE) was tested in this context. It is defined as the ratio between net primary production (NPP) – represented by the annual sum of EVI – and the annual rainfall sum. These indicators were analysed for their suitability to determine the health of the indigenous Fynbos vegetation.
Furthermore, the degree of dispersal of invasive species especially the Acacia saligna was investigated. With the specific characteristics of the tested indicators and the spectral signature of Acacia saligna, i.e. its unique reflectance over the course of the year, the dispersal was estimated. Since the growth of invasive species dramatically reduces the biodiversity of the fragments, their presence is an important factor for the condition of ecosystem health.
This work focused on 11 test sites with an average size of 200ha, distributed over the whole area of the City of Cape Town. Five of these fragments are under conservation and the others shall be protected in the near future, too, which makes them of special interest. In January 2010, fieldwork was undertaken in order to investigate the state and composition of the local vegetation.
The results show promising indicators for the assessment of ecosystem health. The coefficients of determination of the EVI-rainfall regression for Fynbos are minor, because the reaction of this vegetation type to rainfall is considerably lower than the one of the invasive species. Thus, a good distinction between indigenous and alien vegetation is possible on the basis of this regression. On the other hand, the RESTREND method, for which the regression forms the basis, is only of limited use, since the significance of these trends is not given for Fynbos vegetation. Furthermore, the RUE has considerable potential for the assessment of ecosystem health in the study area. The Port Jackson willow has an explicitly higher EVI than the Fynbos vegetation and thus its RUE is more efficient for a similar amount of rainfall. However, it has to be used with caution, because local and temporal variability cannot be extinguished in the study area over the rather short MODIS time series.
These results display that the interpretation of the indicators has to be conducted differently from the literature, because the element of invasive species was not considered in most of the previous papers. An increase in productivity is not necessarily equivalent with an improvement in health of the fragment, but can indicate a dispersal of Acacia saligna. This shows the general problem of the term ‘degradation’ which in most publications so far is only measured by productivity and other factors like invasive species are disregarded.
On the basis of the EVI-rainfall regression and statistical measures of the EVI, the distribution of invasive species could be delineated. Generally, a strong invasion of the Port Jackson willow was discovered on the test sites. The results display that a reasoned and sustainable management of the fragments is essential in order to prevent the suppression of the indigenous Fynbos vegetation by Acacia saligna. For this purpose, remote sensing can give an indication which areas changed so that specific field surveys can be undertaken and subsequent management measures can be determined.
U.S. and German Approaches to Regulating Retail Development: Urban Planning Tools and Local Policies
(2012)
This dissertation examines retail development regulation in the U.S. and in Germany, comparing the various urban planning tools and policies in use by municipal governments. These similarities and differences are explored through research into three case study cities in each country, with special attention paid to how these governments regulate large-scale or "big box" retail.
BACKGROUND: Climate change will probably alter the spread and transmission intensity of malaria in Africa. OBJECTIVES: In this study, we assessed potential changes in the malaria transmission via an integrated weather disease model.
METHODS: We simulated mosquito biting rates using the Liverpool Malaria Model (LMM). The input data for the LMM were bias-corrected temperature and precipitation data from the regional model (REMO) on a 0.5 degrees latitude longitude grid. A Plasmodium falciparum infection model expands the LMM simulations to incorporate information on the infection rate among children. Malaria projections were carried out with this integrated weather disease model for 2001 to 2050 according to two climate scenarios that include the effect of anthropogenic land-use and land-cover changes on climate.
RESULTS: Model-based estimates for the present climate (1960 to 2000) are consistent with observed data for the spread of malaria in Africa. In the model domain, the regions where malaria is epidemic are located in the Sahel as well as in various highland territories. A decreased spread of malaria over most parts of tropical Africa is projected because of simulated increased surface temperatures and a significant reduction in annual rainfall. However, the likelihood of malaria epidemics is projected to increase in the southern part of the Sahel. In most of East Africa, the intensity of malaria transmission is expected to increase. Projections indicate that highland areas that were formerly unsuitable for malaria will become epidemic, whereas in the lower-altitude regions of the East African highlands, epidemic risk will decrease.
CONCLUSIONS: We project that climate changes driven by greenhouse-gas and land-use changes will significantly affect the spread of malaria in tropical Africa well before 2050. The geographic distribution of areas where malaria is epidemic might have to be significantly altered in the coming decades.
The 2007 flood in the Sahel: causes, characteristics and its presentation in the media and FEWS NET
(2012)
During the rainy season in 2007, reports about exceptional rains and floodings in the Sahel were published in the media, especially in August and September. Institutions and organizations like the World Food Programme (WFP) and FEWS NET put the events on the agenda and released alerts and requested help. The partly controversial picture was that most of the Sahel faced a crisis caused by widespread floodings. Our study shows that the rainy season in 2007 was exceptional with regard to rainfall amount and return periods. In many areas the event had a return period between 1 and 50 yr with high spatial heterogeneity, with the exception of the Upper Volta basin, which yielded return periods of up to 1200 yr. Despite the strong rainfall, the interpretation of satellite images show that the floods were mainly confined to lakes and river beds. However, the study also proves the difficulties in assessing the meteorological processes and the demarcation of flooded areas in satellite images without ground truthing. These facts and the somewhat vague and controversial reports in the media and FEWS NET demonstrate that it is crucial to thoroughly analyze such events at a regional and local scale involving the local population.
Home on the Range: Factors Explaining Partial Migration of African Buffalo in a Tropical Environment
(2012)
Partial migration (when only some individuals in a population undertake seasonal migrations) is common in many species and geographical contexts. Despite the development of modern statistical methods for analyzing partial migration, there have been no studies on what influences partial migration in tropical environments. We present research on factors affecting partial migration in African buffalo (Syncerus caffer) in northeastern Namibia. Our dataset is derived from 32 satellite tracking collars, spans 4 years and contains over 35,000 locations. We used remotely sensed data to quantify various factors that buffalo experience in the dry season when making decisions on whether and how far to migrate, including potential man-made and natural barriers, as well as spatial and temporal heterogeneity in environmental conditions. Using an information-theoretic, non-linear regression approach, our analyses showed that buffalo in this area can be divided into 4 migratory classes: migrants, non-migrants, dispersers, and a new class that we call "expanders". Multimodel inference from least-squares regressions of wet season movements showed that environmental conditions (rainfall, fires, woodland cover, vegetation biomass), distance to the nearest barrier (river, fence, cultivated area) and social factors (age, size of herd at capture) were all important in explaining variation in migratory behaviour. The relative contributions of these variables to partial migration have not previously been assessed for ungulates in the tropics. Understanding the factors driving migratory decisions of wildlife will lead to better-informed conservation and land-use decisions in this area.
Due to their negative water budget most recent semi-/arid regions are characterized by vast evaporates (salt lakes and salty soils). We recently identified those hyper-saline environments as additional sources for a multitude of volatile halogenated organohalogens (VOX). These compounds can affect the ozone layer of the stratosphere and play a key role in the production of aerosols. A remote sensing based analysis was performed in the Southern Aral Sea basin, providing information of major soil types as well as their extent and spatial and temporal evolution. VOX production has been determined in dry and moist soil samples after 24 h. Several C1- and C2 organohalogens have been found in hyper-saline topsoil profiles, including CH3Cl, CH3Br, CHBr3 and CHCl3. The range of organohalogens also includes trans-1,2-dichloroethene (DCE), which is reported here to be produced naturally for the first time. Using MODIS time series and supervised image classification a daily production rate for DCE has been calculated for the 15 000 km\(^2\) ranging research area in the southern Aralkum. The applied laboratory setup simulates a short-term change in climatic conditions, starting from dried-out saline soil that is instantly humidified during rain events or flooding. It describes the general VOX production potential, but allows only for a rough estimation of resulting emission loads. VOX emissions are expected to increase in the future since the area of salt affected soils is expanding due to the regressing Aral Sea. Opportunities, limits and requirements of satellite based rapid change detection and salt classification are discussed.
Objective: The objective of this study was to investigate the applicability of microanalytical methods with high spatial resolution to the characterization of the composition and corrosion behavior of two bracket systems.
Material and methods: The surfaces of six nickel-free brackets and six nickel-containing brackets were examined for signs of corrosion and qualitative surface analysis using an electron probe microanalyzer (EPMA), prior to bonding to patient's tooth surfaces and four months after clinical use. The surfaces were characterized qualitatively by secondary electron (SE) images and back scattered electron (BSE) images in both compositional and topographical mode. Qualitative and quantitative wavelength-dispersive analyses were performed for different elements, and by utilizing qualitative analysis the relative concentration of selected elements was mapped two-dimensionally. The absolute concentration of the elements was determined in specially prepared brackets by quantitative analysis using pure element standards for calibration and calculating correction-factors (ZAF).
Results: Clear differences were observed between the different bracket types. The nickel-containing stainless steel brackets consist of two separate pieces joined by a brazing alloy. Compositional analysis revealed two different alloy compositions, and reaction zones on both sides of the brazing alloy. The nickel-free bracket was a single piece with only slight variation in element concentration, but had a significantly rougher surface. After clinical use, no corrosive phenomena were detectable with the methods applied. Traces of intraoral wear at the contact areas between the bracket slot and the arch wire were verified. Conclusion: Electron probe microanalysis is a valuable tool for the characterization of element distribution and quantitative analysis for corrosion studies.
Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region’s area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.
The Mediterranean area reveals a strong vulnerability to future climate change due to a high exposure to projected impacts and a low capacity for adaptation highlighting the need for robust regional or local climate change projections, especially for extreme events strongly affecting the Mediterranean environment. The prevailing study investigates two major topics of the Mediterranean climate variability: the analysis of dynamical downscaling of present-day and future temperature and precipitation means and extremes from global to regional scale and the comprehensive investigation of temperature and rainfall extremes including the estimation of uncertainties and the comparison of different statistical methods for precipitation extremes. For these investigations, several observational datasets of CRU, E-OBS and original stations are used as well as ensemble simulations of the regional climate model REMO driven by the coupled global general circulation model ECHAM5/MPI-OM and applying future greenhouse gas (GHG) emission and land degradation scenarios.
Cu- and Mn-bearing tourmalines from Brazil and Mozambique were characterised chemically (EMPA and LA-ICP-MS) and by X-ray single-crystal structure refinement. All these samples are rich in Al, Li and F (fluor-elbaite) and contain significant amounts of CuO (up to ~1.8 wt%) and MnO (up to ~3.5 wt%). Structurally investigated samples show a pronounced positive correlation between the <Y-O> distances and the (Li + Mn\(^{2+}\) + Cu + Fe\(^{2+}\)) content (apfu) at this site with R\(^2\) = 0.90. An excellent negative correlation exists between the <Y-O> distances and the Al\(_2\)O\(_3\) content (R\(^2\) = 0.94). The samples at each locality generally show a strong negative correlation between the X-site vacancies and the (MnO + FeO) content. The Mn content in these tourmalines depends on the availability of Mn, on the formation temperature, as well as on stereochemical constraints. Because of a very weak correlation between MnO and CuO we believe that the Cu content in tourmaline is essentially dependent on the availability of Cu and on stereochemical constraints.
A modified setup featuring high speed high resolution data and video recording was developed to obtain detailed information on trigger and heat transfer times during explosive molten fuel-coolant-interaction (MFCI). MFCI occurs predominantly in configurations where water is entrapped by hot melt. The setup was modified to allow direct observation of the trigger and explosion onset. In addition the influences of experimental control and data acquisition can now be more clearly distinguished from the pure phenomena. More precise experimental studies will facilitate the description of MFCI thermodynamics.
Spatio-Temporal Analysis of Droughts in Semi-Arid Regions by Using Meteorological Drought Indices
(2013)
Six meteorological drought indices including percent of normal (PN), standardized precipitation index (SPI), China-Z index (CZI), modified CZI (MCZI), Z-Score (Z), the aridity index of E. de Martonne (I) are compared and evaluated for assessing spatio-temporal dynamics of droughts in six climatic regions in Iran. Results indicated that by consideration of the advantages and disadvantages of the mentioned drought predictors in Iran, the Z-Score, CZI and MCZI could be used as a good meteorological drought predictor. Depending on the month, the length of drought and climatic conditions of the region, they are an alternative to the SPI that has limitations both because of only a few available long term data series in Iran and its complex structure.
The natural environment and livelihoods in the Lower Mekong Basin (LMB) are significantly affected by the annual hydrological cycle. Monitoring of soil moisture as a key variable in the hydrological cycle is of great interest in a number of Hydrological and agricultural applications. In this study we evaluated the quality and spatiotemporal variability of the soil moisture product retrieved from C-band scatterometers data across the LMB sub-catchments. The soil moisture retrieval algorithm showed reasonable performance in most areas of the LMB with the exception of a few sub-catchments in the eastern parts of Laos, where the land cover is characterized by dense vegetation. The best performance of the retrieval algorithm was obtained in agricultural regions. Comparison of the available in situ evaporation data in the LMB and the Basin Water Index (BWI), an indicator of the basin soil moisture condition, showed significant negative correlations up to R = −0.85. The inter-annual variation of the calculated BWI was also found corresponding to the reported extreme hydro-meteorological events in the Mekong region. The retrieved soil moisture data show high correlation (up to R = 0.92) with monthly anomalies of precipitation in non-irrigated regions. In general, the seasonal variability of soil moisture in the LMB was well captured by the retrieval method. The results of analysis also showed significant correlation between El Niño events and the monthly BWI anomaly measurements particularly for the month May with the maximum correlation of R = 0.88.
The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass.
This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure.
The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.
Agriculture is mankind’s primary source of food production and plays the key role for cereal supply to humanity. One of the future challenges will be to feed a constantly growing population, which is expected to reach more than nine billion by 2050. The potential to expand cropland is limited, and enhancing agricultural production efficiency is one important means to meet the future food demand. Hence, there is an increasing demand for dependable, accurate and comprehensive agricultural intelligence on crop production. The value of satellite earth observation (EO) data for agricultural monitoring is well recognized. One fundamental requirement for agricultural monitoring is routinely updated information on crop acreage and the spatial distribution of crops. With the technical advancement of satellite sensor systems, imagery with higher temporal and finer spatial resolution became available. The classification of such multi-temporal data sets is an effective and accurate means to produce crop maps, but methods must be developed that can handle such large and complex data sets. Furthermore, to properly use satellite EO for agricultural production monitoring a high temporal revisit frequency over vast geographic areas is often necessary. However, this often limits the spatial resolution that can be used. The challenge of discriminating pixels that correspond to a particular crop type, a prerequisite for crop specific agricultural monitoring, remains daunting when the signal encoded in pixels stems from several land uses (mixed pixels), e.g. over heterogeneous landscapes where individual fields are often smaller than individual pixels.
The main purposes of the presented study were (i) to assess the influence of input dimensionality and feature selection on classification accuracy and uncertainty in object-based crop classification, (ii) to evaluate if combining classifier algorithms can improve the quality of crop maps (e.g. classification accuracy), (iii) to assess the spatial resolution requirements for crop identification via image classification.
Reporting on the map quality is traditionally done with measures that stem from the confusion matrix based on the hard classification result. Yet, these measures do not consider the spatial variation of errors in maps. Measures of classification uncertainty can be used for this purpose, but they have attained only little attention in remote sensing studies. Classifier algorithms like the support vector machine (SVM) can estimate class memberships (the so called soft output) for each classified pixel or object. Based on these estimations, measures of classification uncertainty can be calculated, but it has not been analysed in detail, yet, if these are reliable in predicting the spatial distribution of errors in maps. In this study, SVM was applied for the classification of agricultural crops in irrigated landscapes in Middle Asia at the object-level. Five different categories of features were calculated from RapidEye time series data as classification input. The reliability of classification uncertainty measures like entropy, derived from the soft output of SVM, with regard to predicting the spatial distribution of error was evaluated. Further, the impact of the type and dimensionality of the input data on classification uncertainty was analysed. The results revealed that SMVs applied to the five feature categories separately performed different in classifying different types of crops. Incorporating all five categories of features by concatenating them into one stacked vector did not lead to an increase in accuracy, and partly reduced the model performance most obviously because of the Hughes phenomena. Yet, applying the random forest (RF) algorithm to select a subset of features led to an increase of classification accuracy of the SVM. The feature group with red edge-based indices was the most important for general crop classification, and the red edge NDVI had an outstanding importance for classifying crops. Two measures of uncertainty were calculated based on the soft output from SVM: maximum a-posteriori probability and alpha quadratic entropy. Irrespective of the measure used, the results indicate a decline in classification uncertainty when a dimensionality reduction was performed. The two uncertainty measures were found to be reliable indicators to predict errors in maps. Correctly classified test cases were associated with low uncertainty, whilst incorrectly test cases tended to be associated with higher uncertainty.
The issue of combining the results of different classifier algorithms in order to increase classification accuracy was addressed. First, the SVM was compared with two other non-parametric classifier algorithms: multilayer perceptron neural network (MLP) and RF. Despite their comparatively high classification performance, each of the tested classifier algorithms tended to make errors in different parts of the input space, e.g. performed different in classifying crops. Hence, a combination of the complementary outputs was envisaged. To this end, a classifier combination scheme was proposed, which is based on existing algebraic operators. It combines the outputs of different classifier algorithms at the per-case (e.g. pixel or object) basis. The per-case class membership estimations of each classifier algorithm were compared, and the reliability of each classifier algorithm with respect to classifying a specific crop class was assessed based on the confusion matrix. In doing so, less reliable classifier algorithms were excluded at the per-class basis before the final combination. Emphasis was put on evaluating the selected classification algorithms under limiting conditions by applying them to small input datasets and to reduced training sample sets, respectively. Further, the applicability to datasets from another year was demonstrated to assess temporal transferability. Although the single classifier algorithms performed well in all test sites, the classifier combination scheme provided consistently higher classification accuracies over all test sites and in different years, respectively. This makes this approach distinct from the single classifier algorithms, which performed different and showed a higher variability in class-wise accuracies. Further, the proposed classifier combination scheme performed better when using small training set sizes or when applied to small input datasets, respectively.
A framework was proposed to quantitatively define pixel size requirements for crop identification via image classification. That framework is based on simulating how agricultural landscapes, and more specifically the fields covered by one crop of interest, are seen by instruments with increasingly coarser resolving power. The concept of crop specific pixel purity, defined as the degree of homogeneity of the signal encoded in a pixel with respect to the target crop type, is used to analyse how mixed the pixels can be (as they become coarser) without undermining their capacity to describe the desired surface properties (e.g. to distinguish crop classes via supervised or unsupervised image classification). This tool can be modulated using different parameterizations to explore trade-offs between pixel size and pixel purity when addressing the question of crop identification. Inputs to the experiments were eight multi-temporal images from the RapidEye sensor. Simulated pixel sizes ranged from 13 m to 747.5 m, in increments of 6.5 m. Constraining parameters for crop identification were defined by setting thresholds for classification accuracy and uncertainty. Results over irrigated agricultural landscapes in Middle Asia demonstrate that the task of finding the optimum pixel size did not have a “one-size-fits-all” solution. The resulting values for pixel size and purity that were suitable for crop identification proved to be specific to a given landscape, and for each crop they differed across different landscapes. Over the same time series, different crops were not identifiable simultaneously in the season and these requirements further changed over the years, reflecting the different agro-ecological conditions the investigated crops were growing in. Results further indicate that map quality (e.g. classification accuracy) was not homogeneously distributed in a landscape, but that it depended on the spatial structures and the pixel size, respectively. The proposed framework is generic and can be applied to any agricultural landscape, thereby potentially serving to guide recommendations for designing dedicated EO missions that can satisfy the requirements in terms of pixel size to identify and discriminate crop types.
Regarding the operationalization of EO-based techniques for agricultural monitoring and its application to a broader range of agricultural landscapes, it can be noted that, despite the high performance of existing methods (e.g. classifier algorithms), transferability and stability of such methods remain one important research issue. This means that methods developed and tested in one place might not necessarily be portable to another place or over several years, respectively. Specifically in Middle Asia, which was selected as study region in this thesis, classifier combination makes sense due to its easy implementation and because it enhanced classification accuracy for classes with insufficient training samples. This observation makes it interesting for operational contexts and when field reference data availability is limited. Similar to the transferability of methods, the application of only one certain kind of EO data (e.g. with one specific pixel size) over different landscapes needs to be revisited and the synergistic use of multi-scale data, e.g. combining remote sensing imagery of both fine and coarse spatial resolution, should be fostered. The necessity to predict and control the effects of spatial and temporal scale on crop classification is recognized here as a major goal to achieve in EO-based agricultural monitoring.
Irrigated agriculture in the Khorezm region in the arid inner Aral Sea Basin faces enormous challenges due to a legacy of cotton monoculture and non-sustainable water use. Regional crop growth monitoring and yield estimation continuously gain in importance, especially with regard to climate change and food security issues. Remote sensing is the ideal tool for regional-scale analysis, especially in regions where ground-truth data collection is difficult and data availability is scarce. New satellite systems promise higher spatial and temporal resolutions. So-called light use efficiency (LUE) models are based on the fraction of photosynthetic active radiation absorbed by vegetation (FPAR), a biophysical parameter that can be derived from satellite measurements. The general objective of this thesis was to use satellite data, in conjunction with an adapted LUE model, for inferring crop yield of cotton and rice at field (6.5 m) and regional (250 m) scale for multiple years (2003-2009), in order to assess crop yield variations in the study area. Intensive field measurements of FPAR were conducted in the Khorezm region during the growing season 2009. RapidEye imagery was acquired approximately bi-weekly during this time. The normalized difference vegetation index (NDVI) was calculated for all images. Linear regression between image-based NDVI and field-based FPAR was conducted. The analyses resulted in high correlations, and the resulting regression equations were used to generate time series of FPAR at the RapidEye level. RapidEye-based FPAR was subsequently aggregated to the MODIS scale and used to validate the existing MODIS FPAR product. This step was carried out to evaluate the applicability of MODIS FPAR for regional vegetation monitoring. The validation revealed that the MODIS product generally overestimates RapidEye FPAR by about 6 to 15 %. Mixture of crop types was found to be a problem at the 1 km scale, but less severe at the 250 m scale. Consequently, high resolution FPAR was used to calibrate 8-day, 250 m MODIS NDVI data, this time by linear regression of RapidEye-based FPAR against MODIS-based NDVI. The established FPAR datasets, for both RapidEye and MODIS, were subsequently assimilated into a LUE model as the driving variable. This model operated at both satellite scales, and both required an estimation of further parameters like the photosynthetic active radiation (PAR) or the actual light use efficiency (LUEact). The latter is influenced by crop stress factors like temperature or water stress, which were taken account of in the model. Water stress was especially important, and calculated via the ratio of the actual (ETact) to the potential, crop-specific evapotranspiration (ETc). Results showed that water stress typically occurred between the beginning of May and mid-September and beginning of May and end of July for cotton and rice crops, respectively. The mean water stress showed only minor differences between years. Exceptions occurred in 2008 and 2009, where the mean water stress was higher and lower, respectively. In 2008, this was likely caused by generally reduced water availability in the whole region. Model estimations were evaluated using field-based harvest information (RapidEye) and statistical information at district level (MODIS). The results showed that the model at both the RapidEye and the MODIS scale can estimate regional crop yield with acceptable accuracy. The RMSE for the RapidEye scale amounted to 29.1 % for cotton and 30.4 % for rice, respectively. At the MODIS scale, depending on the year and evaluated at Oblast level, the RMSE ranged from 10.5 % to 23.8 % for cotton and from -0.4 % to -19.4 % for rice. Altogether, the RapidEye scale model slightly underestimated cotton (bias = 0.22) and rice yield (bias = 0.11). The MODIS-scale model, on the other hand, also underestimated official rice yield (bias from 0.01 to 0.87), but overestimated official cotton yield (bias from -0.28 to -0.6). Evaluation of the MODIS scale revealed that predictions were very accurate for some districts, but less for others. The produced crop yield maps indicated that crop yield generally decreases with distance to the river. The lowest yields can be found in the southern districts, close to the desert. From a temporal point of view, there were areas characterized by low crop yields over the span of the seven years investigated. The study at hand showed that light use efficiency-based modeling, based on remote sensing data, is a viable way for regional crop yield prediction. The found accuracies were good within the boundaries of related research. From a methodological viewpoint, the work carried out made several improvements to the existing LUE models reported in the literature, e.g. the calibration of FPAR for the study region using in situ and high resolution RapidEye imagery and the incorporation of crop-specific water stress in the calculation.
Nature-based tourism and ecotourism experienced a dynamic development over the past decade. While originally often described as specialized post-Fordist niche markets for ecologically aware and affluent target groups, in many regions they are nowadays characterized by a heterogeneous structure and the presence of a wide product range, from individual travels to package tours.
The present dissertation analyzes the structure and economic importance of tourism in two highly frequented protected areas in middle income countries, the Sian Ka’an Biosphere Reserve (SKBR) in Mexico and the Souss-Massa National Park (SMNP) in Morocco. Both areas are situated in close proximity to the most important package tour destinations Cancún (Mexico) and Agadir (Morocco) and are subject to high touristic use and development pressure. So far, the planning of a more sustainable tourism development is hampered by the lack of reliable data.
Based on demand-side surveys and income multipliers calculated with the help of regionalized input-output models, the visitor structure and economic impact of tourism in both protected areas are described. With regional income effects of approximately 1 million USD (SKBR) and approximately 1.9 million USD (SMNP), and resulting income equivalents of 1,348 and 5,218 persons, both the SKBR and the SMNP play an important—and often undervalued—role for the regional economies in underdeveloped rural peripheral regions of the countries.
Detailed analyses of the visitor structures show marked differences with regard to criteria such as travel organization, nature/protected area affinity and expenditures. With regard to planning and marketing of nature-based tourism, protected area managers and political decision-takers are advised to focus on ecologically and economically attractive visitor groups. Based on the results of the two case studies as well as existing tourism typologies from the literature, a classification scheme is presented that may be used for a more target-oriented development and marketing of nature-based tourism products.
Mapping threatened dry deciduous dipterocarp forest in South-east Asia for conservation management
(2014)
Habitat loss is the primary reason for species extinction, making habitat conservation a critical strategy for maintaining global biodiversity. Major habitat types, such as lowland tropical evergreen forests or mangrove forests, are already well represented in many conservation priorities, while others are underrepresented. This is particularly true for dry deciduous dipterocarp forests (DDF), a key forest type in Asia that extends from the tropical to the subtropical regions in South-east Asia (SE Asia), where high temperatures and pronounced seasonal precipitation patterns are predominant. DDF are a unique forest ecosystem type harboring a wide range of important and endemic species and need to be adequately represented in global biodiversity conservation strategies. One of the greatest challenges in DDF conservation is the lack of detailed and accurate maps of their distribution due to inaccurate open-canopy seasonal forest mapping methods. Conventional land cover maps therefore tend to perform inadequately with DDF. Our study accurately delineates DDF on a continental scale based on remote sensing approaches by integrating the strong, characteristic seasonality of DDF. We also determine the current conservation status of DDF throughout SE Asia. We chose SE Asia for our research because its remaining DDF are extensive in some areas but are currently degrading and under increasing pressure from significant socio-economic changes throughout the region. Phenological indices, derived from MODIS vegetation index time series, served as input variables for a Random Forest classifier and were used to predict the spatial distribution of DDF. The resulting continuous fields maps of DDF had accuracies ranging from R-2 = 0.56 to 0.78. We identified three hotspots in SE Asia with a total area of 156,000 km(2), and found Myanmar to have more remaining DDF than the countries in SE Asia. Our approach proved to be a reliable method for mapping DDF and other seasonally influenced ecosystems on continental and regional scales, and is very valuable for conservation management in this region.
In this work the potential of polarimetric Synthetic Aperture Radar (PolSAR) data of dual-polarized TerraSAR-X (HH/VV) and quad-polarized Radarsat-2 was examined in combination with multispectral Landsat 8 data for unsupervised and supervised classification of tundra land cover types of Richards Island, Canada. The classification accuracies as well as the backscatter and reflectance characteristics were analyzed using reference data collected during three field work campaigns and include in situ data and high resolution airborne photography. The optical data offered an acceptable initial accuracy for the land cover classification. The overall accuracy was increased by the combination of PolSAR and optical data and was up to 71% for unsupervised (Landsat 8 and TerraSAR-X) and up to 87% for supervised classification (Landsat 8 and Radarsat-2) for five tundra land cover types. The decomposition features of the dual and quad-polarized data showed a high sensitivity for the non-vegetated substrate (dominant surface scattering) and wetland vegetation (dominant double bounce and volume scattering). These classes had high potential to be automatically detected with unsupervised classification techniques.
Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation.
Defining the Spatial Resolution Requirements for Crop Identification Using Optical Remote Sensing
(2014)
The past decades have seen an increasing demand for operational monitoring of crop conditions and food production at local to global scales. To properly use satellite Earth observation for such agricultural monitoring, high temporal revisit frequency over vast geographic areas is necessary. However, this often limits the spatial resolution that can be used. The challenge of discriminating pixels that correspond to a particular crop type, a prerequisite for crop specific agricultural monitoring, remains daunting when the signal encoded in pixels stems from several land uses (mixed pixels), e.g., over heterogeneous landscapes where individual fields are often smaller than individual pixels. The question of determining the optimal pixel sizes for an application such as crop identification is therefore naturally inclined towards finding the coarsest acceptable pixel sizes, so as to potentially benefit from what instruments with coarser pixels can offer. To answer this question, this study builds upon and extends a conceptual framework to quantitatively define pixel size requirements for crop identification via image classification. This tool can be modulated using different parameterizations to explore trade-offs between pixel size and pixel purity when addressing the question of crop identification. Results over contrasting landscapes in Central Asia demonstrate that the task of finding the optimum pixel size does not have a “one-size-fits-all” solution. The resulting values for pixel size and purity that are suitable for crop identification proved to be specific to a given landscape, and for each crop they differed across different landscapes. Over the same time series, different crops were not identifiable simultaneously in the season and these requirements further changed over the years, reflecting the different agro-ecological conditions the crops are growing in. Results indicate that sensors like MODIS (250 m) could be suitable for identifying major crop classes in the study sites, whilst sensors like Landsat (30 m) should be considered for object-based classification. The proposed framework is generic and can be applied to any agricultural landscape, thereby potentially serving to guide recommendations for designing dedicated EO missions that can satisfy the requirements in terms of pixel size to identify and discriminate crop types.
Crop mapping in West Africa is challenging, due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. To address this challenge, we integrated high spatial resolution multi-temporal optical (RapidEye) and dual polarized (VV/VH) SAR (TerraSAR-X) data to map crops and crop groups in northwestern Benin using the random forest classification algorithm. The overall goal was to ascertain the contribution of the SAR data to crop mapping in the region. A per-pixel classification result was overlaid with vector field boundaries derived from image segmentation, and a crop type was determined for each field based on the modal class within the field. A per-field accuracy assessment was conducted by comparing the final classification result with reference data derived from a field campaign. Results indicate that the integration of RapidEye and TerraSAR-X data improved classification accuracy by 10%–15% over the use of RapidEye only. The VV polarization was found to better discriminate crop types than the VH polarization. The research has shown that if optical and SAR data are available for the whole cropping season, classification accuracies of up to 75% are achievable.
Remote sensing for disease risk profiling: a spatial analysis of schistosomiasis in West Africa
(2014)
Global environmental change leads to the emergence of new human health risks. As a consequence, transmission opportunities of environment-related diseases are transformed and human infection with new emerging pathogens increase. The main motivation for this study is the considerable demand for disease surveillance and monitoring in relation to dynamic environmental drivers. Remote sensing (RS) data belong to the key data sources for environmental modelling due to their capabilities to deliver spatially continuous information repeatedly for large areas with an ecologically adequate spatial resolution.
A major research gap as identified by this study is the disregard of the spatial mismatch inherent in current modelling approaches of profiling disease risk using remote sensing data. Typically, epidemiological data are aggregated at school or village level. However, these point data do neither represent the spatial distribution of habitats, where disease-related species find their suitable environmental conditions, nor the place, where infection has occurred. As a consequence, the prevalence data and remotely sensed environmental variables, which aim to characterise the habitat of disease-related species, are spatially disjunct.
The main objective of this study is to improve RS-based disease risk models by incorporating the ecological and spatial context of disease transmission. Exemplified by the analysis of the human schistosomiasis disease in West Africa, this objective includes the quantification of the impact of scales and ecological regions on model performance.
In this study, the conditions that modify the transmission of schistosomiasis are reviewed in detail. A conceptual underpinning of the linkages between geographical RS measures, disease transmission ecology, and epidemiological survey data is developed. During a field-based analysis, environmental suitability for schistosomiasis transmission was assessed on the ground, which is then quantified by a habitat suitability index (HSI) and applied to RS data. This conceptual model of environmental suitability is refined by the development of a hierarchical model approach that statistically links school-based disease prevalence with the ecologically relevant measurements of RS data. The statistical models of schistosomiasis risk are derived from two different algorithms; the Random Forest and the partial least squares regression (PLSR). Scale impact is analysed based on different spatial resolutions of RS data. Furthermore, varying buffer extents are analysed around school-based measurements. Three distinctive sites of Burkina Faso and Côte d’Ivoire are specifically modelled to represent a gradient of ecozones from dry savannah to tropical rainforest including flat and mountainous regions.
The model results reveal the applicability of RS data to spatially delineate and quantitatively evaluate environmental suitability for the transmission of schistosomiasis. In specific, the multi-temporal derivation of water bodies and the assessment of their riparian vegetation coverage based on high-resolution RapidEye and Landsat data proofed relevant. In contrast, elevation data and water surface temperature are constraint in their ability to characterise habitat conditions for disease-related parasites and freshwater snail species. With increasing buffer extent observed around the school location, the performance of statistical models increases, improving the prediction of transmission risk. The most important RS variables identified to model schistosomiasis risk are the measure of distance to water bodies, topographic variables, and land surface temperature (LST). However, each ecological region requires a different set of RS variables to optimise the modelling of schistosomiasis risk. A key result of the hierarchical model approach is its superior performance to explain the spatial risk of schistosomiasis.
Overall, this study stresses the key importance of considering the ecological and spatial context for disease risk profiling and demonstrates the potential of RS data. The methodological approach of this study contributes substantially to provide more accurate and relevant geoinformation, which supports an efficient planning and decision-making within the public health sector.
Information on the state of the terrestrial vegetation cover is important for several ecological, economical, and planning issues. In this regard, vegetation properties such as the type, vitality, or density can be described by means of continuous biophysical parameters. One of these parameters is the leaf area index (LAI), which is defined as half the total leaf area per unit ground surface area. As leaves constitute the interface between the biosphere and the atmosphere, the LAI is used to model exchange processes between plants and their environment. However, to account for the variability of ecosystems, spatially and temporally explicit information on LAI is needed both for monitoring and modeling applications.
Remote sensing aims at providing such information. LAI is commonly derived from remote sensing data by empirical-statistical or physical models. In the first approach, an empirical relationship between LAI measured in situ and the corresponding canopy spectral signature is established. Although this method achieves accurate LAI estimates, these relationships are only valid for the place and time at which the field data were sampled, which hampers automated LAI derivation. The physical approach uses a radiation transfer model to simulate canopy reflectance as a function of the scene’s geometry and of leaf and canopy parameters, from which LAI is derived through model inversion based on remote sensing data. However, this model inversion is not stable, as it is an under-determined and ill-posed problem.
Until now, LAI research focused either on the use of coarse resolution remote sensing data for global applications, or on LAI modeling over a confined area, mostly in forest and crop ecosystems, using medium to high spatial resolution data. This is why to date no study is available in which high spatial resolution data are used for LAI mapping in a heterogeneous, natural landscape such as alpine grasslands, although a growing amount of high spatial and temporal resolution remote sensing data would allow for an improved environmental monitoring. Therefore, issues related to model parameterization and inversion regularization techniques improving its stability have not yet been investigated for this ecosystem.
This research gap was taken up by this thesis, in which the potential of high spatial resolution remote sensing data for grassland LAI estimation based on statistical and radiation transfer modeling is analyzed, and the achieved accuracy and robustness of the two approaches is compared. The objectives were an ecosystem-adapted radiation transfer model set-up and an optimized LAI derivation in mountainous grassland areas. Multi-temporal LAI in situ measurements as well as time series of RapidEye data from 2011 and 2012 over the catchment of the River Ammer in the Bavarian alpine upland were used. In order to obtain accurate in situ data, a comparison of the LAI derivation algorithms implemented in the LAI-2000 PCA instrument with destructively measured LAI was performed first. For optimizing the empirical-statistical approach, it was then analyzed how the selection of vegetation indices and regression models impacts LAI modeling, and how well these models can be transferred to other dates. It was shown that LAI can be derived
with a mean accuracy of 80 % using contemporaneous field data, but that the accuracy decreases to on average 51 % when using these models on remote sensing data from other dates. The combined use of several data sets to create a regression which is used for LAI derivation at different points in time increased the LAI estimation accuracy to on average 65 %. Thus, reduced field measurement labor comes at the cost of LAI error rates being increased by 10 - 30 % as long as at least two campaigns are conducted. Further, it was shown that the use of RapidEye’s red edge channel improves the LAI derivation by on average 5.4 %.
With regard to physical LAI modeling, special interest lay in assessing the accuracy improvements that can be achieved through model set-up and inversion regularization techniques. First, a global sensitivity analysis was applied to the radiation transfer model in order to identify the most important model parameters and most sensitive spectral features. After model parameterization, several inversion regularizations, namely the use of a multiple sample solution, the additional use of vegetation indices, and the addition of noise, were analyzed. Further, an approach to include the local scene’s geometry in the retrieval process was introduced to account for the mountainous topography. LAI modeling accuracies of in average 70 % were achieved using the best combination of regularization techniques, which is in the upper range of accuracies that were achieved in the few existing other grassland studies based on in situ or air-borne measured hyperspectral data. Finally, further physically derived vegetation parameters and inversion uncertainty measures were evaluated in detail to identify challenging modeling conditions, which was mostly neglected in other studies. An increased modeling uncertainty for extremely high and low LAI values was observed. This indicates an insufficiently wide model parameterization and a canopy deviation from model assumptions on some fields. Further, the LAI modeling accuracies varied strongly between the different scenes. From this observation it can be deduced that the radiometric quality of the remote sensing data, which might be reduced by atmospheric effects or unexpected surface reflectances, exerts a high influence on the LAI modeling accuracy.
The major findings of the comparison between the empirical-statistical and physical LAI modeling approaches are the higher accuracies achieved by the empirical-statistical approach as long as contemporaneous field data are available, and the computationally efficiency of the statistical approach. However, when no or temporally unfitting in situ measurements are available, the physical approach achieves comparable or even higher accuracies. Furthermore, radiation transfer modeling enables the derivation of other leaf and canopy variables useful for ecological monitoring and modeling applications, as well as of pixel-wise uncertainty measures indicating the robustness and reliability of the model inversion and LAI derivation procedure. The established look-up tables can be used for further LAI derivation in Central European grassland also in other years.
The use of high spatial resolution remote sensing data for LAI derivation enables a reliable land cover classification and thus a reduced LAI mapping error due to misclassifications. Furthermore, the RapidEye pixels being smaller than individual fields allow for a radiation transfer model inversion over homogeneous canopies in most cases, as canopy gaps or field parcels can be clearly distinguished. However, in case of unexpected local surface conditions such as blooming, litter, or canopy gaps, high spatial resolution data show corresponding strong deviations in reflectance values and hence LAI estimation, which would be reduced using coarser resolution data through the balancing effect of the surrounding surface reflectances. An optimal pixel size with regard to modeling accuracy hence depends on the canopy and landscape structure. Furthermore, a reduced spatial resolution would enable a considerable acceleration of the LAI map derivation.
This illustration of the potential of RapidEye data and of the challenges associated to LAI derivation in heterogeneous grassland areas contributes to the development of robust LAI estimation procedures based on new and upcoming, spatially and temporally high resolution remote sensing imagery such as Landsat 8 and Sentinel-2.
Rapid population growth in West Africa has led to expansion in croplands due to the need to grow more food to meet the rising food demand of the burgeoning population. These expansions negatively impact the sub-region's ecosystem, with implications for water and soil quality, biodiversity and climate. In order to appropriately monitor the changes in croplands and assess its impact on the ecosystem and other environmental processes, accurate and up-to-date information on agricultural land use is required. But agricultural land use mapping (i.e. mapping the spatial distribution of crops and croplands) in West Africa has been challenging due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. This study, therefore, investigated the possibilities of improving agricultural land use mapping by utilizing optical satellite images with higher spatial and temporal resolution as well as images from Synthetic Aperture Radar (SAR) systems which are near-independent of weather conditions. The study was conducted at both watershed and regional scales.
At watershed scale, classification of different crop types in three watersheds in Ghana, Burkina Faso and Benin was conducted using multi-temporal: (1) only optical images (RapidEye) and (2) optical plus dual polarimetric (VV/VH) SAR images (TerraSAR-X). In addition, inter-annual or short term (2-3 years) changes in cropland area in the past ten years were investigated using historical Landsat images. Results obtained indicate that the use of only optical images to map different crop types in West Africa can achieve moderate classification accuracies (57% to 71%). Overlaps between the cropping calendars of most crops types and certain inter-croppings pose a challenge to optical images in achieving an adequate separation between those crop classes. Integration of SAR images, however, can improve classification accuracies by between 8 and 15%, depending on the number of available images and their acquisition dates. The sensitivity of SAR systems to different crop canopy architectures and land surface characteristics improved the separation between certain crop types. The VV polarization of TerraSAR-X was found to better discrimination between crop types than the VH. Images acquired between August and October were found to be very useful for crop mapping in the sub-region due to structural differences in some crop types during this period.
At the regional scale, inter-annual or short term changes in cropland area in the Sudanian Savanna agro-ecological zone in West Africa were assessed by upscaling historical cropland information derived at the watershed scale (using Landsat imagery) unto a coarse spatial resolution, but geographically large, satellite imagery (MODIS) using regression based modeling. The possibility of using such regional scale cropland information to improve government-derived agricultural statistics was investigated by comparing extracted cropland area from the fractional cover maps with district-level agricultural statistics from Ghana The accuracy of the fractional cover maps (MAE between 14.2% and 19.1%) indicate that the heterogeneous agricultural landscape of West Africa can be suitably represented at the regional or continental scales by estimating fractional cropland cover on low resolution Analysis of the results revealed that cropland area in the Sudanian Savanna zone has experienced inter-annual or short term fluctuations in the past ten years due to a variety of factors including climate factors (e.g. floods and droughts), declining soil fertility, population increases and agricultural policies such as fertilizer subsidies. Comparison of extracted cropland area from the fractional cover maps with government's agricultural statistics (MoFA) for seventeen districts (second administrative units) in Ghana revealed high inconsistencies in the government statistics, and highlighted the potential of satellite derived cropland information at regional scales to improve national/sub-national agricultural statistics in West Africa.
The results obtained in this study is promising for West Africa, considering the recent launch of optical (Landsat 8) and SAR sensors (Sentinel-1) that will provide free data for crop mapping in the sub-region. This will improve chances of obtaining adequate satellite images acquired during the cropping season for agricultural land use mapping and bolster opportunities of operationalizing agricultural land use mapping in West Africa. This can benefit a wide range of biophysical and economic models and improve decision making based on their results.
The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential.
Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.
Purpose – The purpose of this dissertation is to reveal the status quo of development of the grocery retailers’ internationalization process in China as well as to model future trends, opportunities and challenges within a very competitive market. Using several, geographically distant cities as case studies, this paper focuses on the development and outlook of different store formats, along with the development of competition in this respect by explicitly treating China not as a single market. The study thereby analyses historical and geographical diffusion in regard to store formats. The impacts of the main factors of change are discussed.
Design/methodology/approach – The dissertation reviews extensively the literature of grocery retail internationalization with special focus on China. In addition, it draws on primary research in the form of a wide range of expert interviews. As China´s ‘supermarket revolution’ is underway, an understanding of the local and foreign competition and the development of different store formats within different regions of China as well as their prospects, will be crucial to companies expanding into this area.
Findings – The study explains how grocery retailers have already entered the Chinese market with different store formats and how competition has and will further develop. In addition, the study reveals challenges and obstacles in regard to future market strategies, especially in regard to store formats and geographical regions.
Research limitations/implications – The study reveals the current landscape of the Chinese grocery retailing market and emphasizes important strategic pillars, modelling future implications and challenges for food retailers operating in China. Because China is a vast country this dissertation forms only a small part of the geographical evolution process in regard to store formats and competition.
Practical implications – Explores current understanding of the internationalization process in China by considering different format choices. Supplementary, the dissertation proposes an outlook of competition enlargement, prospects of format development and therewith strategic implications within different regions as well as a future research agenda.
Originality / value – Contributes to the understanding of the Chinese grocery retailing market. Furthermore, it is among the first to critically explore possible future developments in regard to store formats and competition within a geographical context in China
Background
Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health.
Methodology
We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d’Ivoire and validated against readily available survey data from school-aged children.
Principal Findings
Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d’Ivoire.
Conclusions/Significance
A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.
Accurate quantification of land use/cover change (LULCC) is important for efficient environmental management, especially in regions that are extremely affected by climate variability and continuous population growth such as West Africa. In this context, accurate LULC classification and statistically sound change area estimates are essential for a better understanding of LULCC processes. This study aimed at comparing mono-temporal and multi-temporal LULC classifications as well as their combination with ancillary data and to determine LULCC across the heterogeneous landscape of southwest Burkina Faso using accurate classification results. Landsat data (1999, 2006 and 2011) and ancillary data served as input features for the random forest classifier algorithm. Five LULC classes were identified: woodland, mixed vegetation, bare surface, water and agricultural area. A reference database was established using different sources including high-resolution images, aerial photo and field data. LULCC and LULC classification accuracies, area and area uncertainty were computed based on the method of adjusted error matrices. The results revealed that multi-temporal classification significantly outperformed those solely based on mono-temporal data in the study area. However, combining mono-temporal imagery and ancillary data for LULC classification had the same accuracy level as multi-temporal classification which is an indication that this combination is an efficient alternative to multi-temporal classification in the study region, where cloud free images are rare. The LULCC map obtained had an overall accuracy of 92%. Natural vegetation loss was estimated to be 17.9% ± 2.5% between 1999 and 2011. The study area experienced an increase in agricultural area and bare surface at the expense of woodland and mixed vegetation, which attests to the ongoing deforestation. These results can serve as means of regional and global land cover products validation, as they provide a new validated data set with uncertainty estimates in heterogeneous ecosystems prone to classification errors.
An Overview of the Regional Experiments for Land-atmosphere Exchanges 2012 (REFLEX 2012) Campaign
(2015)
The REFLEX 2012 campaign was initiated as part of a training course on the organization of an airborne campaign to support advancement of the understanding of land-atmosphere interaction processes. This article describes the campaign, its objectives and observations, remote as well as in situ. The observations took place at the experimental Las Tiesas farm in an agricultural area in the south of Spain. During the period of ten days, measurements were made to capture the main processes controlling the local and regional land-atmosphere exchanges. Apart from multi-temporal, multi-directional and multi-spatial space-borne and airborne observations, measurements of the local meteorology, energy fluxes, soil temperature profiles, soil moisture profiles, surface temperature, canopy structure as well as leaf-level measurements were carried out. Additional thermo-dynamical monitoring took place at selected sites. After presenting the different types of measurements, some examples are given to illustrate the potential of the observations made.
Rice is the most important food crop in Asia, and the timely mapping and monitoring of paddy rice fields subsequently emerged as an important task in the context of food security and modelling of greenhouse gas emissions. Rice growth has a distinct influence on Synthetic Aperture Radar (SAR) backscatter images, and time-series analysis of C-band images has been successfully employed to map rice fields. The poor data availability on regional scales is a major drawback of this method. We devised an approach to classify paddy rice with the use of all available Envisat ASAR WSM (Advanced Synthetic Aperture Radar Wide Swath Mode) data for our study area, the Mekong Delta in Vietnam. We used regression-based incidence angle normalization and temporal averaging to combine acquisitions from multiple tracks and years. A crop phenology-based classifier has been applied to this time series to detect single-, double- and triple-cropped rice areas (one to three harvests per year), as well as dates and lengths of growing seasons. Our classification has an overall accuracy of 85.3% and a kappa coefficient of 0.74 compared to a reference dataset and correlates highly with official rice area statistics at the provincial level (R-2 of 0.98). SAR-based time-series analysis allows accurate mapping and monitoring of rice areas even under adverse atmospheric conditions.
The 2010 eruption of Eyjafjallajokull volcano was characterized by pulsating activity. Discrete ash bursts merged at higher altitude and formed a sustained quasi-continuous eruption column. High-resolution near-field videos were recorded on 8-10 May, during the second explosive phase of the eruption, and supplemented by contemporary aerial observations. In the observed period, pulses occurred at intervals of 0.8 to 23.4 s (average, 4.2 s). On the basis of video analysis, the pulse volume and the velocity of the reversely buoyant jets that initiated each pulse were determined. The expansion history of jets was tracked until the pulses reached the height of transition from a negatively buoyant jet to a convective buoyant plume about 100 m above the vent. Based on the assumption that the density of the gas-solid mixture making up the pulse approximates that of the surrounding air at the level of transition from the jet to the plume, a mass flux ranging between 2.2 and 3.5 . 10\(^4\) kg/s was calculated. This mass eruption rate is in good agreement with results obtained with simple models relating plume height with mass discharge at the vent. Our findings indicate that near-field measurements of eruption source parameters in a pulsating eruption may prove to be an effective monitoring tool. A comparison of the observed pulses with those generated in calibrated large-scale experiments reveals very similar characteristics and suggests that the analysis of near-field sensors could in the future help to constrain the triggering mechanism of explosive eruptions.
The ecosystem of the high northern latitudes is affected by the recently changing environmental conditions. The Arctic has undergone a significant climatic change over the last decades. The land coverage is changing and a phenological response to the warming is apparent. Remotely sensed data can assist the monitoring and quantification of these changes. The remote sensing of the Arctic was predominantly carried out by the usage of optical sensors but these encounter problems in the Arctic environment, e.g. the frequent cloud cover or the solar geometry. In contrast, the imaging of Synthetic Aperture Radar is not affected by the cloud cover and the acquisition of radar imagery is independent of the solar illumination. The objective of this work was to explore how polarimetric Synthetic Aperture Radar (PolSAR) data of TerraSAR-X, TanDEM-X, Radarsat-2 and ALOS PALSAR and interferometric-derived digital elevation model data of the TanDEM-X Mission can contribute to collect meaningful information on the actual state of the Arctic Environment. The study was conducted for Canadian sites of the Mackenzie Delta Region and Banks Island and in situ reference data were available for the assessment. The up-to-date analysis of the PolSAR data made the application of the Non-Local Means filtering and of the decomposition of co-polarized data necessary.
The Non-Local Means filter showed a high capability to preserve the image values, to keep the edges and to reduce the speckle. This supported not only the suitability for the interpretation but also for the classification. The classification accuracies of Non-Local Means filtered data were in average +10% higher compared to unfiltered images. The correlation of the co- and quad-polarized decomposition features was high for classes with distinct surface or double bounce scattering and a usage of the co-polarized data is beneficial for regions of natural land coverage and for low vegetation formations with little volume scattering. The evaluation further revealed that the X- and C-Band were most sensitive to the generalized land cover classes. It was found that the X-Band data were sensitive to low vegetation formations with low shrub density, the C-Band data were sensitive to the shrub density and the shrub dominated tundra. In contrast, the L-Band data were less sensitive to the land cover. Among the different dual-polarized data the HH/VV-polarized data were identified to be most meaningful for the characterization and classification, followed by the HH/HV-polarized and the VV/VH-polarized data. The quad-polarized data showed highest sensitivity to the land cover but differences to the co-polarized data were small. The accuracy assessment showed that spectral information was required for accurate land cover classification. The best results were obtained when spectral and radar information was combined. The benefit of including radar data in the classification was up to +15% accuracy and most significant for the classes wetland and sparse vegetated tundra. The best classifications were realized with quad-polarized C-Band and multispectral data and with co-polarized X-Band and multispectral data. The overall accuracy was up to 80% for unsupervised and up to 90% for supervised classifications. The results indicated that the shortwave co-polarized data show promise for the classification of tundra land cover since the polarimetric information is sensitive to low vegetation and the wetlands. Furthermore, co-polarized data provide a higher spatial resolution than the quad-polarized data.
The analysis of the intermediate digital elevation model data of the TanDEM-X showed a high potential for the characterization of the surface morphology. The basic and relative topographic features were shown to be of high relevance for the quantification of the surface morphology and an area-wide application is feasible. In addition, these data were of value for the classification and delineation of landforms. Such classifications will assist the delineation of geomorphological units and have potential to identify locations of actual and future morphologic activity.
The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.
Disentangling the relative effects of bushmeat availability on human nutrition in central Africa
(2015)
We studied links between human malnutrition and wild meat availability within the Rainforest Biotic Zone in central Africa. We distinguished two distinct hunted mammalian diversity distributions, one in the rainforest areas (Deep Rainforest Diversity, DRD) containing taxa of lower hunting sustainability, the other in the northern rainforest-savanna mosaic, with species of greater hunting potential (Marginal Rainforest Diversity, MRD). Wild meat availability, assessed by standing crop mammalian biomass, was greater in MRD than in DRD areas. Predicted bushmeat extraction was also higher in MRD areas. Despite this, stunting of children, a measure of human malnutrition, was greater in MRD areas. Structural equation modeling identified that, in MRD areas, mammal diversity fell away from urban areas, but proximity to these positively influenced higher stunting incidence. In DRD areas, remoteness and distance from dense human settlements and infrastructures explained lower stunting levels. Moreover, stunting was higher away from protected areas. Our results suggest that in MRD areas, forest wildlife rational use for better human nutrition is possible. By contrast, the relatively low human populations in DRD areas currently offer abundant opportunities for the continued protection of more vulnerable mammals and allow dietary needs of local populations to be met.
Background:
Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions.
Methods:
We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised.
Results:
We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from.
Conclusions:
Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.
River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta's general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas-namely the Yellow River Delta (China), the Mekong Delta (Vietnam), the Irrawaddy Delta (Myanmar), and the Ganges-Brahmaputra (Bangladesh, India)-as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013). A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid-latitude, subtropical, and polar deltas are illustrated, and the advantages and limitations of the approach for inundation derivation are discussed.
Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS) techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI). Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.
Most animals live in seasonal environments and experience very different conditions throughout the year. Behavioral strategies like migration, hibernation, and a life cycle adapted to the local seasonality help to cope with fluctuations in environmental conditions. Thus, how an individual utilizes the environment depends both on the current availability of habitat and the behavioral prerequisites of the individual at that time. While the increasing availability and richness of animal movement data has facilitated the development of algorithms that classify behavior by movement geometry, changes in the environmental correlates of animal movement have so far not been exploited for a behavioral annotation. Here, we suggest a method that uses these changes in individual–environment associations to divide animal location data into segments of higher ecological coherence, which we term niche segmentation. We use time series of random forest models to evaluate the transferability of habitat use over time to cluster observational data accordingly. We show that our method is able to identify relevant changes in habitat use corresponding to both changes in the availability of habitat and how it was used using simulated data, and apply our method to a tracking data set of common teal (Anas crecca). The niche segmentation proved to be robust, and segmented habitat suitability outperformed models neglecting the temporal dynamics of habitat use. Overall, we show that it is possible to classify animal trajectories based on changes of habitat use similar to geometric segmentation algorithms. We conclude that such an environmentally informed classification of animal trajectories can provide new insights into an individuals' behavior and enables us to make sensible predictions of how suitable areas might be connected by movement in space and time.
The freeze-thaw cycles in periglacial areas during the Quaternary glacials increased frost weathering, leading to a disintegration of rock formations. Transported downslope, clasts allowed in some areas the formation of stratified slope deposits known as “grèzes litées”. This study reviews the existing theories and investigates the grèzes litées deposits of Enscherange and Rodershausen in Luxembourg. This process was reinforced by the lithostructural control of the parent material expressed by the dip of schistosity (66°) and its orientation parallel to the main slopes in the area. This gave opportunities to activate the frost-weathering process on top of the ridge where the parent material outcropped. As the stratified slope deposits have a dip of 23° and as there is no significant lateral variation in rock fragment size, slope processes that involve only gravity are excluded and transportation in solifluction lobes with significant slopewash and sorting processes is hypothesized. The Enscherange formation, the biggest known outcrop of grèzes litées in north-western Europe, shows evidence of clear layering over the whole profile depth. A palaeolandscape reconstruction shows that ridges must have been tens of metres higher than presently. The investigation of the matrix composition shows Laacher See tephra in the overlying periglacial cover bed with infiltrations of the minerals in the reworked upper layer of the grèzes litées deposit. Chronostratigraphic approaches using the underlying cryoturbation zone and Laacher See heavy minerals in the overlying topsoil place the formation of grèzes litées deposits in the Late Pleistocene.
Rice is an important food crop and a large producer of green-house relevant methane. Accurate and timely maps of paddy fields are most important in the context of food security and greenhouse gas emission modelling. During their life-cycle, rice plants undergo a phenological development that influences their interaction with waves in the visible light and infrared spectrum. Rice growth has a distinctive signature in time series of remotely-sensed data. We used time series of MODIS (Moderate Resolution Imaging Spectroradiometer) products MOD13Q1 and MYD13Q1 and a one-class support vector machine to detect these signatures and classify paddy rice areas in continental China. Based on these classifications, we present a novel product for continental China that shows rice areas for the years 2002, 2005, 2010 and 2014 at 250-m resolution. Our classification has an overall accuracy of 0.90 and a kappa coefficient of 0.77 compared to our own reference dataset for 2014 and correlates highly with rice area statistics from China’s Statistical Yearbooks (R2 of 0.92 for 2010, 0.92 for 2005 and 0.90 for 2002). Moderate resolution time series analysis allows accurate and timely mapping of rice paddies over large areas with diverse cropping schemes.
This study analyzed the spatiotemporal pattern of settlement expansion in Abuja, Nigeria, one of West Africa’s fastest developing cities, using geoinformation and ancillary datasets. Three epochs of Land-use Land-cover (LULC) maps for 1986, 2001 and 2014 were derived from Landsat images using support vector machines (SVM). Accuracy assessment (AA) of the LULC maps based on the pixel count resulted in overall accuracy of 82%, 92% and 92%, while the AA derived from the error adjusted area (EAA) method stood at 69%, 91% and 91% for 1986, 2001 and 2014, respectively. Two major techniques for detecting changes in the LULC epochs involved the use of binary maps as well as a post-classification comparison approach. Quantitative spatiotemporal analysis was conducted to detect LULC changes with specific focus on the settlement development pattern of Abuja, the federal capital city (FCC) of Nigeria. Logical transitions to the urban category were modelled for predicting future scenarios for the year 2050 using the embedded land change modeler (LCM) in the IDRISI package. Based on the EAA, the result showed that urban areas increased by more than 11% between 1986 and 2001. In contrast, this value rose to 17% between 2001 and 2014. The LCM model projected LULC changes that showed a growing trend in settlement expansion, which might take over allotted spaces for green areas and agricultural land if stringent development policies and enforcement measures are not implemented. In conclusion, integrating geospatial technologies with ancillary datasets offered improved understanding of how urbanization processes such as increased imperviousness of such a magnitude could influence the urban microclimate through the alteration of natural land surface temperature. Urban expansion could also lead to increased surface runoff as well as changes in drainage geography leading to urban floods.
Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012
(2016)
This study is aimed at a better understanding of how upstream runoff formation affected the cropping intensity (CI: number of harvests) in the Aral Sea Basin (ASB) between 2000 and 2012. MODIS 250 m NDVI time series and knowledge-based pixel masking that included settlement layers and topography features enabled to map the irrigated cropland extent (iCE). Random forest models supported the classification of cropland vegetation phenology (CVP: winter/summer crops, double cropping, etc.). CI and the percentage of fallow cropland (PF) were derived from CVP. Spearman’s rho was selected for assessing the statistical relation of CI and PF to runoff formation in the Amu Darya and Syr Darya catchments per hydrological year. Validation in 12 reference sites using multi-annual Landsat-7 ETM+ images revealed an average overall accuracy of 0.85 for the iCE maps. MODIS maps overestimated that based on Landsat by an average factor of ~1.15 (MODIS iCE/Landsat iCE). Exceptional overestimations occurred in case of inaccurate settlement layers. The CVP and CI maps achieved overall accuracies of 0.91 and 0.96, respectively. The Amu Darya catchment disclosed significant positive (negative) relations between upstream runoff with CI (PF) and a high pressure on the river water resources in 2000–2012. Along the Syr Darya, reduced dependencies could be observed, which is potentially linked to the high number of water constructions in that catchment. Intensified double cropping after drought years occurred in Uzbekistan. However, a 10 km × 10 km grid of Spearman’s rho (CI and PF vs. upstream runoff) emphasized locations at different CI levels that are directly affected by runoff fluctuations in both river systems. The resulting maps may thus be supportive on the way to achieve long-term sustainability of crop production and to simultaneously protect the severely threatened environment in the ASB. The gained knowledge can be further used for investigating climatic impacts of irrigation in the region.
The Sentinel-1 Satellite (S-1) of ESA's Copernicus Mission delivers freely available C-Band Synthetic Aperture Radar (SAR) data that are suited for interferometric applications (InSAR). The high geometric resolution of less than fifteen meter and the large coverage offered by the Interferometric Wide Swath mode (IW) point to new perspectives on the comprehension and understanding of surface changes, the quantification and monitoring of dynamic processes, especially in arid regions. The contribution shows the application of S-1 intensities and InSAR coherences in time series analysis for the delineation of changes related to fluvial morphodynamics in Damghan, Iran. The investigations were carried out for the period from April to October 2015 and exhibit the potential of the S-1 data for the identification of surface disturbances, mass movements and fluvial channel activity in the surroundings of the Damghan Playa. The Amplitude Change Detection highlighted extensive material movement and accumulation - up to sizes of more than 4,000 m in width - in the east of the Playa via changes in intensity. Further, the Coherence Change Detection technique was capable to indicate small-scale channel activity of the drainage system that was neither recognizable in the S-1 intensity nor the multispectral Landsat-8 data. The run off caused a decorrelation of the SAR signals and a drop in coherence. Seen from a morphodynamic point of view, the results indicated a highly dynamic system and complex tempo-spatial patterns were observed that will be subject of future analysis. Additionally, the study revealed the necessity to collect independent reference data on fluvial activity in order to train and adjust the change detector.
This study investigates a two component decomposition technique for HH/VV-polarized PolSAR (Polarimetric Synthetic Aperture Radar) data. The approach is a straight forward adaption of the Yamaguchi decomposition and decomposes the data into two scattering contributions: surface and double bounce under the assumption of a negligible vegetation scattering component in Tundra environments. The dependencies between the features of this two and the classical three component Yamaguchi decomposition were investigated for Radarsat-2 (quad) and TerraSAR-X (HH/VV) data for the Mackenzie Delta Region, Canada. In situ data on land cover were used to derive the scattering characteristics and to analyze the correlation among the PolSAR features. The double bounce and surface scattering features of the two and three component scattering model (derived from pseudo-HH/VV- and quad-polarized data) showed similar scattering characteristics and positively correlated-R2 values of 0.60 (double bounce) and 0.88 (surface scattering) were observed. The presence of volume scattering led to differences between the features and these were minimized for land cover classes of low vegetation height that showed little volume scattering contribution. In terms of separability, the quad-polarized Radarsat-2 data offered the best separation of the examined tundra land cover types and will be best suited for the classification. This is anticipated as it represents the largest feature space of all tested ones. However; the classes “wetland” and “bare ground” showed clear positions in the feature spaces of the C- and X-Band HH/VV-polarized data and an accurate classification of these land cover types is promising. Among the possible dual-polarization modes of Radarsat-2 the HH/VV was found to be the favorable mode for the characterization of the aforementioned tundra land cover classes due to the coherent acquisition and the preserved co-pol. phase. Contrary, HH/HV-polarized and VV/VH-polarized data were found to be best suited for the characterization of mixed and shrub dominated tundra.
11 Conclusion
11.1 Glaze compositions
Glazes from tiles of imposing Islamic buildings and some tableware glazes of the medieval epoch in Central Asia, the Middle East, Asia Minor, and North Africa are analysed regarding their main composition and colouring agents. Three major production recipes can be distinguished, i.e. alkali glazes, alkali lead glazes, and lead glazes. In the work of Tite (2011), Islamic glazes from Egypt, Iran, Iraq, and Syria are subdivided into four groups of composition, being partly consistent with those of this work. The alkali lime glazes with <2 wt% PbO correspond to the alkali glazes, but with higher content of CaO. The second and third group of low lead alkali and lead alkali glazes (2-10 wt% PbO and 10-35 wt% PbO) can be subsumed to the alkali lead group described here. Tite´s high lead group has PbO contents >35 wt% and is comparable to the lead glazes (>30 wt% PbO) of this study. The lead and the alkali oxides serve as a flux for the lowering the melting point.
In the interaction of ceramic body and glaze, primarily an influence from Si, Al, and K is observed in the line scans from the cross section of ceramic and glaze. However, the input of ceramic material doesn’t seem to be critical for the classification of glazes according to their alkali and alkali lead compositions.
In every epoch and locality, except of the Ilkhanate dynasty in Iran, lead glaze samples can be verified. This is also observed in previous investigations e.g. from medieval Iraq, Jordan and Iran (McCarthy, 1996; Al-Saad, 2002; Holakooei et al., 2014). In the Moroccan and Bulgarian glazes, lead seems to be the only important flux. In part, the lead flux is supplemented by additional alkali contents. The lack of alkali and alkali lead glazes in Bulgarian and Moroccan glazes (assuming that the Ottoman alkali lead glazes are imported tableware) seems to affect the regions with Roman-influenced history and with geographical distance to the Near East alkali flux tradition.
For the alkali lead glazes and alkali glazes, the overall characteristic is sodium dominated, although the absolute soda values are in part surprisingly low. Samples from Bukhara, Takht-i-Suleiman and the Turkish localities have the highest, but still moderate Na2O values up to 15 wt%, compared to other analyses from e.g. India (Gill & Rehren, 2011).
The source of the alkali flux is either mineral natron or plant ash. The source can be determined regarding the MgO values, limited to 1.3 wt% in mineral natron and exceeding 2.0 wt% in the case of plant ashes. In the samples of the present study, the K2O component is not suitable for the indication of the flux-relevant alkali source due to its broad scattering. The P2O5 contents are also enhanced in the plant ash compositions but the data set is not sufficient for statistical evaluation. An influence of the ceramic body on the glaze composition is observed only for SiO2, Al2O3, and K2O in quartz frit ceramics with slight K-feldspar content.
The earliest Uzbek tableware glazes from the 10th-11th century (Seljuq period) were generally produced using a lead flux. The same applies to part of the Uzbek tile glazes which were produced between the 13th and 16th century. In Iran, glazes from the 12th century (Khwarezmid period) are lead glazes, but also alkali-fluxed glazes with mineral natron characteristics can be found. Although the production of lead-rich glazes was established from the 8th-9th century on in Iraq, Syria, and Egypt (Henshaw, 2010; Tite et al., 2011), alkali glazes are found in almost all regions except of Bulgaria and Morocco.
Plant ash-fluxed alkali glazes are found in 13th century glazes from Takht-i-Suleiman. The plant ash flux technology is assumed to be continuously used in Mesopotamia, Iran, and Central Asia (Sayre & Smith, 1974; Henderson, 2009), but it could be shown that a parallel use of mineral natron parallel existed in the alkali glaze production from the 12th-15th century from Uzbekistan to Afghanistan. Mineral natron characteristics are also reported by Mason (2004) for Syrian and Iranian alkali glazes on lustre ware of the 8th-14th century. Tile glazes with partly mineral natron compositions are found in the Mughal architectural glazes from the 14th- 17th century from India (Gill et al., 2014).
Alkali and alkali lead tile glazes from Samarkand from the 13th century (Mongolian period) have mineral natron flux characteristics, but samples from the 15th century (Timurid period) show plant ash signature. Alkali fluxed Uzbek glazes from Bukhara from the 16th century (Sheibanid dynasty) are also made by plant ash flux and are subdivided into two groups with high and low sodium oxide content. The Afghan alkali glazes have sodium oxide contents similar to the sodium-poor Uzbek subgroup, which points to a possible exchange of glaze makers or glaze making technology from Uzbekistan and Afghanistan in the 15th-17th century. Regarding the extensive exchange of Timurid craftsmen in Central Asia, this option seems to be even more likely (Golombek, 1996). One sample from the 15th century from Afghanistan with mineral natron reveals that this material was parallel used in these centuries.
Concerning the colouring of the glazes, it has to be distinguished between pigments and colouring ions which are incorporated in the glassy matrix. The colouring agents for translucent glazes are cations of various transition metals. As ions, Co2+ (blue), Cu2+ (green in a lead rich matrix), Fe3+ (brown/black), Mn4+ (brown/black) and Mn3+ (violet) are determined by EPMA. For opaque yellow, white, and turquoise glazes, different pigments were used. The crystalline pigments are investigated by a µ XRD2 device with the result of SnO2, SiO2, and PbSiO4 as whitening agents. PbSiO4 and Pb2Sn2O6 are found in the yellow glaze, from which only the lead tin oxide causes the yellow colour. In the black glazes, different Cr-rich pigments, Cu-Cr-Mn-oxides and iron containing clinopyroxenes are found, even in samples of the same period and region. Cr-rich particles are also detected in two turquoise Afghan glazes from the 15th and 16th century. The use of the ions of Fe, Cu, Co, Cr, and Mn seems to be widely common in the Islamic glazes and corresponds to the described colouring agents in e.g. the study of Tite (2011). The use of opacifying SnO2 particles is widespread as it is reported from different Islamic glazes from Iraq, Iran, Egypt, and Syria (Henshaw, 2010; O´Kane, 2011; Tite, 2011). The colouring agents are known already from former, e.g. Egyptian, Roman and pre-islamic periods, but especially SnO2 pigments became increasingly widespread in the Islamic glazing tradition. The use of yellow and black pigments instead varies already within the buildings from Bukhara from Cr crystals and clino-pyroxenes in the mosque Khoja Zainuddin to a Cu-Cr-Mn-oxide in the madrassa Mir-i Arab of the same epoch.
Regarding the matrix compositions connected with the colouring, a certain assignment within the different locations and epochs can be seen. It is noticeable that e.g. the content of lead in turquoise glazes in Uzbekistan is in the range of 0.0-9.2 wt% Pb, whereas blue glazes are mostly alkali ones with PbO contents <2.0 wt%. The turquoise glazes show, that this restriction is not influenced by any defaults of availability and processability. The assumption of common addition of lead and tin to the glaze, which is already described for Iranian glazes of the 13th century (Allan et al., 1973) cannot be confirmed by correlations of tin and lead oxide in the compositions.
11.2 Portable XRF measurement
With the p-XRF, semi-quantitative information about the major element compositions is generated. The depth of the detectable signals depends on the analysed sample setup. The p-XRF data are collected with the XL3 Hybrid device of the company Analyticon Instruments. In the comparison of p-XRF results of the “mining” program from Uzbek glazes with EPMA results, the same major composition groups can be distinguished. The Moroccan glazes, all lead rich, are measured with the “mining” as well as with the “soil” program, revealing a better performance in the “mining” measurements. The deviations are nevertheless high, because of the high lead contents, which make the calculation of matrix correction difficult.
The measurement of the colouring oxides MnO2, CoO, and CuO is satisfying with the internal calibration of the device and even improved with the “mining” program measurement, if compared to the results of the “soil” program. The measurements of glaze imitations lead to better results than that of bulk glass. This can be attributed to the smoother surface texture.
In spite of the accuracy limits in the measurements of particular elements in glazes, the classification of flux composition into three groups could be confirmed with the p XRF analysis. The measurement precision is therefore sufficient for the semi-quantitative analysis of the flux characteristic of glazes. Especially for the on-site measurement of large sample quantities on historical buildings, the device is a suitable tool.
11.3 Restoration material
The ORMOCER® fulfils the requirements of stability, reversibility, and transparency, which are imposed to a modern restoration material. As pigments, historically coloured glass, cobalt blue, Egyptian blue, lead tin yellow, manganese violet, iron oxide, copper oxide, and cassiterite were used. The metal compounds have higher colour intensities than the pigments of coloured glass. It has to be considered that the proportion of ORMOCER® in the batch must be high enough (70 vol%) to guarantee the ORMOCER® properties of weathering and mechanical stability. The adhesion properties of the ORMOCER® and the homogeneity of the mixture are the best in a fraction of max. 30 vol% particles per ORMOCER®.
With integrated particles, the ORMOCER® G materials show homogeneous coatings, whereas the particles in the ORMCOER® E show more agglomeration. In the sedimentation and weathering experiments, the use of an ultrasonic finger in combination with a roller mill is favourable compared to the treatment with bead grinding mill. The treatments with ultrasonic finger and roller mill result in less sedimentation and better adhesion of the dispersions. The treatment of the dispersions in the bead grinding mill does not result in sufficient adhesion, certainly due to the sedimentation behaviour and a congregation of particles on the bottom of the coating.
The modification of dispersed nano-particles by 3-methacryl-oxypropyltrimethoxysilan leads to a further homogenization in the sedimentation tests. It is therefore approved for the use in coloured glaze supplements. In weathered coatings of nano-particle compounds, the surface modification shows certainly no enhancement of stability.
The treatment of pigmented coatings with an additional layer of pure ORMOCER® results in a bright and transparent appearing, which is closer to the original optical appearance of the glaze. A long-time test application on a historical building will be the next step to validate the suitability of the restoration material.
The global-local sustainable development and climate change adaptation policy, and the emerging political discourse on the value of local Adaptation, have positioned the local institutions and their governance space within the strategic enclaves of multilevel governance system. Such shifts have transformed the context for sustainable Nature Based Tourism (NBT) development and adaptation in Nepal in general, and its protected areas, in particular. The emerging institutional adaptation discourse suggests on the need to link tourism development, adaptation and governance within the sustainability concept, and also to recognize the justice and inclusive dimensions of local adaptation. However, sociological investigation of institutional adaptation, particularly at the interface between sustainability, justice and inclusive local adaptation is an undertheorized research topic.
This exploratory study examined the sociological process of the institutional adaptation, especially the social resilience and adaptive governance capacities of the NBT institutions, in 7 Village Development Committees of the Mustang district, a popular destination in the Annapurna Conservation Area, Nepal. Using the sphere (a dynamic social space concept) and quality of governance as the analytical framework, the integrative adaptation as the methodological approach and the case study action research method, the study investigated and generated a holistic picture on the state of the social resilience and adaptive governance capacities of the NBT institutions.
The findings show institutional social resilience capacities to be contingent on socio-political construction of adaptation knowledge and power. Factors influencing such constructions among NBT institutions include: the site and institutions specific political, economic and environmental dispositions; the associated socio-political processes of knowledge constructions and volition action; and the social relationships and interaction, operating within the spheres and at multiple governance levels. The adaptive governance capacities hinge on the institutional arrangements, the procedural aspects of adaptation governance and the governmentality. These are reflective of the diverse legal frameworks, the interiority perspective of the decision making and governance practices of the NBT institutions.
In conclusion, it is argued that effective local adaptation in the Mustang district is contingent on the adaptation and institutional dynamics of the NBT institutions, consisting of the cognitive, subjective, process and procedural aspects of the adaptation knowledge production and its use.
Monitoring the spatio-temporal development of vegetation is a challenging task in heterogeneous and cloud-prone landscapes. No single satellite sensor has thus far been able to provide consistent time series of high temporal and spatial resolution for such areas. In order to overcome this problem, data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) have been established and frequently used in recent years to generate high-resolution time series. In order to make it applicable to larger scales and to increase the input data availability especially in cloud-prone areas, an ESTARFM framework was developed in this study introducing several enhancements. An automatic filling of cloud gaps was included in the framework to make best use of available, even partly cloud-covered Landsat images. Furthermore, the ESTARFM algorithm was enhanced to automatically account for regional differences in the heterogeneity of the study area. The generation of time series was automated and the processing speed was accelerated significantly by parallelization. To test the performance of the developed ESTARFM framework, MODIS and Landsat-8 data were fused for generating an 8-day NDVI time series for a study area of approximately 98,000 km\(^{2}\) in West Africa. The results show that the ESTARFM framework can accurately produce high temporal resolution time series (average MAE (mean absolute error) of 0.02 for the dry season and 0.05 for the vegetative season) while keeping the spatial detail in such a heterogeneous, cloud-prone region. The developments introduced within the ESTARFM framework establish the basis for large-scale research on various geoscientific questions related to land degradation, changes in land surface phenology or agriculture
The contact of hot melt with liquid water - called Molten Fuel Coolant Interaction (MFCI) - can result in vivid explosions. Such explosions can occur in different scenarios: in steel or powerplants but also in volcanoes. Because of the possible dramatic consequences of such explosions an investigation of the explosion process is necessary.
Fundamental basics of this process are already discovered and explained, such as the frame conditions for these explosions. It has been shown that energy transfer during an MFCI-process can be very high because of the transfer of thermal energy caused by positive feedback mechanisms.
Up to now the influence of several varying parameters on the energy transfer and the explosions is not yet investigated sufficiently. An important parameter is the melt temperature, because the amount of possibly transferable energy depends on it. The investigation of this influence is the main aim of this work. Therefor metallic tin melt was used, because of its nearly constant thermal material properties in a wide temperature range. With tin melt research in the temperature range from 400 °C up to 1000 °C are
possible.
One important result is the lower temperature limit for vapor film stability in the experiments. For low melt temperatures up to about 600 °C the vapor film is so unstable that it already can collapse before the mechanical trigger. As expected the transferred thermal energy all in all increases with higher temperatures. Although this effect sometimes is superposed by other influences such as the premix of melt and water, the result is confirmed after a consequent filtering of the remaining influences. This trend is not only recognizable in the amount of transferred energy, but also in the fragmentation of melt or the vaporizing water. But also the other influences on MFCI-explosions showed interesting results in the frame of this work. To perform the experiments the installation and preparation of the experimental Setup in the laboratory were necessary.
In order to compare the results to volcanism and to get a better investigation of the brittle fragmentation
of melt additional runs with magmatic melt were made. In the results the thermal power during energy transfer could be estimated. Furthermore the model of “cooling fragments “ could be usefully applied.
Interactions between different formative processes are reflected in the internal structure of rock glaciers. Therefore, the detection of subsurface conditions can help to enhance our understanding of landform development. For an assessment of subsurface conditions, we present an analysis of the spatial variability of active layer thickness, ground ice content and frost table topography for two different rock glaciers in the Eastern Swiss Alps by means of quasi-3-D electrical resistivity imaging (ERI). This approach enables an extensive mapping of subsurface structures and a spatial overlay between site-specific surface and subsurface characteristics. At Nair rock glacier, we discovered a gradual descent of the frost table in a downslope direction and a constant decrease of ice content which follows the observed surface topography. This is attributed to ice formation by refreezing meltwater from an embedded snow bank or from a subsurface ice patch which reshapes the permafrost layer. The heterogeneous ground ice distribution at Uertsch rock glacier indicates that multiple processes on different time domains were involved in the development. Resistivity values which represent frozen conditions vary within a wide range and indicate a successive formation which includes several advances, past glacial overrides and creep processes on the rock glacier surface. In combination with the observed topography, quasi-3-D ERI enables us to delimit areas of extensive and compressive flow in close proximity. Excellent data quality was provided by a good coupling of electrodes to the ground in the pebbly material of the investigated rock glaciers. Results show the value of the quasi-3-D ERI approach but advise the application of complementary geophysical methods for interpreting the results.
West African summer monsoon precipitation is characterized by distinct decadal variability. Due to its welldocumented link to oceanic boundary conditions in various ocean basins it represents a paradigm for decadal predictability. In this study, we reappraise this hypothesis for several sub-regions of sub-Saharan West Africa using the new German contribution to the coupled model intercomparison project phase 5 (CMIP5) near-term prediction system.
In addition, we assume that dynamical downscaling of the global decadal predictions leads to an enhanced predictive skill because enhanced resolution improves the atmospheric response to oceanic forcing and landsurface feedbacks. Based on three regional climate models, a heterogeneous picture is drawn: none of the regional climate models outperforms the global decadal predictions or all other regional climate models in every region nor decade. However, for every test case at least one regional climate model was identified which outperforms the global predictions. The highest predictive skill is found in the western and central Sahel Zone with correlation coefficients and mean-square skill scores exceeding 0.9 and 0.8, respectively.
In the 1960s, when most African nations gained their independence after the age of colonialism, several theories and strategies emerged with the goal of "developing" these apparently "underdeveloped" territories. One of the most influential approaches for this task was represented in Julius K. Nyerere´s idea of Ujamaa, the Tanzanian version of African socialism.
Even before the Arusha Declaration established Ujamaa as a national development strategy in 1967, several groups of politicized young farmers took to the empty countryside of Tanzania to implement their own version of cooperative development. From one of these attempts emerged the Ruvuma Development Association (RDA), which organized up to 18 villages in southwestern Tanzania. The RDA became the inspiration for Nyerere´s concretization of Ujamaa and its implementation on national level. Yet, the central state could not replicate the success of the peasants, which was based on voluntariness and intrinsic motivation.
In 2015, this exploratory study has revisited the Region of Ruvuma. Through a case study approach, relying mostly on qualitative methods, new insights into the local history of Ujamaa and its perception have been gathered. In particular, narrative interviews with contemporary witnesses and group interviews with the present-day farmers’ groups have been conducted. Furthermore, NGOs active within the region, as well as regional and local government institutions were among the key stakeholders identified to concretize the local narrative of Ujamaa development. All interviews were analyzed according to the principles of qualitative content analysis. Additionally, individual villager questionnaires were used to achieve a more holistic picture of the local perception of development, challenges and the Ujamaa era.
None of the original Ujamaa groups of the times of the RDA was still operational at the time of research and no case of village-wide organization of collective agriculture could be observed. Nevertheless, in all of the three case study villages, several farmers’ groups (vikundi) were active in organizing development activities for their members. Furthermore, the perception of the Ujamaa era was generally positive throughout all of the case study sites. Yet, there have been significant differences in this perception, based on the village, age, gender and field size of the recipients. Overall, the period of Ujamaa was seen as an inspiration for present-day group activities, and the idea of such activities as a remedy for the developmental challenges of these villages was common among all stakeholders.
This thesis concludes that the positive perception of group activities as a vehicle for village development and the perception of Ujamaa history as a positive asset for the inception and organization of farmers’ groups would be highly beneficial to further attempts to support such development activities. However, the limitations in market access and capital availability for these highly-motivated group members have to be addressed by public and private development institutions. Otherwise, "the smell of Ujamaa" will be of little use for the progress of these villages.
Burkina Faso ranges amongst the fastest growing countries in the world with an annual population growth rate of more than three percent. This trend has consequences for food security since agricultural productivity is still on a comparatively low level in Burkina Faso. In order to compensate for the low productivity, the agricultural areas are expanding quickly. The mapping and monitoring of this expansion is difficult, even on the basis of remote sensing imagery, since the extensive farming practices and frequent cloud coverage in the area make the delineation of cultivated land from other land cover and land use types a challenging task. However, as the rapidly increasing population could have considerable effects on the natural resources and on the regional development of the country, methods for improved mapping of LULCC (land use and land cover change) are needed. For this study, we applied the newly developed ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) framework to generate high temporal (8-day) and high spatial (30 m) resolution NDVI time series for all of Burkina Faso for the years 2001, 2007, and 2014. For this purpose, more than 500 Landsat scenes and 3000 MODIS scenes were processed with this automated framework. The generated ESTARFM NDVI time series enabled extraction of per-pixel phenological features that all together served as input for the delineation of agricultural areas via random forest classification at 30 m spatial resolution for entire Burkina Faso and the three years. For training and validation, a randomly sampled reference dataset was generated from Google Earth images and based on expert knowledge. The overall accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the applied methodology. The results show an expansion of agricultural area of 91% between 2001 and 2014 to a total of 116,900 km\(^2\). While rainfed agricultural areas account for the major part of this trend, irrigated areas and plantations also increased considerably, primarily promoted by specific development projects. This expansion goes in line with the rapid population growth in most provinces of Burkina Faso where land was still available for an expansion of agricultural area. The analysis of agricultural encroachment into protected areas and their surroundings highlights the increased human pressure on these areas and the challenges of environmental protection for the future.
In Germany, as in many Western societies, demographic change will lead to a higher number of senior visitors to natural recreational areas and national parks. Given the high physiological requirements of many outdoor recreation activities, especially in mountain areas, it seems likely that demographic change will affect the spatial behaviour of national park visitors, which may pose a challenge to the management of these areas. With the help of GPS tracking and a standardized questionnaire (n=481), this study empirically investigates the spatial behaviour of demographic age brackets in Berchtesgaden National Park (NP) and the potential effects of demographic change on the use of the area. Cluster analysis revealed four activity types in the study area. More than half of the groups with visitors aged 60 and older belong to the activity type of Walker.
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.
Detailed information on the land cover types present and the horizontal position of the land–water interface is needed for sensitive coastal ecosystems throughout the Arctic, both to establish baselines against which the impacts of climate change can be assessed and to inform response operations in the event of environmental emergencies such as oil spills. Previous work has demonstrated potential for accurate classification via fusion of optical and SAR data, though what contribution either makes to model accuracy is not well established, nor is it clear what shorelines can be classified using optical or SAR data alone. In this research, we evaluate the relative value of quad pol RADARSAT-2 and Landsat 5 data for shoreline mapping by individually excluding both datasets from Random Forest models used to classify images acquired over Nunavut, Canada. In anticipation of the RADARSAT Constellation Mission (RCM), we also simulate and evaluate dual and compact polarimetric imagery for shoreline mapping. Results show that SAR data is needed for accurate discrimination of substrates as user’s and producer’s accuracies were 5–24% higher for models constructed with quad pol RADARSAT-2 and DEM data than models constructed with Landsat 5 and DEM data. Models based on simulated RCM and DEM data achieved significantly lower overall accuracies (71–77%) than models based on quad pol RADARSAT-2 and DEM data (80%), with Wetland and Tundra being most adversely affected. When classified together with Landsat 5 and DEM data, however, model accuracy was less affected by the SAR data type, with multiple polarizations and modes achieving independent overall accuracies within a range acceptable for operational mapping, at 89–91%. RCM is expected to contribute positively to ongoing efforts to monitor change and improve emergency preparedness throughout the Arctic.
Maize cropping systems mapping using RapidEye observations in agro-ecological landscapes in Kenya
(2017)
Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer’s accuracy and UA: user’s accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10–20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.
Past and the projected future climate change in Afghanistan has been analyzed systematically and differentiated with respect to its different climate regions to gain some first quantitative insights into Afghanistan’s vulnerability to ongoing and future climate changes. For this purpose, temperature, precipitation and five additional climate indices for extremes and agriculture assessments (heavy precipitation; spring precipitation; growing season length (GSL), the Heat Wave Magnitude Index (HWMI); and the Standardized Precipitation Evapotranspiration Index (SPEI)) from the reanalysis data were examined for their consistency to identify changes in the past (data since 1950). For future changes (up to the year 2100), the same parameters were extracted from an ensemble of 12 downscaled regional climate models (RCM) of the Coordinated Regional Climate Downscaling Experiment (CORDEX)-South Asia simulations for low and high emission scenarios (Representative Concentration Pathways 4.5 and 8.5). In the past, the climatic changes were mainly characterized by a mean temperature increase above global level of 1.8 °C from 1950 to 2010; uncertainty with regard to reanalyzed rainfall data limited a thorough analysis of past changes. Climate models projected the temperature trend to accelerate in the future, depending strongly on the global carbon emissions (2006–2050 Representative Concentration Pathways 4.5/8.5: 1.7/2.3 °C; 2006–2099: 2.7/6.4 °C, respectively). Despite the high uncertainty with regard to precipitation projections, it became apparent that the increasing evapotranspiration is likely to exacerbate Afghanistan’s already existing water stress, including a very strong increase of frequency and magnitude of heat waves. Overall, the results show that in addition to the already extensive deficiency in adaptation to current climate conditions, the situation will be aggravated in the future, particularly in regard to water management and agriculture. Thus, the results of this study underline the importance of adequate adaptation to climate change in Afghanistan. This is even truer taking into account that GSL is projected to increase substantially by around 20 days on average until 2050, which might open the opportunity for extended agricultural husbandry or even additional harvests when water resources are properly managed.
The Kaapvaal Craton hosts a number of large gold deposits (e.g. Witwatersrand Supergroup) which mining companies have exploited at certain stratigraphic positions. It also hosts the largest platinum group element (PGE) deposits (e.g. Bushveld Igneous Complex) which mining companies have exploited in different mineralised layered magmatic zones. In spite of the extensive exploration history in the Kaapvaal Craton, the origin of the Witwatersrand gold deposits and Bushveld Igneous Complex PGE deposits has remained one of the most debated topics in economic geology. The goal of this study was to identify the geochemical characteristics of marine shales in the Barberton, Witwatersrand, and Transvaal supergroups in South Africa in order to make inferences on their sediment provenance and siderophile element endowments. Understanding why some of the Archaean and Proterozoic hinterlands are heavily mineralised, compared to others with similar geological characteristics, will aid in the development of more efficient exploration models. Fresh, unmineralised marine shales from the Barberton (Fig Tree and Moodies groups), Witwatersrand (West Rand and Central Rand groups), and Transvaal (Black Reef Formation and Pretoria Group) supergroups were sampled from drill core and underground mining exposures. Analytical methods, such as X-ray powder diffraction (XRD), optical microscopy, X-ray fluorescence (XRF), inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and electron microprobe analysis (EMPA) were applied to comprehensively characterise the shales. All of the Au and PGE assays examined the newly collected shale samples.
The Barberton Supergroup shales consist mainly of quartz, illite, chlorite, and albite, with diverse heavy minerals, including sulfides and oxides, representing the minor constituents. The regionally persistent Witwatersrand Supergroup shales consist mainly of quartz, muscovite, and chlorite, and also contain minor constituents of sulfides and oxides. The Transvaal Supergroup shales comprise quartz, chlorite, and carbonaceous material. Major, trace (including rare-earth element) concentrations were determined for shales from the above supergroups to constrain their source and post-depositional evolution. Chemical variations were observed in all the studied marine shales. Results obtained from this study revealed that post-depositional modification of shale chemistry was significant only near contacts with over- and underlying coarser-grained siliciclastic rocks and along cross-cutting faults, veins, and dykes. Away from such zones, the shale composition remained largely unaltered and can be used to draw inferences concerning sediment provenance and palaeoweathering in the source region and/or on intrabasinal erosion surfaces. Evaluation of weathering profiles through sections of the studied supergroups revealed that the shales therein are characterised by high chemical index of alteration (CIA), chemical index of weathering (CIW), and index of compositional variability (ICV), suggesting that the source area was lithologically complex and subject to intense chemical weathering.
A progressive change in the chemical composition was identified, from a dominant ultramafic–mafic source for the Fig Tree Group to a progressively felsic–plutonic provenance for the Moodies Group. The West Rand Group of the Witwatersrand Supergroup shows a dominance of tonalite–trondhjemite–granodiorite and calcalkaline granite sources. Compositional profiles through the only major marine shale unit within the Central Rand Group indicate the progressive unroofing of a granitic source in an otherwise greenstone-dominated hinterland during the course of sedimentation. No plausible likely tectonic setting was obtained through geochemical modelling. However, the combination of the systematic shale chemistry, geochronology, and sedimentology in the Witwatersrand Supergroup supports the hypothesised passive margin setting for the >2.98 to 2.91 Ga West Rand Group, and an active continental margin source for the overlying >2.90 to 2.78 Ga Central Rand Group, along with a foreland basin setting for the latter.
Ultra-low detection limit analyses of gold and PGE concentrations revealed a variable degree of gold accumulation within pristine unmineralised shales. All the studied shales contain elevated gold and PGE contents relative to the upper continental crust, with marine shales from the Central Rand Group showing the highest Au (±9.85 ppb) enrichment. Based on this variation in the provenance of contemporaneous sediments in different parts of the Kaapvaal Craton, one can infer that the siderophile elements were sourced from a fertile hinterland, but concentrated into the marine shales by a combination of different processes. It is proposed that accumulation of siderophile elements in the studied marine shales was mainly controlled by mechanical coagulation and aggregation. These processes involved suspended sediments, fine gold particles, and other trace elements being trapped in marine environments. Mechanical coagulation and aggregation resulted in gold enrichments by 2–3 orders of magnitude, whereas some of the gold in these marine shales can be reconciled by seawater adsorption into sedimentary pyrite.
For the source of gold and PGEs in the studied marine shales in the Kaapvaal Craton, a genetic model is proposed that involves the following:
(1) A highly siderophile elements enriched upper mantle domain, herein referred to as “geochemically anomalous mantle domain”, from which the Kaapvaal crust was sourced. This mantle domain enriched in highly siderophile elements was formed either by inhomogeneous mixing with cosmic material that was added during intense meteorite bombardment of the Hadaean to Palaeoarchaean Earth or by plume-like ascent of relics from the core–mantle boundary. In both cases, elevated siderophile elements concentrations would be expected. The geochemically anomalous mantle domain is likely the ultimate source of the Witwatersrand modified palaeoplacer gold deposits and was tapped again ca. 2.054 Ga during the emplacement of the Bushveld Igneous Complex. Therefore, I propose that there is a genetic link (i.e. common geochemically anomalous mantle source) between the Witwatersrand gold deposits and the younger Bushveld Igneous Complex PGE deposits.
(2) Scavenging of crustal gold by various surface processes such as trapping of gold from Archaean/Palaeoproterozoic river water on the surface of local photosynthesizing cyanobacterial or microbial mats, and reworking of these mats into erosion channels during flooding events.
The above two models complement each other, with model (1) providing a common geological source for the Witwatersrand gold and Bushveld Igneous Complex PGE deposits, and model (2) explaining the processes responsible for Witwatersrand-type gold pre-concentration processes. In sequences such as the Transvaal Supergroup, a less fertile hinterland and/or less reworking of older sediments led to a correspondingly lower gold endowment. These findings indicate temporal distribution of siderophile elements in the upper crust (e.g. marine shales). The overall implications of these findings are that background concentrations of gold and PGEs can be used to target potential exploration areas in other cratons of similar age. This increases the likelihood of finding other Witwatersrand-type gold or Bushveld Igneous Complex-type PGE deposits in other cratons.
In this study, polarimetric Synthetic Aperture Radar (PolSAR) data at X-, C- and L-Bands, acquired by the satellites: TerraSAR-X (2011), Radarsat-2 (2011), ALOS (2010) and ALOS-2 (2016), were used to characterize the tundra land cover of a test site located close to the town of Tuktoyaktuk, NWT, Canada. Using available in situ ground data collected in 2010 and 2012, we investigate PolSAR scattering characteristics of common tundra land cover classes at X-, C- and L-Bands. Several decomposition features of quad-, co-, and cross-polarized data were compared, the correlation between them was investigated, and the class separability offered by their different feature spaces was analyzed. Certain PolSAR features at each wavelength were sensitive to the land cover and exhibited distinct scattering characteristics. Use of shorter wavelength imagery (X and C) was beneficial for the characterization of wetland and tundra vegetation, while L-Band data highlighted differences of the bare ground classes better. The Kennaugh Matrix decomposition applied in this study provided a unified framework to store, process, and analyze all data consistently, and the matrix offered a favorable feature space for class separation. Of all elements of the quad-polarized Kennaugh Matrix, the intensity based elements K0, K1, K2, K3 and K4 were found to be most valuable for class discrimination. These elements contributed to better class separation as indicated by an increase of the separability metrics squared Jefferys Matusita Distance and Transformed Divergence. The increase in separability was up to 57% for Radarsat-2 and up to 18% for ALOS-2 data.
Long-term slash-and-burn experiments, when compared with intensive tillage without manuring, resulted in a huge data set relating to potential crop yields, depending on soil quality, crop type, and agricultural measures. Cultivation without manuring or fallow phases did not produce satisfying yields, and mono-season cropping on freshly cleared and burned plots resulted in rather high yields, comparable to those produced during modern industrial agriculture - at least ten-fold the ones estimated for the medieval period. Continuous cultivation on the same plot, using imported wood from adjacent areas as fuel, causes decreasing yields over several years. The high yield of the first harvest of a slash-and-burn agriculture is caused by nutrient input through the ash produced and mobilization from the organic matter of the topsoil, due to high soil temperatures during the burning process and higher topsoil temperatures due to the soil’s black surface. The harvested crops are pure, without contamination of any weeds. Considering the amount of work required to fight weeds without burning, the slash-and-burn technique yields much better results than any other tested agricultural approach. Therefore, in dense woodland, without optimal soils and climate, slash-and-burn agriculture seems to be the best, if not the only, feasible method to start agriculture, for example, during the Late Neolithic, when agriculture expanded from the loess belt into landscapes less suitable for agriculture. Extensive and cultivation with manuring is more practical in an already-open landscape and with a denser population, but its efficiency in terms of the ratio of the manpower input to food output, is worse. Slash-and-burn agriculture is not only a phenomenon of temperate European agriculture during the Neolithic, but played a major role in land-use in forested regions worldwide, creating anthromes on a huge spatial scale.
Nearly a quarter of the Alpine area is covered by a dense network of large protected areas (LPAs) of the four categories national park(NP), biosphere reserve (BR), nature park and world natural heritage site (WNHS). From the time of early industrialization, the Alpine area has undergone a mixed and increasingly polarized demographic development between the poles of immigration and emigration. This article investigates the possible mutual impact of population development and the existence of LPAs. The research design includes a quantitative survey of all Alpine LPAs in terms of their population development and the structure of immigration in the first decade of the 21st century. This will be linked with qualitative expert interviews in four selected NPs. The overall results allow an interpretation of the statistical
correlations between type of LPA and migration.
As a cradle of ancient Chinese civilization, the Yellow River Basin has a very long human-environment interrelationship, where early anthropogenic activities re- sulted in large scale landscape modifications. Today, the impact of this relationship
has intensified further as the basin plays a vital role for China’s continued economic
development. It is one of the most densely-populated, fastest growing, and most dynamic
regions of China with abundant natural and environmental resources providing a livelihood for almost 190 million people. Triggered by fundamental economic reforms, the
basin has witnessed a spectacular economic boom during the last decades and can be
considered as an exemplary blueprint region for contemporary dynamic Global Change
processes occurring throughout the country, which is currently transitioning from an
agrarian-dominated economy into a modern urbanized society. However, this resourcesdemanding growth has led to profound land use changes with adverse effects on the Yellow
River social-ecological systems, where complex challenges arise threatening a long-term
sustainable development.
Consistent and continuous remote sensing-based monitoring of recent and past land
cover and land use change is a fundamental requirement to mitigate the adverse impacts
of Global Change processes. Nowadays, technical advancement and the multitude of
available satellite sensors, in combination with the opening of data archives, allow the
creation of new research perspectives in regional land cover applications over heterogeneous landscapes at large spatial scales. Despite the urgent need to better understand the
prevailing dynamics and underlying factors influencing the current processes, detailed
regional specific land cover data and change information are surprisingly absent for this
region.
In view of the noted research gaps and contemporary developments, three major objectives are defined in this thesis. First (i), the current and most pressing social-ecological
challenges are elaborated and policy and management instruments towards more sustainability are discussed. Second (ii), this thesis provides new and improved insights on
the current land cover state and dynamics of the entire Yellow River Basin. Finally (iii),
the most dominant processes related to mining, agriculture, forest, and urban dynamics
are determined on finer spatial and temporal scales.
The complex and manifold problems and challenges that result from long-term abuse
of the water and land resources in the basin have been underpinned by policy choices,
cultural attitude, and institutions that have evolved over centuries in China. The tremendous economic growth that has been mainly achieved by extracting water and exploiting
land resources in a rigorous, but unsustainable manner, might not only offset the economic benefits, but could also foster social unrest. Since the early emergence of the first Chinese dynasties, flooding was considered historically as a primary issue in river management and major achievements have been made to tame the wild nature of the Yellow
River. Whereas flooding is therefore largely now under control, new environmental and
social problems have evolved, including soil and water pollution, ecological degradation,
biodiversity decline, and food security, all being further aggravated by anthropogenic
climate change. To resolve the contemporary and complex challenges, many individual
environmental laws and regulations have been enacted by various Chinese ministries.
However, these policies often pursue different, often contradictory goals, are too general
to tackle specific problems and are usually implemented by a strong top-down approach.
Recently, more flexible economic and market-based incentives (pricing, tradable permits,
investments) have been successfully adopted, which are specifically tailored to the respective needs, shifting now away from the pure command and regulating instruments.
One way towards a more holistic and integrated river basin management could be the
establishment of a common platform (e.g. a Geographical Information System) for data
handling and sharing, possibly operated by the Yellow River Basin Conservancy Commission (YRCC), where available spatial data, statistical information and in-situ measures
are coalesced, on which sustainable decision-making could be based. So far, the collected
data is hardly accessible, fragmented, inconsistent, or outdated.
The first step to address the absence and lack of consistent and spatially up-to-date
information for the entire basin capturing the heterogeneous landscape conditions was
taken up in this thesis. Land cover characteristics and dynamics were derived from
the last decade for the years 2003 and 2013, based on optical medium-resolution hightemporal MODIS Normalized Differenced Vegetation Index (NDVI) time series at 250 m.
To minimize the inherent influence of atmospheric and geometric interferences found in
raw high temporal data, the applied adaptive Savitzky-Golay filter successfully smoothed
the time series and substantially reduced noise. Based on the smoothed time series
data, a large variety of intra-annual phenology metrics as well as spectral and multispectral annual statistics were derived, which served as input variables for random
forest (RF) classifiers. High quality reference data sets were derived from very high
resolution imagery for each year independently of which 70 % trained the RF models. The
accuracy assessments for all regionally specific defined thematic classes were based on the
remaining 30 % reference data split and yielded overall accuracies of 87 % and 84 % for
2003 and 2013, respectively. The first regional adapted Yellow River Land Cover Products
(YRB LC) depict the detail spatial extent and distribution of the current land cover status
and dynamics. The novel products overall differentiate overall 18 land cover and use
classes, including classes of natural vegetation (terrestrial and aquatic), cultivated classes,
mosaic classes, non-vegetated, and artificial classes, which are not presented in previous
land cover studies so far.
Building on this, an extended multi-faceted land cover analysis on the most prominent
land cover change types at finer spatial and temporal scales provides a better and more
detailed picture of the Yellow River Basin dynamics. Precise spatio-temporal products
about mining, agriculture, forest, and urban areas were examined from long-trem Landsat
satellite time series monitored at annual scales to capture the rapid rate of change in four
selected focus regions. All archived Landsat images between 2000 and 2015 were used to
derive spatially continuous spectral-temporal, multi-spectral, and textural metrics. For
each thematic region and year RF models were built, trained and tested based on a stablepixels reference data set. The automated adaptive signature (AASG) algorithm identifies those pixels that did not change between the investigated time periods to generate a
mono-temporal reference stable-pixels data set to keep manual sampling requirements
to a minimum level. Derived results gained high accuracies ranging from 88 % to 98 %.
Throughout the basin, afforestation on the Central Loess Plateau and urban sprawl are
identified as most prominent drivers of land cover change, whereas agricultural land
remained stable, only showing local small-scale dynamics. Mining operations started in
2004 on the Qinghai-Tibet Plateau, which resulted in a substantial loss of pristine alpine
meadows and wetlands.
In this thesis, a novel and unique regional specific view of current and past land cover
characteristics in a complex and heterogeneous landscape was presented by using a
multi-source remote sensing approach. The delineated products hold great potential for
various model and management applications. They could serve as valuable components
for effective and sustainable land and water management to adapt and mitigate the
predicted consequences of Global Change processes.
West Africa is one of the fastest growing regions in the world with annual population growth rates of more than three percent for several countries. Since the 1950s, West Africa experienced a fivefold increase of inhabitants, from 71 to 353 million people in 2015 and it is expected that the region’s population will continue to grow to almost 800 million people by the year 2050. This strong trend has and will have serious consequences for food security since agricultural productivity is still on a comparatively low level in most countries of West Africa. In order to compensate for this low productivity, an expansion of agricultural areas is rapidly progressing. The mapping and monitoring of agricultural areas in West Africa is a difficult task even on the basis of remote sensing. The small scale extensive farming practices with a low level of agricultural inputs and mechanization make the delineation of cultivated land from other land cover and land use (LULC) types highly challenging. In addition, the frequent cloud coverage in the region considerably decreases the availability of earth observation datasets. For the accurate mapping of agricultural area in West Africa, high temporal as well as spatial resolution is necessary to delineate the small-sized fields and to obtain data from periods where different LULC types are distinguishable. However, such consistent time series are currently not available for West Africa. Thus, a spatio-temporal data fusion framework was developed in this thesis for the generation of high spatial and temporal resolution time series.
Data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) enjoyed increasing popularity during recent years but they have hardly been used for the application on larger scales. In order to make it applicable for this purpose and to increase the input data availability, especially in cloud-prone areas such as West Africa, the ESTARFM framework was developed in this thesis introducing several enhancements. An automatic filling of cloud gaps was included in the framework in order to use even partly cloud-covered Landsat images for the fusion without producing gaps on the output images. In addition, the ESTARFM algorithm was improved to automatically account for regional differences in the heterogeneity of the study region. Further improvements comprise the automation of the time series generation as well as the significant acceleration of the processing speed through parallelization. The performance of the developed ESTARFM framework was tested by fusing an 8-day NDVI time series from Landsat and MODIS data for a focus area of 98,000 km² in the border region between Burkina Faso and Ghana. The results of this test show the capability of the ESTARFM framework to accurately produce high temporal resolution time series while maintaining the spatial detail, even in such a heterogeneous and cloud-prone region.
The successfully tested framework was subsequently applied to generate consistent time series as the basis for the mapping of agricultural area in Burkina Faso for the years 2001, 2007, and 2014. In a first step, high temporal (8-day) and high spatial (30 m) resolution NDVI time series for the entire country and the three years were derived with the ESTARFM framework. More than 500 Landsat scenes and 3000 MODIS scenes were automatically processed for this purpose. From the fused ESTARFM NDVI time series, phenological metrics were extracted and together with the single time steps of NDVI served as input for the delineation of rainfed agricultural areas, irrigated agricultural areas and plantations. The classification was conducted with the random forest algorithm at a 30 m spatial resolution for entire Burkina Faso and the three years 2001, 2007, and 2014. For the training and validation of the classifier, a randomly sampled reference dataset was generated from Google Earth images based on expert knowledge of the region. The overall classification accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the developed methodology. The resulting maps show an expansion of agricultural area of 91% from about 61,000 km² in 2001 to 116,900 km² in 2014. While rainfed agricultural areas account for the major part of this increase, irrigated areas and plantations also spread considerably. Especially the expansion of irrigation systems and plantation area can be explained by the promotion through various national and international development projects. The increase of agricultural areas goes in line with the rapid population growth in most of Burkina Faso’s provinces which still had available land resources for an expansion of agricultural area. An analysis of the development of agricultural areas in the vicinity of protected areas highlighted the increased human pressure on these reserves. The protection of the remnant habitats for flora and fauna while at the same time improving food security for a rapidly growing population, are the major challenges for the region in the future.
The developed ESTARFM framework showed great potential beyond its utilization for the mapping of agricultural area. Other large-scale research that requires a sufficiently high temporal and spatial resolution such as the monitoring of land degradation or the investigation of land surface phenology could greatly benefit from the application of this framework.
Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.
Inadequate land management and agricultural activities have largely resulted in land degradation in Burkina Faso. The nationwide governmental and institutional driven implementation and adoption of soil and water conservation measures (SWCM) since the early 1960s, however, is expected to successively slow down the degradation process and to increase the agricultural output. Even though relevant measures have been taken, only a few studies have been conducted to quantify their effect, for instance, on soil erosion and environmental restoration. In addition, a comprehensive summary of initiatives, implementation strategies, and eventually region-specific requirements for adopting different SWCM is missing. The present study therefore aims to review the different SWCM in Burkina Faso and implementation programs, as well as to provide information on their effects on environmental restoration and agricultural productivity. This was achieved by considering over 143 studies focusing on Burkina Faso’s experience and research progress in areas of SWCM and soil erosion. SWCM in Burkina Faso have largely resulted in an increase in agricultural productivity and improvement in food security. Finally, this study aims at supporting the country’s informed decision-making for extending already existing SWCM and for deriving further implementation strategies.
The command area of the Rakh branch canal grows wheat, sugarcane, and rice crops in abundance. The canal water, which is trivial for irrigating these crops, is conveyed to the farms through the network of canals and distributaries. For the maintenance of this vast infrastructure; the end users are charged on a seasonal basis. The present water charges are severely criticized for not being adequate to properly manage the entire infrastructure. We use the residual value to determine the value of the irrigation water and then based on the quantity of irrigation water supplied to farm land coupled with the infrastructure maintenance cost, full cost recovery figures are executed for the study area, and policy recommendations are made for the implementation of the full cost recovery system. The approach is unique in the sense that the pricings are based on the actual quantity of water conveyed to the field for irrigating crops. The results of our analysis showed that the canal water is severely under charged in the culturable command area of selected distributaries, thus negating the plan of having a self-sustainable irrigation system.
The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971–1999/2000) and future (2070/2071–2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.
The focus of this analysis is on the early detection of forest health changes, specifically that of Norway spruce (Picea abies L. Karst.). In this analysis, we planned to examine the time (degree of early detection), spectral wavelengths and appropriate method for detecting vitality changes. To accomplish this, a ring-barking experiment with seven subsequent laboratory needle measurements was carried out in 2013 and 2014 in an area in southeastern Germany near Altötting. The experiment was also accompanied by visual crown condition assessment. In total, 140 spruce trees in groups of five were ring-barked with the same number of control trees in groups of five that were selected as reference trees in order to compare their development. The laboratory measurements were analysed regarding the separability of ring-barked and control samples using spectral reflectance, vegetation indices and derivative analysis. Subsequently, a random forest classifier for determining important spectral wavelength regions was applied. Results from the methods are consistent and showed a high importance of the visible (VIS) spectral region, very low importance of the near-infrared (NIR) and minor importance of the shortwave infrared (SWIR) spectral region. Using spectral reflectance data as well as indices, the earliest separation time was found to be 292 days after ring-barking. The derivative analysis showed that a significant separation was observed 152 days after ring-barking for six spectral features spread through VIS and SWIR. A significant separation was detected using a random forest classifier 292 days after ring-barking with 58% separability. The visual crown condition assessment was analysed regarding obvious changes of vitality and the first indication was observed 302 days after ring-barking as bark beetle infestation and yellowing of foliage in the ring-barked trees only. This experiment shows that an early detection, compared with visual crown assessment, is possible using the proposed methods for this specific data set. This study will contribute to ongoing research for early detection of vitality changes that will support foresters and decision makers.
The use of inverse methods allow efficient model calibration. This study employs PEST to calibrate a large catchment scale transient flow model. Results are demonstrated by comparing manually calibrated approaches with the automated approach. An advanced Tikhonov regularization algorithm was employed for carrying out the automated pilot point (PP) method. The results indicate that automated PP is more flexible and robust as compared to other approaches. Different statistical indicators show that this method yields reliable calibration as values of coefficient of determination (R-2) range from 0.98 to 0.99, Nash Sutcliffe efficiency (ME) range from 0.964 to 0.976, and root mean square errors (RMSE) range from 1.68 m to 1.23 m, for manual and automated approaches, respectively. Validation results of automated PP show ME as 0.969 and RMSE as 1.31 m. The results of output sensitivity suggest that hydraulic conductivity is a more influential parameter. Considering the limitations of the current study, it is recommended to perform global sensitivity and linear uncertainty analysis for the better estimation of the modelling results.
Impervious surface areas (ISA) are heavily influenced by urban structure and related structural features. We examined the effects of object-based impervious surface spatial pattern analysis on land surface temperature and population density in Guangzhou, China, in comparison to classic per-pixel analyses. An object-based support vector machine (SVM) and a linear spectral mixture analysis (LSMA) were integrated to estimate ISA fraction using images from the Chinese HJ-1B satellite for 2009 to 2011. The results revealed that the integrated object-based SVM-LSMA algorithm outperformed the traditional pixel-wise LSMA algorithm in classifying ISA fraction. More specifically, the object-based ISA spatial patterns extracted were more suitable than pixel-wise patterns for urban heat island (UHI) studies, in which the UHI areas (landscape surface temperature >37 °C) generally feature high ISA fraction values (ISA fraction >50%). In addition, the object-based spatial patterns enable us to quantify the relationship of ISA with population density (correlation coefficient >0.2 in general), with global human settlement density (correlation coefficient >0.2), and with night-time light map (correlation coefficient >0.4), and, whereas pixel-wise ISA did not yield significant correlations. These results indicate that object-based spatial patterns have a high potential for UHI detection and urbanization monitoring. Planning measures that aim to reduce the urbanization impacts and UHI intensities can be better supported.
Urban areas are population, culture and infrastructure concentration points. Electricity blackouts or interruptions of water supply severely affect people when happening unexpected and at large scale. Interruptions of such infrastructure supply services alone have the potential to trigger crises. But when happening in concert with or as a secondary effect of an earthquake, for example, the crisis situation is often aggravated. This is the case for any country, but it has been observed that even highly industrialised
countries face severe risks when their degree of acquired dependency on services of what is termed Critical Infrastructure results in even bigger losses when occurring unexpectedly in a setting that usually has high reliability of services.
Optical remote sensing is an important tool in the study of animal behavior providing ecologists with the means to understand species-environment interactions in combination with animal movement data. However, differences in spatial and temporal resolution between movement and remote sensing data limit their direct assimilation. In this context, we built a data-driven framework to map resource suitability that addresses these differences as well as the limitations of satellite imagery. It combines seasonal composites of multiyear surface reflectances and optimized presence and absence samples acquired with animal movement data within a cross-validation modeling scheme. Moreover, it responds to dynamic, site-specific environmental conditions making it applicable to contrasting landscapes. We tested this framework using five populations of White Storks (Ciconia ciconia) to model resource suitability related to foraging achieving accuracies from 0.40 to 0.94 for presences and 0.66 to 0.93 for absences. These results were influenced by the temporal composition of the seasonal reflectances indicated by the lower accuracies associated with higher day differences in relation to the target dates. Additionally, population differences in resource selection influenced our results marked by the negative relationship between the model accuracies and the variability of the surface reflectances associated with the presence samples. Our modeling approach spatially splits presences between training and validation. As a result, when these represent different and unique resources, we face a negative bias during validation. Despite these inaccuracies, our framework offers an important basis to analyze species-environment interactions. As it standardizes site-dependent behavioral and environmental characteristics, it can be used in the comparison of intra- and interspecies environmental requirements and improves the analysis of resource selection along migratory paths. Moreover, due to its sensitivity to differences in resource selection, our approach can contribute toward a better understanding of species requirements.
Via providing various ecosystem services, the old-growth Hyrcanian forests play a crucial role in the environment and anthropogenic aspects of Iran and beyond. The amount of growing stock volume (GSV) is a forest biophysical parameter with great importance in issues like economy, environmental protection, and adaptation to climate change. Thus, accurate and unbiased estimation of GSV is also crucial to be pursued across the Hyrcanian. Our goal was to investigate the potential of ALOS-2 and Sentinel-1's polarimetric features in combination with Sentinel-2 multi-spectral features for the GSV estimation in a portion of heterogeneously-structured and mountainous Hyrcanian forests. We used five different kernels by the support vector regression (nu-SVR) for the GSV estimation. Because each kernel differently models the parameters, we separately selected features for each kernel by a binary genetic algorithm (GA). We simultaneously optimized R\(^2\) and RMSE in a suggested GA fitness function. We calculated R\(^2\), RMSE to evaluate the models. We additionally calculated the standard deviation of validation metrics to estimate the model's stability. Also for models over-fitting or under-fitting analysis, we used mean difference (MD) index. The results suggested the use of polynomial kernel as the final model. Despite multiple methodical challenges raised from the composition and structure of the study site, we conclude that the combined use of polarimetric features (both dual and full) with spectral bands and indices can improve the GSV estimation over mixed broadleaf forests. This was partially supported by the use of proposed evaluation criterion within the GA, which helped to avoid the curse of dimensionality for the applied SVR and lowest over estimation or under estimation.
Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an overview of validation approaches concerning temporally dense time-series of land surface geo-information products that cover the continental to global scale. Categorization according to utilized validation data revealed that product intercomparisons and comparison to reference data are the conventional validation methods. The reviewed studies are mainly based on optical sensors and orientated towards global coverage, with vegetation-related variables as the focus. Trends indicate an increase in remote sensing-based studies that feature long-term datasets of land surface variables. The hereby corresponding validation efforts show only minor methodological diversification in the past two decades. To sustain comprehensive and standardized validation efforts, the provision of spatiotemporally dense validation data in order to estimate actual differences between measurement and the true state has to be maintained. The promotion of novel approaches can, on the other hand, prove beneficial for various downstream applications, although typically only theoretical uncertainties are provided.
Estimating penetration-related X-band InSAR elevation bias: a study over the Greenland ice sheet
(2019)
Accelerating melt on the Greenland ice sheet leads to dramatic changes at a global scale. Especially in the last decades, not only the monitoring, but also the quantification of these changes has gained considerably in importance. In this context, Interferometric Synthetic Aperture Radar (InSAR) systems complement existing data sources by their capability to acquire 3D information at high spatial resolution over large areas independent of weather conditions and illumination. However, penetration of the SAR signals into the snow and ice surface leads to a bias in measured height, which has to be corrected to obtain accurate elevation data. Therefore, this study purposes an easy transferable pixel-based approach for X-band penetration-related elevation bias estimation based on single-pass interferometric coherence and backscatter intensity which was performed at two test sites on the Northern Greenland ice sheet. In particular, the penetration bias was estimated using a multiple linear regression model based on TanDEM-X InSAR data and IceBridge laser-altimeter measurements to correct TanDEM-X Digital Elevation Model (DEM) scenes. Validation efforts yielded good agreement between observations and estimations with a coefficient of determination of R\(^2\) = 68% and an RMSE of 0.68 m. Furthermore, the study demonstrates the benefits of X-band penetration bias estimation within the application context of ice sheet elevation change detection.
Peatlands located on slopes (herein called slope bogs) are typical landscape units in the Hunsrueck, a low mountain range in Southwestern Germany. The pathways of the water feeding the slope bogs have not yet been documented and analyzed. The identification of the different mechanisms allowing these peatlands to originate and survive requires a better understanding of the subsurface lithology and hydrogeology. Hence, we applied a multi-method approach to two case study sites in order to characterize the subsurface lithology and to image the variable spatio-temporal hydrological conditions. The combination of Electrical Resistivity Tomography (ERT) and an ERT-Monitoring and Ground Penetrating Radar (GPR), in conjunction with direct methods and data (borehole drilling and meteorological data), allowed us to gain deeper insights into the subsurface characteristics and dynamics of the peatlands and their catchment area. The precipitation influences the hydrology of the peatlands as well as the interflow in the subsurface. Especially, the geoelectrical monitoring data, in combination with the precipitation and temperature data, indicate that there are several forces driving the hydrology and hydrogeology of the peatlands. While the water content of the uppermost layers changes with the weather conditions, the bottom layer seems to be more stable and changes to a lesser extent. At the selected case study sites, small differences in subsurface properties can have a huge impact on the subsurface hydrogeology and the water paths. Based on the collected data, conceptual models have been deduced for the two case study sites.
Central Europe experienced several droughts in the recent past, such as in the year 2018, which was characterized by extremely low rainfall rates and high temperatures, resulting in substantial agricultural yield losses. Time series of satellite earth observation data enable the characterization of past drought events over large temporal and spatial scales. Within this study, Moderate Resolution Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) (MOD13Q1) 250 m time series were investigated for the vegetation periods of 2000 to 2018. The spatial and temporal development of vegetation in 2018 was compared to other dry and hot years in Europe, like the drought year 2003. Temporal and spatial inter- and intra-annual patterns of EVI anomalies were analyzed for all of Germany and for its cropland, forest, and grassland areas individually. While vegetation development in spring 2018 was above average, the summer months of 2018 showed negative anomalies in a similar magnitude as in 2003, which was particularly apparent within grassland and cropland areas in Germany. In contrast, the year 2003 showed negative anomalies during the entire growing season. The spatial pattern of vegetation status in 2018 showed high regional variation, with north-eastern Germany mainly affected in June, north-western parts in July, and western Germany in August. The temporal pattern of satellite-derived EVI deviances within the study period 2000-2018 were in good agreement with crop yield statistics for Germany. The study shows that the EVI deviation of the summer months of 2018 were among the most extreme in the study period compared to other years. The spatial pattern and temporal development of vegetation condition between the drought years differ.