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Institute
- Institut für Geographie und Geologie (114)
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- 20-3044-2-11 (1)
- 308377 (1)
- 714087 (1)
- 776019 (1)
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.
The Kunduz River is one of the main tributaries of the Amu Darya Basin in North Afghanistan. Many communities live in the Kunduz River Basin (KRB), and its water resources have been the basis of their livelihoods for many generations. This study investigates climate change impacts on the KRB catchment. Rare station data are, for the first time, used to analyze systematic trends in temperature, precipitation, and river discharge over the past few decades, while using Mann–Kendall and Theil–Sen trend statistics. The trends show that the hydrology of the basin changed significantly over the last decades. A comparison of landcover data of the river basin from 1992 and 2019 shows significant changes that have additional impact on the basin hydrology, which are used to interpret the trend analysis. There is considerable uncertainty due to the data scarcity and gaps in the data, but all results indicate a strong tendency towards drier conditions. An extreme warming trend, partly above 2 °C since the 1960s in combination with a dramatic precipitation decrease by more than −30% lead to a strong decrease in river discharge. The increasing glacier melt compensates the decreases and leads to an increase in runoff only in the highland parts of the upper catchment. The reduction of water availability and the additional stress on the land leads to a strong increase of barren land and a reduction of vegetation cover. The detected trends and changes in the basin hydrology demand an active management of the already scarce water resources in order to sustain water supply for agriculture and ecosystems in the KRB.
The coast of Aqaba and the Aqaba region (Jordan) were investigated on their hydrogeo-ecosystem. The results of the research were translated into digits to build a geo-spatial data base. The fillings of the graben aquifer receive indirect type of recharge through the side wadis which drain the highlands. Surface water balance was modeled for a period of 20 years of daily climate records using MODBIL program which attributes direct recharge to wet years only. The hydrodynamic fresh water/seawater interface in the coastal zones was investigated by applying vertical geoelectric surveys and models of several methods to confirm its coincidence with the aquifer’s flow amounts, where human impacts in terms of over-pumping allowed more encroachment of seawater into land, and unintended recharge which led to seaward interface migration. A groundwater balance and solute transport were approached by developing a flow model from the hydrogeological and hydrochemical data. The nature of soil cover and aquifer whose physical properties enhance human impacts indicated the vulnerability of groundwater to pollution. This certainly threatens the marine ecology which forms the sink where the in-excess flow ends. The constructed digital background was exported into GIS to sub-zone the study area in terms of the aquifer’s vulnerability to pollution risks using DRASTIC index. However, it was unable to meet all geo-spatial factors that proved to have significant impacts on the vulnerability. Consequently, a comprehensive index -SALUFT- was developed. This suggests the suitable land use units for each zone in the light of vulnerability grades aiming at protecting the available groundwater resources.
Two phases of reef sampling were carried out. The first included regular samples taken along the coastline of Aqaba (27km long) at depths of 4-15m, and used to determine spatial distribution of pollution. The second phase included three 20cm-deep cores obtained from within the industrial zone. These cores were drilled from pre-dated communities, where the growth rate was determined earlier to be 10mm y-1, therefore the core obtained represented a period of 20 years (i.e. 1980-2000). The cores were used to reconstruct the metal pollution history at the most heavily used site along the coast (industrial zone).All samples were examined with respect to their metal content of Cd, Pb, Cu, Zn, Ni, and Cr. Almost all of them have shown records above the calculated background values. Mean values of Cd, Pb, Cu, Zn, Ni and Cr recorded along the coast were 1,25; 4,26; 9,76; 11,40; 2,29 and 10,522, µg g-1 respectively, and for core samples 1.4; 4.2; 5.7; 6.4; 2.3 and 8.21 µg g-1 respectively. Spatial distribution of metal enrichment in reef samples have shown a general and clear increasing trend towards the south. Same increasing trend was also in core samples where the six metals have shown a prominent increasing trend towards the core surface indicating an increase of coastal activities during the last twenty years. High and relatively high values were recorded at the oil port, the industrial area and main port, and thus categorized as highly impacted areas. Intermediate metal content were recorded in samples of the north beach, and thus classified as being relatively impacted, where the lowest metal concentrations were observed at the marine reserve, the least impacted site along the coast. The high enrichment of metal is attributed mainly to anthropogenic impacts. The natural inputs of the six metals studied in the Gulf of Aqaba are generally very low, due to the geographic positions and the absence of wadi discharge and as a result of low rainfall. Several potential sources of heavy metals were investigated. The industrial-related activities, port operations and phosphate dust were among the main sources currently threatening the marine ecosystem in Aqaba. Applying the Principle Components Analysis method (PCA) to all samples taken along the coastline has resulted in categorizing three different groups according to their metal enrichment, the first is composed of samples taken from the north beach and the main port with intermediate to high enrichment, the second joined the samples of the marine park and the marine reserve with low and relatively low enrichment, and the last group joined samples of the industrial zone and the oil port with high enrichment. The Principle Component Scores were also utilized to confirm the spatial distribution and relationships of the examined heavy metals along the coast. Two models (interpolated by SURFER  7.0 and ArcView 3.2a) were developed, the first was based on the PC scores of the first component, and shows clearly the positive anomalies in metal concentrations along the coast. The second model was developed by plotting the second factor scores on a landuse map of Aqaba. According to these models, it has shown that the positive anomalies are associated with three different zones; industrial area, the main port and the oil port. The results have shown that coral reefs can be used as good environmental indicator for assessments and monitoring processes, and they can provide data and information on both the spatial distribution of pollution and their history. The present work is the first to document the environmental status along the whole coast of Aqaba and the first to use coral reef as a tool/ indicator.
In a three-year study the current aeolian transportation processes were examined in a linear dune area previously used for grazing near Nizzana at the Israeli-Egyptian border. The research area was subject to heavy grazing across the border, which led to the total destruction of the natural vegetation in the period of 1967 to 1982. As a consequence, intensified aeolian activity and significant changes of the morphology of the dunes were observed. After the end of the grazingg on the Israeli side, a rapid return of the vegetation in the interdune corridors and on the footslopes of the dunes took place. In addition also a reduction of obviously active areas on the dune crests was observed. The situation on Egyptian territory west the border remained unchanged until today. This study is aimed at understanding the changed aeolian morphodynamics east the border. The emphasis was placed on the investigation of the spatial and temporal distribution of aeolian sand transport as well as on the influencing factors morphology, surface condition and vegetation.
The Niger Delta belongs to the largest swamp and mangrove forests in the world hosting many endemic and endangered species. Therefore, its conservation should be of highest priority. However, the Niger Delta is confronted with overexploitation, deforestation and pollution to a large extent. In particular, oil spills threaten the biodiversity, ecosystem services, and local people. Remote sensing can support the detection of spills and their potential impact when accessibility on site is difficult. We tested different vegetation indices to assess the impact of oil spills on the land cover as well as to detect accumulations (hotspots) of oil spills. We further identified which species, land cover types, and protected areas could be threatened in the Niger Delta due to oil spills. The results showed that the Enhanced Vegetation Index, the Normalized Difference Vegetation Index, and the Soil Adjusted Vegetation Index were more sensitive to the effects of oil spills on different vegetation cover than other tested vegetation indices. Forest cover was the most affected land-cover type and oil spills also occurred in protected areas. Threatened species are inhabiting the Niger Delta Swamp Forest and the Central African Mangroves that were mainly affected by oil spills and, therefore, strong conservation measures are needed even though security issues hamper the monitoring and control.
Numerous ephemeral rivers and thousands of natural pans characterize the transboundary Iishana-System of the Cuvelai Basin between Namibia and Angola. After the rainy season, surface water stored in pans is often the only affordable water source for many people in rural areas. High inter- and intra-annual rainfall variations in this semiarid environment provoke years of extreme flood events and long periods of droughts. Thus, the issue of water availability is playing an increasingly important role in one of the most densely populated and fastest growing regions in southwestern Africa. Currently, there is no transnational approach to quantifying the potential storage and supply functions of the Iishana-System. To bridge these knowledge gaps and to increase the resilience of the local people's livelihood, suitable pans for expansion as intermediate storage were identified and their metrics determined. Therefore, a modified Blue Spot Analysis was performed, based on the high-resolution TanDEM-X digital elevation model. Further, surface area–volume ratio calculations were accomplished for finding suitable augmentation sites in a first step. The potential water storage volume of more than 190,000 pans was calculated at 1.9 km\(^3\). Over 2200 pans were identified for potential expansion to facilitate increased water supply and flood protection in the future.
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.
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.
Environmental interlinked problems such as human-induced land cover change, water scarcity, loss in soil fertility, and anthropogenic climate change are expected to affect the viability of agriculture and increase food insecurity in many developing countries. Climate change is certainly the most serious of these challenges for the twenty-first century. The poorest regions of the world – tropical West Africa included – are the most vulnerable due to their high dependence on climate and weather sensitive activities such as agriculture, and the widespread poverty that limits the institutional and economic capacities to adapt to the new stresses brought about by climate change. Climate change is already acting negatively on the poor smallholders of tropical West Africa whose livelihoods dependent mainly on rain-fed agriculture that remains the cornerstone of the economy in the region. Adaptation of the agricultural systems to climate change effects is, therefore, crucial to secure the livelihoods of these rural communities. Since information is a key for decision-making, it is important to provide well-founded information on the magnitude of the impacts in order to design appropriate and sustainable adaptation strategies.
Considering the case of agricultural production in the Republic of Benin, this study aims at using large-scale climatic predictors to assess the potential impacts of past and future climate change on agricultural productivity at a country scale in West Africa. Climate signals from large-scale circulation were used because state-of-the art regional climate models (RCM) still do not perfectly resolve synoptic and mesoscale convective processes. It was hypothesised that in rain-fed systems with low investments in agricultural inputs, yield variations are widely governed by climatic factors. Starting with pineapple, a perennial fruit crops, the study further considered some annual crops such as cotton in the group of fibre crops, maize, sorghum and rice in the group of cereals, cowpeas and groundnuts belonging to the legume crops, and cassava and yams which are root and tuber crops. Thus the selected crops represented the three known groups of photosynthetic pathways (i.e. CAM, C3, and C4 plants).
In the study, use was made of the historical agricultural yield statistics for the Republic of Benin, observed precipitation and mean near-surface air temperature data from the Climatic Research Unit (CRU TS 3.1) and the corresponding variables simulated by the regional climate model (RCM) REMO. REMO RCM was driven at its boundaries by the global climate model ECHAM 5. Simulations with different greenhouse gas concentrations (SRES-A1B and B1 emission scenarios) and transient land cover change scenarios for present-day and future conditions were considered. The CRU data were submitted to empirical orthogonal functions analysis over the north hemispheric part of Africa to obtain large-scale observed climate predictors and associated consistent variability modes. REMO RCM data for the same region were projected on the derived climate patterns to get simulated climate predictors. By means of cross-validated Model Output Statistics (MOS) approach combined with Bayesian model averaging (BMA) techniques, the observed climate predictors and the crop predictand were further on used to derive robust statistical relationships. The robust statistical crop models perform well with high goodness-of-fit coefficients (e.g. for all combined crop models: 0.49 ≤ R2 ≤ 0.99; 0.28 ≤ Brier-Skill-Score ≤ 0.90).
Provided that REMO RCM captures the main features of the real African climate system and thus is able to reproduce its inter-annual variability, the time-independent statistical transfer functions were then used to translate future climate change signal from the simulated climate predictors into attainable crop yields/crop yield changes. The results confirm that precipitation and air temperature governed agricultural production in Benin in general, and particularly, pineapple yield variations are mainly influenced by temperature. Furthermore, the projected yield changes under future anthropogenic climate change during the first-half of the 21st century amount up to -12.5% for both maize and groundnuts, and -11%, -29%, -33% for pineapple, cassava, and cowpeas respectively. Meanwhile yield gain of up to +10% for sorghum and yams, +24% for cotton, and +39% for rice are expected. Over the time period 2001 – 2050, on average the future yield changes range between -3% and -13% under REMO SRES–B1 (GHG)+LCC, -2% and -11% under REMO SRES–A1B (GHG only),and -3% and -14% under REMO SRES–A1B (GHG)+LCC for pineapple, maize, sorghum, groundnuts, cowpeas and cassava. In the meantime for yams, cotton and rice, the average yield gains lie in interval of about +2% to +7% under REMO SRES–B1 (GHG)+LCC, +0.1% and +12% under REMO SRES–A1B (GHG only), and +3% and +10% under REMO SRES–A1B (GHG)+LCC. For sorghum, although the long-term average future yield depicts a reduction there are tendencies towards increasing yields in the future. The results also reveal that the increases in mean air temperature more than the changes in precipitation patterns are responsible for the projected yield changes. As well the results suggest that the reductions in pineapple yields cannot be attributed to the land cover/land use changes across sub-Saharan Africa. The production of groundnuts and in particular yams and cotton will profit from the on-going land use/land cover changes while the other crops will face detrimental effects.
Henceforth, policymakers should take effective measures to limit the on-going land degradation processes and all other anthropogenic actions responsible for temperature increase. Biotechnological improvement of the cultivated crop varieties towards development of set of seed varieties adapted to hotter and dry conditions should be included in the breeding pipeline programs. Amongst other solutions, application of appropriate climate-smart agricultural practices and conservation agriculture are also required to offset the negative impacts of climate change in agriculture.
High rates of land conversion due to urbanization are causing fragmented and dispersed spatial patterns in the wildland-urban interface (WUI) worldwide. The occurrence of anthropogenic fires in the WUI represents an important environmental and social issue, threatening not only vegetated areas but also periurban inhabitants, as is the case in many Latin American cities. However, research has not focused on the dynamics of the local climate in the WUI. This study analyzes whether wildfires contribute to the increase in land surface temperature (LST) in the WUI of the metropolitan area of the city of Guanajuato (MACG), a semi-arid Mexican city. We estimated the pre- and post-fire LST for 2018–2021. Spatial clusters of high LST were detected using hot spot analysis and examined using ANOVA and Tukey’s post-hoc statistical tests to assess whether LST is related to the spatial distribution of wildfires during our study period. Our results indicate that the areas where the wildfires occurred, and their surroundings, show higher LST. This has negative implications for the local ecosystem and human population, which lacks adequate infrastructure and services to cope with the effects of rising temperatures. This is the first study assessing the increase in LST caused by wildfires in a WUI zone in Mexico.
Thin, pyroclastic marker beds are preserved in argillaceous units of the Dwyka Group in southern Nambia and South Africa which are the earliest witnesses of volcanism in Karoo-equivalent strata of southern Africa. The aim of this study is to present the field appearance of these marker beds, to characterise their mineralogy, geochemistry and heavy mineral contents and to present new radiometric age data from their juvenile zircons. Carboniferous-Permian Karoo deposits in the Aranos Basin of southern Namibia include the glacially dominated, Carboniferous Dwyka Group and the shelf sediments of the overlying Permian Ecca Group. The Dwyka Group can be subdivided into four upward-fining deglaciation sequences, each capped by relatively fine-grained glaciolacustrine or glaciomarine deposits. The uppermost part of the second deglaciation sequence comprises a thick fossiliferous mudstone unit, referred to as the ”Ganigobis Shale Member”. An abundance of marine macro- and ichnofossils as well as extrabasinally derived ashfall tuff beds characterise the more than 40 m thick mudstones and provide the basis for an integrated high-resolution biostratigraphic and tephrostratigraphic framework. The Ganigobis Shale Member contains remains of paleoniscoid fishes, bivalves, gastropods, scyphozoa, crinoid stalks, sponges and sponge spicules, radiolaria, coprolites and permineralised wood. These mostly marine body and trace fossils record the extent of the first of a series of marine incursions into the disintegrating Gondwanan interior as early as the Carboniferous. Within the Ganigobis Shale Member 21 bentonitic tuff beds displaying a thickness of 0.1 and 2.0 cm were determined which in part can be traced laterally over tens of kilometres indicating an ashfall derivation. Further bentonitic tuff beds of the Dwyka Group were detected in cut banks of the Orange River near Zwartbas in the Karasburg Basin (southern Namibia). The 65 tuff beds vary between 0.1 and 4.0 cm in thickness. Due to a similar fossil content and age of the background deposits, the tuff beds are thought to have originated from the same source area as those from the Aranos Basin. Thin-sections reveal the derivation of the tuff beds as distal fallout ashes produced by explosive volcanic eruptions. The matrix consists of a micro- to cryptocrystalline clay mineral-quartz mixture. Rare fragments of splinter quartz, completely recrystallized ash-sized particles of former volcanic glass and few apatite and zircon grains are the only juvenile components. The tuff beds contain as non-opaque, juvenile heavy minerals mostly zircon, apatite, monazite and sphene but also biotite, garnet, hornblende and tourmaline. Geochemical analyses point to an original, intermediate to acid composition of the tuff samples. LREE enrichment and Eu-anomalies show that the parent magma of the tuff beds was a highly evolved calc-alkaline magma. Tectonomagmatic discrimination diagrams point to a volcanic arc setting. Bedding characteristics and the lack of any Carboniferous-Permian volcanic successions onshore Namibia makes an aeolian transport of the ash particles over larger distances likely. Siliceous ashes could thus have been transported by prevailing south-westerly winds from arc-related vents in South America to southern Africa. A second, more local source area could have been located in an intracontinental rift zone along the western margin of southern Africa which is indicated by north-south directed ice-flow directions in the Late Carboniferous. SHRIMP-based age determinations of juvenile magmatic zircons separated from the tuff beds allow a new time calibration of Dwyka Group deglaciation sequences II - IV and the Dwyka/Ecca boundary. Zircons of the Ganigobis Shale Member yield SHRIMP-ages of 302-300 Ma. This dates the uppermost part of the second deglaciation sequence in southern Namibia to the Late Carboniferous (Gzelian) and provides a minimum age for the onset of Karoo-equivalent marine deposition. The age of the uppermost argillaceous part of the third deglaciation sequence (297 Ma) was determined from zircons of a tuffaceous bed sampled in a roadcut in the Western Cape Province, South Africa. The deposits correlate with the Hardap Shale Member in the Aranos Basin of southern Namibia which are part of much more widespread Eurydesma transgression. The age of the Dwyka/Ecca boundary was determined by SHRIMP-measurements of juvenile zircons from two tuff beds of the basal Prince Albert Formation sampled in the Western Cape Province (South Africa). The zircons revealed ages of 289 - 288 Ma which date the Dwyka/Ecca boundary at about 290 Ma. According to these ages, deglaciation sequences II-IV lasted for 5 Ma on average.
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.
Sand ramps have been (and still are) neglected in geomorphological research. Only recently any awareness of their potential of being a major source of palaeoenvironmental information, thanks to their multi-process character, has been developed. In Namibia, sand ramps were terra incognita. This study defines, classifies and systematizes sand ramps, investigates the formative processes and examines their palaeoenvironmental significance. The study region is located between the coastal Namib desert and the Great Escarpment, between the Tiras Mountains to the north and the Aus area to the south. Two lines of work were followed: geomorphological and sedimentological investigations in the field, assisted by interpretation of satellite images, aerial photographs and topographic maps, and palaeopedological and sedimentological analytical work in the laboratory. Two generations of sand ramps could be identified. The older generation, represented by a single sand ramp within the study region, is characterized by the presence of old basal sediments. The bulk of the sand ramps is assigned to the young generation, which is divided into three morpho-types: in windward positions voluminous ramps are found, in leeward positions low-volume ramps exist, either of very high or very low slope angle. The most distinct characteristic of sand ramp sediments is their formation by interacting aeolian deposition and fluvial slope wash. The last period of deposition, which shaped all the entire young sand ramps, but also the upper part of the old ramp, is suggested to have occurred after c. 40 ka BP, implying a highly dynamic climatic system during that time, with seasonal aridity and low-frequency, but high-intensity rainfall. A phase of environmental stability followed, most likely around 25 ka BP, supporting growth of vegetation, stabilization and consolidation of the sediments as well as soil formation. Subsequently, the profile was truncated and a desert pavement formed, under climatic conditions comparable to those of the present semi-desert. The ramps were then largely cut off from the bedrock slopes, implying a change towards higher ecosystem variability. As the final major process, recent and modern aeolian sands accumulated on the upper ramp slopes. A luminescence date for the recent sand places their deposition at about 16 ka BP, close to the Last Glacial Maximum. Regarding the source of the sands, a local origin is proposed. For the sand ramp of the old generation the "basic cycle" of initial deposition, stabilization and denudation occurred twelve times, including a phase of calcrete and/or root-cast formation in each of them, adding up to around 60 changes in morphodynamics altogether. At least nine of these cycles took place between 105 ka BP and the LGM, indicating that the general cooling trend during the Late Pleistocene was subject to a high number of oscillations of the environmental conditions not identified before for southern Namibia. Due to the high resolution obtained by the study of sand ramp sediments, but also due to the very special situation of the study area in a desert margin, 100 km from the South Atlantic and in the transition zone between summer and winter rainfall, correlation with stratigraphies (of mostly lower resolution) established for different regions in southern Africa did not appear promising. In conclusion, sand ramps generally serve as a valuable tool for detailed deciphering of past morphodynamics and thereby palaeoenvironmental conditions. For south-west Namibia, sand ramps shed some more light on the Late Quaternary landscape evolution.
There are ample sand dune and sand sheets in the Texas Rolling Plains, U.S.A. Their varied location, morphology and paleosol content pointed to differnces in their historical develpment throughout the Holocene. Younger dunes, so called fence line dunes have been identified as remnants of unsound agricultural practices which just recently formed at the beginning of this century. Correspondingly soils were eroded, in parts, down to the C-horizon in some of these areas. More mature sand were dated with the radiocarbon method and identified having formed during the Altithermal warming period. This study identifies major eolian anthropogenic and climatic reactivation and stabilisation phases in the Rolling Plains of Texas during the Holocene, but also ties them into the existing Southern High Plains and Great Plains climatic record. This study also researched the reasons for the regional and local sand reactivation phases and contributes to the eolian history in the Great Plains region. The outline of this dissertation is oriented towards a comprehensive regional approach in cultural and physical geography. Chapter 1 covers the physiographic setting of the Rolling Plains region including geology, geomorphology, climate and vegetation. Here the prerequisites for eolian activity in the area are explained, followed by the criteria for the selection of the individual study sites. In chapter 2 selected dune fields and sand sheets are introduced. Chapter 3 outlines the methodology as a combination of field research, laboratory analysis and remote sensing techniques, along with a brief interpretation of their application and success rate. Chapter 4 investigates interactive processes between the cultural development and the physical landscape of the region. The next 4 chapters are focusing on research results and interpretation. Chapter 5 interprets the youngest eolian episodes resulting from the cultural de-velopment of the area, including a description and definition of so called "fenceline dunes" and "shinnery motts". Other dunes with very young buried horizons are also described in this chapter, and a comparison with outcrops in the Nebraska Sand Hills is performed. Chapter 6 interprets short-term, cyclic, drought related sand reactivations several hundred years ago by means of a Post Oak (Quercus stellata) tree ring record as established by STAHLE and CLEAVELAND (1988). In chapter 7 older Holocene reactivation cycles are introduced, investigating the idea of the existence of a warmer period, previously named the Altithermal, which so far has only been identified in the Southern High Plains. The last chapter (8) includes a brief statement of the study’s purpose along with the summary and discussion of results presented. This chapter will end with further implications of this research.
The high-grade metamorphic Epupa Complex (EC) of north-western Namibia constitutes the south-western margin of the Archean to Proterozoic Congo Craton. The north-eastern portion of the EC has been geochemically and petrologically investigated in order to reconstruct its tectono-metamorphic evolution. Two distinct metamorphic units have been recognized, which are separated by ductile shear zones: (1) Upper amphibolite facies rocks (Orue Unit) and (2) ultrahigh-temperature (UHT) granulite facies rocks (Epembe Unit). The rocks of the EC are transsected by a large anorthosite massif, the Kunene Intrusive Complex (KIC). The Orue Unit and the Epembe Unit were affected by two distinct Mesoproterozoic metamorphic events, as is evident from differences in their metamorphic grade, in the P-T paths and in the age of peak-metamorphism: (1) The Orue Unit consists of a Palaeoproterozoic volcano-sedimentary sequence, which was intruded by large masses of I-type granitoids and by rare mafic dykes. During the Mesoproterozoic (1390-1318 Ma) the Orue Unit rocks underwent upper amphibolite facies metamorphism. The volcano-sedimentary sequence is constituted by interlayered basaltic amphibolites and rhyolitic felsic gneisses, with intercalations of migmatitic metagreywackes, migmatitic metapelites, metaarkoses and calc-silicate rocks. The Orue Unit was subdivided into three parts, which record similar heating-cooling paths but represent individual crustal levels: Heating led to the partial replacement of amphibole, biotite and muscovite through dehydration melting reactions. The peak-metamorphic P-T conditions of c. 700°C, 6.5 +/- 1.0 kbar (south-eastern part), c. 820°C, 8 +/- 0.5 kbar (south-western part) and c. 800°C, 6.0 +/- 1.0 kbar (northern part) correlate well with the mineral assemblage in the metapelites, i.e. Grt-Bt-Sil gneisses and schist in the south-eastern and south-western region and (Grt-)Crd-Bt gneisses in the northern part. Peak-metamorphism was followed by retrograde cooling to middle amphibolite facies conditions. Contact metamorphism, related with the intrusion of the anorthosites, is restricted to the direct contact to the KIC and recorded by massive metapelitic Grt-Sil-Crd felses, formed under upper amphibolite facies conditions (c. 750°C, c. 6.5 kbar). (2) The Epembe Unit consists of a Palaeoproterozoic volcano-sedimentary succession, which was intruded by small bodies of S-type granitoids and by andesitic dykes. All these rocks underwent UHT granulite facies metamorphism during the early Mesoproterozoic (1520-1447 Ma). The volcano-sedimentary succession is dominated by interlayered basaltic two-pyroxene granulites and rhyolitic felsic granulites. Migmatitic metapelites and metagreywackes are intercalated in the metavolcanites. Sapphirine-bearing MgAl-rich gneisses occur as restitic schlieren in the migmatitic metagreywackes. Reconstructed anti-clockwise P-T paths are subdivided into several distinct stages: During prograde near-isobaric heating to UHT conditions at c. 7 kbar biotite- or hornblende-bearing mineral assemblages were almost completely replaced by anhydrous mineral assemblages through various dehydration melting reactions. A subsequent pressure increase of 2-3 kbar led to the formation of the peak-metamorphic mineral assemblages Grt-Opx and (Grt-)Opx-Cpx in the orthogneisses and Grt-Opx, Grt-Sil and (Grt-)(Spr-)Opx-Sil-Qtz in the paragneisses. UHT-Metamorphism is proved by conventional geothermobarometry (970 +/- 70°C; 9.5 +/- 2.5 kbar), by the very high Al content of peak-metamorphic orthopyroxene (up to 11.9 wt.% Al2O3) in many paragneisses and by Opx-Sil-Qtz assemblages in the MgAl-rich gneisses. Post-peak decompression is recorded by several corona and symplectite textures, formed at the expense of the peak-metamorphic phases: Initial UHT decompression of about ca. 2 kbar to 940 +/- 60°C at 8 +/- 2 kbar is mainly evident from the formation of sapphirine-bearing symplectites in the Opx-Sil gneisses. Subsequent high-temperature decompression to 6 +/- 2 kbar at 800 +/- 60°C resulted in the formation of Crd-Opx-Spl, Crd-Opx and Spl-Crd symplectites. Subsequent near-isobaric cooling to upper amphibolite conditions of 660 +/- 30°C at 5 +/- 1.5 kbar led to the re-growth of biotite, hornblende, sillimanite and garnet. During continued decompression orthopyroxene and cordierite were formed at the expense of biotite in several paragneisses. In a geodynamic model UHT metamorphism of the Epembe Unit is correlated with the formation of a large magma chamber at the mantle-crust boundary, which forms the source for the anorthosites of the KIC. In contrast, amphibolite facies metamorphism of the Orue Unit is ascribed to a regional contact metamorphic event, caused by the emplacement of the anorthositic crystal mushes in the middle crust.
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 Essential Climate Variable (ECV) Permafrost is currently undergoing strong changes due to rising ground and air temperatures. Surface movement, forming characteristic landforms such as rock glaciers, is one key indicator for mountain permafrost. Monitoring this movement can indicate ongoing changes in permafrost; therefore, rock glacier velocity (RGV) has recently been added as an ECV product. Despite the increased understanding of rock glacier dynamics in recent years, most observations are either limited in terms of the spatial coverage or temporal resolution. According to recent studies, Sentinel-1 (C-band) Differential SAR Interferometry (DInSAR) has potential for monitoring RGVs at high spatial and temporal resolutions. However, the suitability of DInSAR for the detection of heterogeneous small-scale spatial patterns of rock glacier velocities was never at the center of these studies. We address this shortcoming by generating and analyzing Sentinel-1 DInSAR time series over five years to detect small-scale displacement patterns of five high alpine permafrost environments located in the Central European Alps on a weekly basis at a range of a few millimeters. Our approach is based on a semi-automated procedure using open-source programs (SNAP, pyrate) and provides East-West displacement and elevation change with a ground sampling distance of 5 m. Comparison with annual movement derived from orthophotos and unpiloted aerial vehicle (UAV) data shows that DInSAR covers about one third of the total movement, which represents the proportion of the year suited for DInSAR, and shows good spatial agreement (Pearson R: 0.42–0.74, RMSE: 4.7–11.6 cm/a) except for areas with phase unwrapping errors. Moreover, the DInSAR time series unveils spatio-temporal variations and distinct seasonal movement dynamics related to different drivers and processes as well as internal structures. Combining our approach with in situ observations could help to achieve a more holistic understanding of rock glacier dynamics and to assess the future evolution of permafrost under changing climatic conditions.
Availability of water and desiccation of important water reservoirs is a vital challenge in semi-arid to arid climates with growing economy and population. Low quantities of precipitation and high evaporation rates leave the water supply vulnerable to human activity and climatic variations. Endorheic basins of Northern Iran were hydrologically landlocked within geological timescales and thus bear evidence of past variations of water resources in generations of water related landforms, like abandoned lake level shorelines, alluvial fans and stream terraces. Understanding the development of these landforms reveals crucial information about past water reservoirs and landscape history.
This study offers a comprehensive approach on understanding the geomorphological development of the landscape throughout Late Pleistocene and Holocene times. It integrates remote sensing and geographic information system analysis, with geomorphological and stratigraphical mapping fieldwork and detailed sedimentological investigations.
The work shows the importance of analytical geomorphological mapping for delineating stratigraphic units of the Iranian Quaternary. Thus, several phases of drying and lake level retreat were identified in parallel geoarchives and could be dated to a time span from today to Late Pleistocene. The findings link the fate of the citizens of the ancient city of "Tepe Hissar" to their access to water and to the power of geomorphological processes, which started changing their environment.
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.
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.
Current changes of biodiversity result almost exclusively from human activities. This anthropogenic conversion of natural ecosystems during the last decades has led to the so-called ‘biodiversity crisis’, which comprises the loss of species as well as changes in the global distribution patterns of organisms. Species richness is unevenly distributed worldwide. Altogether, 17 so-called ‘megadiverse’ nations cover less than 10% of the earth’s land surface but support nearly 70% of global species richness. Mexico, the study area of this thesis, is one of those countries. However, due to Mexico’s large extent and geographical complexity, it is impossible to conduct reliable and spatially explicit assessments of species distribution ranges based on these collection data and field work alone. In the last two decades, Species distribution models (SDMs) have been established as important tools for extrapolating such in situ observations. SDMs analyze empirical correlations between geo-referenced species occurrence data and environmental variables to obtain spatially explicit surfaces indicating the probability of species occurrence. Remote sensing can provide such variables which describe biophysical land surface characteristics with high effective spatial resolutions. Especially during the last three to five years, the number of studies making use of remote sensing data for modeling species distributions has therefore multiplied. Due to the novelty of this field of research, the published literature consists mostly of selective case studies. A systematic framework for modeling species distributions by means of remote sensing is still missing. This research gap was taken up by this thesis and specific studies were designed which addressed the combination of climate and remote sensing data in SDMs, the suitability of continuous remote sensing variables in comparison with categorical land cover classification data, the criteria for selecting appropriate remote sensing data depending on species characteristics, and the effects of inter-annual variability in remotely sensed time series on the performance of species distribution models. The corresponding novel analyses were conducted with the Maximum Entropy algorithm developed by Phillips et al. (2004). In this thesis, a more comprehensive set of remote sensing predictors than in the existing literature was utilized for species distribution modeling. The products were selected based on their ecological relevance for characterizing species distributions. Two 1 km Terra-MODIS Land 16-day composite standard products including the Enhanced Vegetation Index (EVI), Reflectance Data, and Land Surface Temperature (LST) were assembled into enhanced time series for the time period of 2001 to 2009. These high-dimensional time series data were then transformed into 18 phenological and 35 statistical metrics that were selected based on an extensive literature review. Spatial distributions of twelve tree species were modeled in a hierarchical framework which integrated climate (WorldClim) and MODIS remote sensing data. The species are representative of the major Mexican forest types and cover a variety of ecological traits, such as range size and biotope specificity. Trees were selected because they have a high probability of detection in the field and since mapping vegetation has a long tradition in remote sensing. The result of this thesis showed that the integration of remote sensing data into species distribution models has a significant potential for improving and both spatial detail and accuracy of the model predictions.
Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.
Previous work on Jurassic bivalves from the Iberian Range is reviewed, whereby emphasis is placed on Callovian-Kimmeridgian species. The taxonomy, distribution pattern and ecology of the bivalve fauna occurring in Middle and Upper Jurassic rocks of the Aragonian Branch of the Iberian Range have been analysed. For this purpose 14 sections and 5 additional outcrops, selected according to the abundance of bivalves, were measured in detail and sampled. The rocks studied belong to the Chelva, Yátova, Sot de Chera and Loriguilla formations of Callovian-Kimmeridgian age. The distribution of species of bivalves is given for each section. More than 3000 specimens of bivalves representing 83 species that belong to 46 genera and subgenera of the subclasses Palaeotaxodonta, Pteriomorphia, Isofilibranchia. Palaeoheterodonta, Heterodonta and Anomaldesmata have been used for the taxonomic analysis. One species is new: Plagiostoma fuersichi from the Callovian of the Chelva Fm. The autecology (trophic group and life habit) of each bivalve has been discussed. 49 samples of four sections habe been selected for a quantitative palaeoecological analysis of the bivalve fraction of the benthic fauna. Five bivalve associations and two assemblages are recognised by a Q-mode hierarchical cluster analysis (Ward method). The main environmental factors controlling bivalve associations are thought to be substrate, water energy and distribution of organic matter. The bivalves exhibit a distinct spatial and temporal distribution pattern within the Aragonian Branch. Four of the bivalve associations occur in the Upper Oxfordian (Sot de Chera Fm) and one association in the Lower Callovian (Chelva Fm). In the Sot de Chera and Loriguilla formations, the abundance of bivalves decreases from NW to SE i.e., from relatively close to the shore line towards the distal-most part of the carbonate platform. In the Chelva Fm. bivalves are abundant in the Ariño region, interpreted as a palaeogeographic high. The distribution of bivalves might have been largely controlled by the availability of nutrients.
Accurate crop monitoring in response to climate change at a regional or field scale
plays a significant role in developing agricultural policies, improving food security,
forecasting, and analysing global trade trends. Climate change is expected to
significantly impact agriculture, with shifts in temperature, precipitation patterns, and
extreme weather events negatively affecting crop yields, soil fertility, water availability,
biodiversity, and crop growing conditions. Remote sensing (RS) can provide valuable
information combined with crop growth models (CGMs) for yield assessment by
monitoring crop development, detecting crop changes, and assessing the impact of
climate change on crop yields. This dissertation aims to investigate the potential of RS
data on modelling long-term crop yields of winter wheat (WW) and oil seed rape (OSR)
for the Free State of Bavaria (70,550 km2
), Germany. The first chapter of the dissertation
describes the reasons favouring the importance of accurate crop yield predictions for
achieving sustainability in agriculture. Chapter second explores the accuracy
assessment of the synthetic RS data by fusing NDVIs of two high spatial resolution data
(high pair) (Landsat (30 m, 16-days; L) and Sentinel-2 (10 m, 5–6 days; S), with four low
spatial resolution data (low pair) (MOD13Q1 (250 m, 16-days), MCD43A4 (500 m, one
day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, 8-days)) using the spatial
and temporal adaptive reflectance fusion model (STARFM), which fills regions' cloud
or shadow gaps without losing spatial information. The chapter finds that both L-MOD13Q1 (R2 = 0.62, RMSE = 0.11) and S-MOD13Q1 (R2 = 0.68, RMSE = 0.13) are more
suitable for agricultural monitoring than the other synthetic products fused. Chapter
third explores the ability of the synthetic spatiotemporal datasets (obtained in chapter
2) to accurately map and monitor crop yields of WW and OSR at a regional scale. The
chapter investigates and discusses the optimal spatial (10 m, 30 m, or 250 m), temporal
(8 or 16-day) and CGMs (World Food Studies (WOFOST), and the semi-empiric light
use efficiency approach (LUE)) for accurate crop yield estimations of both crop types.
Chapter third observes that the observations of high temporal resolution (8-day)
products of both S-MOD13Q1 and L-MOD13Q1 play a significant role in accurately
measuring the yield of WW and OSR. The chapter investigates that the simple light use
efficiency (LUE) model (R2 = 0.77 and relative RMSE (RRMSE) = 8.17%) that required fewer input parameters to simulate crop yield is highly accurate, reliable, and more
precise than the complex WOFOST model (R2 = 0.66 and RRMSE = 11.35%) with higher
input parameters. Chapter four researches the relationship of spatiotemporal fusion
modelling using STRAFM on crop yield prediction for WW and OSR using the LUE
model for Bavaria from 2001 to 2019. The chapter states the high positive correlation
coefficient (R) = 0.81 and R = 0.77 between the yearly R2 of synthetic accuracy and
modelled yield accuracy for WW and OSR from 2001 to 2019, respectively. The chapter
analyses the impact of climate variables on crop yield predictions by observing an
increase in R2
(0.79 (WW)/0.86 (OSR)) and a decrease in RMSE (4.51/2.57 dt/ha) when
the climate effect is included in the model. The fifth chapter suggests that the coupling
of the LUE model to the random forest (RF) model can further reduce the relative root
mean square error (RRMSE) from -8% (WW) and -1.6% (OSR) and increase the R2 by
14.3% (for both WW and OSR), compared to results just relying on LUE. The same
chapter concludes that satellite-based crop biomass, solar radiation, and temperature
are the most influential variables in the yield prediction of both crop types. Chapter six
attempts to discuss both pros and cons of RS technology while analysing the impact of
land use diversity on crop-modelled biomass of WW and OSR. The chapter finds that
the modelled biomass of both crops is positively impacted by land use diversity to the
radius of 450 (Shannon Diversity Index ~0.75) and 1050 m (~0.75), respectively. The
chapter also discusses the future implications by stating that including some dependent
factors (such as the management practices used, soil health, pest management, and
pollinators) could improve the relationship of RS-modelled crop yields with
biodiversity. Lastly, chapter seven discusses testing the scope of new sensors such as
unmanned aerial vehicles, hyperspectral sensors, or Sentinel-1 SAR in RS for achieving
accurate crop yield predictions for precision farming. In addition, the chapter highlights
the significance of artificial intelligence (AI) or deep learning (DL) in obtaining higher
crop yield accuracies.
Accurate crop monitoring in response to climate change at a regional or field scale plays a significant role in developing agricultural policies, improving food security, forecasting, and analysing global trade trends. Climate change is expected to significantly impact agriculture, with shifts in temperature, precipitation patterns, and extreme weather events negatively affecting crop yields, soil fertility, water availability, biodiversity, and crop growing conditions. Remote sensing (RS) can provide valuable information combined with crop growth models (CGMs) for yield assessment by monitoring crop development, detecting crop changes, and assessing the impact of climate change on crop yields. This dissertation aims to investigate the potential of RS data on modelling long-term crop yields of winter wheat (WW) and oil seed rape (OSR) for the Free State of Bavaria (70,550 km2), Germany. The first chapter of the dissertation describes the reasons favouring the importance of accurate crop yield predictions for achieving sustainability in agriculture. Chapter second explores the accuracy assessment of the synthetic RS data by fusing NDVIs of two high spatial resolution data (high pair) (Landsat (30 m, 16-days; L) and Sentinel-2 (10 m, 5–6 days; S), with four low spatial resolution data (low pair) (MOD13Q1 (250 m, 16-days), MCD43A4 (500 m, one day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, 8-days)) using the spatial and temporal adaptive reflectance fusion model (STARFM), which fills regions' cloud or shadow gaps without losing spatial information. The chapter finds that both L-MOD13Q1 (R2 = 0.62, RMSE = 0.11) and S-MOD13Q1 (R2 = 0.68, RMSE = 0.13) are more suitable for agricultural monitoring than the other synthetic products fused. Chapter third explores the ability of the synthetic spatiotemporal datasets (obtained in chapter 2) to accurately map and monitor crop yields of WW and OSR at a regional scale. The chapter investigates and discusses the optimal spatial (10 m, 30 m, or 250 m), temporal (8 or 16-day) and CGMs (World Food Studies (WOFOST), and the semi-empiric light use efficiency approach (LUE)) for accurate crop yield estimations of both crop types. Chapter third observes that the observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 play a significant role in accurately measuring the yield of WW and OSR. The chapter investigates that the simple light use efficiency (LUE) model (R2 = 0.77 and relative RMSE (RRMSE) = 8.17%) that required fewer input parameters to simulate crop yield is highly accurate, reliable, and more precise than the complex WOFOST model (R2 = 0.66 and RRMSE = 11.35%) with higher input parameters. Chapter four researches the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for WW and OSR using the LUE model for Bavaria from 2001 to 2019. The chapter states the high positive correlation coefficient (R) = 0.81 and R = 0.77 between the yearly R2 of synthetic accuracy and modelled yield accuracy for WW and OSR from 2001 to 2019, respectively. The chapter analyses the impact of climate variables on crop yield predictions by observing an increase in R2 (0.79 (WW)/0.86 (OSR)) and a decrease in RMSE (4.51/2.57 dt/ha) when the climate effect is included in the model. The fifth chapter suggests that the coupling of the LUE model to the random forest (RF) model can further reduce the relative root mean square error (RRMSE) from -8% (WW) and -1.6% (OSR) and increase the R2 by 14.3% (for both WW and OSR), compared to results just relying on LUE. The same chapter concludes that satellite-based crop biomass, solar radiation, and temperature are the most influential variables in the yield prediction of both crop types. Chapter six attempts to discuss both pros and cons of RS technology while analysing the impact of land use diversity on crop-modelled biomass of WW and OSR. The chapter finds that the modelled biomass of both crops is positively impacted by land use diversity to the radius of 450 (Shannon Diversity Index ~0.75) and 1050 m (~0.75), respectively. The chapter also discusses the future implications by stating that including some dependent factors (such as the management practices used, soil health, pest management, and pollinators) could improve the relationship of RS-modelled crop yields with biodiversity. Lastly, chapter seven discusses testing the scope of new sensors such as unmanned aerial vehicles, hyperspectral sensors, or Sentinel-1 SAR in RS for achieving accurate crop yield predictions for precision farming. In addition, the chapter highlights the significance of artificial intelligence (AI) or deep learning (DL) in obtaining higher crop yield accuracies.
The eminent importance of snow cover for climatic, hydrologic, anthropogenic, and economic reasons has been widely discussed in scientific literature. Up to 50% of the Northern Hemisphere is covered by snow at least temporarily, turning snow to the most prevalent land cover types at all. Depending on regular precipitation and temperatures below freezing point it is obvious that a changing climate effects snow cover characteristics fundamentally. Such changes can have severe impacts on local, national, and even global scale. The region of Central Asia is not an exception from this general rule, but are the consequences accompanying past, present, and possible future changes in snow cover parameters of particular importance. Being characterized by continental climate with hot and dry summers most precipitation accumulates during winter and spring months in the form of snow. The population in this 4,000,000 km² vast area is strongly depending on irrigation to facilitate agriculture. Additionally, electricity is often generated by hydroelectric power stations. A large proportion of the employed water originates from snow melt during spring months, implying that changes in snow cover characteristics will automatically affect both the total amount of obtainable water and the time when this water becomes available. The presented thesis explores the question how the spatial extent of snow covered surface has evolved since the year 1986. This investigation is based on the processing of medium resolution remote sensing data originating from daily MODIS and AVHRR sensors, thus forming a unique approach of snow cover analysis in terms of temporal and spatial resolution. Not only duration but also onset and melt of snow coverage are tracked over time, analyzing for systematic changes within this 26 years lasting time span. AVHRR data are processed from raw Level 1B orbit data to Level 3 thematic snow cover products. Both, AVHRR and MODIS snow maps undergo a further post-processing, producing daily full-area mosaics while completely eliminating inherent cloud cover. Snow cover parameters are derived based on these daily and cloud-free time series, allowing for a detailed analysis of current status and changes. The results confirm the predictions made by coarse resolution predictions from climate models: Central Asian snow cover is changing, posing new challenges for the ecosystem and future water supply. The changes, however, are not aimed at only one direction. Regions with decreasing snow cover exist as well as those where the duration of snow cover increases. A shift towards earlier snow cover start and melt can be observed, posing a serious challenge to water management authorities due to a changed runoff regime.
With accelerating global climate change, the Antarctic Ice Sheet is exposed to increasing ice dynamic change. During 1992 and 2017, Antarctica contributed ~7.6 mm to global sea-level-rise mainly due to ocean thermal forcing along West Antarctica and atmospheric warming along the Antarctic Peninsula (API). Together, these processes caused the progressive retreat of glaciers and ice shelves and weakened their efficient buttressing force causing widespread ice flow accelerations. Holding ~91% of the global ice mass and 57.3 m of sea-level-equivalent, the Antarctic Ice Sheet is by far the largest potential contributor to future sea-level-rise.
Despite the improved understanding of Antarctic ice dynamics, the future of Antarctica remains difficult to predict with its contribution to global sea-level-rise representing the largest uncertainty in current projections. Given that recent studies point towards atmospheric warming and melt intensification to become a dominant driver for future Antarctic ice mass loss, the monitoring of supraglacial lakes and their impacts on ice dynamics is of utmost importance. In this regard, recent progress in Earth Observation provides an abundance of high-resolution optical and Synthetic Aperture Radar (SAR) satellite data at unprecedented spatial and temporal coverage and greatly supports the monitoring of the Antarctic continent where ground-based mapping efforts are difficult to perform. As an automated mapping technique for supraglacial lake extent delineation in optical and SAR satellite imagery as well as a pan-Antarctic inventory of Antarctic supraglacial lakes at high spatial and temporal resolution is entirely missing, this thesis aims to advance the understanding of Antarctic surface hydrology through exploitation of spaceborne remote sensing.
In particular, a detailed literature review on spaceborne remote sensing of Antarctic supraglacial lakes identified several research gaps including the lack of (1) an automated mapping technique for optical or SAR satellite data that is transferable in space and time, (2) high-resolution supraglacial lake extent mappings at intra-annual and inter-annual temporal resolution and (3) large-scale mapping efforts across the entire Antarctic continent. In addition, past method developments were found to be restricted to purely visual, manual or semi-automated mapping techniques hindering their application to multi-temporal satellite imagery at large-scale. In this context, the development of automated mapping techniques was mainly limited by sensor-specific characteristics including the similar appearance of supraglacial lakes and other ice sheet surface features in optical or SAR data, the varying temporal signature of supraglacial lakes throughout the year as well as effects such as speckle noise and wind roughening in SAR data or cloud coverage in optical data. To overcome these limitations, this thesis exploits methods from artificial intelligence and big data processing for development of an automated processing chain for supraglacial lake extent delineation in Sentinel-1 SAR and optical Sentinel-2 satellite imagery. The combination of both sensor types enabled to capture both surface and subsurface lakes as well as to acquire data during cloud cover or wind roughening of lakes. For Sentinel-1, a deep convolutional neural network based on residual U-Net was trained on the basis of 21,200 labeled Sentinel-1 SAR image patches covering 13 Antarctic regions. Similarly, optical Sentinel-2 data were collected over 14 Antarctic regions and used for training of a Random Forest classifier. Optical and SAR classification products were combined through decision-level fusion at bi-weekly temporal scale and unprecedented 10 m spatial resolution. Finally, the method was implemented as part of DLR’s High-Performance Computing infrastructure allowing for an automated processing of large amounts of data including all required pre- and postprocessing steps. The results of an accuracy assessment over independent test scenes highlighted the functionality of the classifiers returning accuracies of 93% and 95% for supraglacial lakes in Sentinel-1 and Sentinel-2 satellite imagery, respectively.
Exploiting the full archive of Sentinel-1 and Sentinel-2, the developed framework for the first time enabled the monitoring of seasonal characteristics of Antarctic supraglacial lakes over six major ice shelves in 2015-2021. In particular, the results for API ice shelves revealed low lake coverage during 2015-2018 and particularly high lake coverage during the 2019-2020 and 2020-2021 melting seasons. On the contrary, East Antarctic ice shelves were characterized by high lake coverage during 2016-2019 and
extremely low lake coverage during the 2020-2021 melting season. Over all six investigated ice shelves, the development of drainage systems was revealed highlighting an increased risk for ice shelf instability. Through statistical correlation analysis with climate data at varying time lags as well as annual data on Southern Hemisphere atmospheric modes, environmental drivers for meltwater ponding were revealed. In addition, the influence of the local glaciological setting was investigated through computation of annual recurrence times of lakes. Over both ice sheet regions, the complex interplay between local, regional and large-scale environmental drivers was found to control supraglacial lake formation despite local to regional discrepancies, as revealed through pixel-based correlation analysis. Local control factors included the ice surface topography, the ice shelf geometry, the presence of low-albedo features as well as a reduced firn air content and were found to exert strong control on lake distribution. On the other hand, regional controls on lake evolution were revealed to be the amount of incoming solar radiation, air temperature and wind occurrence. While foehn winds were found to dictate lake evolution over the API, katabatic winds influenced lake ponding in East Antarctica. Furthermore, the regional near-surface climate was shown to be driven by large-scale atmospheric modes and teleconnections with the tropics. Overall, the results highlight that similar driving factors control supraglacial lake formation on the API and EAIS pointing towards their transferability to other Antarctic regions.
Supraglacial lakes can have considerable impact on ice sheet mass balance and global sea-level-rise through ice shelf fracturing and subsequent glacier speedup. In Antarctica, the distribution and temporal development of supraglacial lakes as well as their potential contribution to increased ice mass loss remains largely unknown, requiring a detailed mapping of the Antarctic surface hydrological network. In this study, we employ a Machine Learning algorithm trained on Sentinel-2 and auxiliary TanDEM-X topographic data for automated mapping of Antarctic supraglacial lakes. To ensure the spatio-temporal transferability of our method, a Random Forest was trained on 14 training regions and applied over eight spatially independent test regions distributed across the whole Antarctic continent. In addition, we employed our workflow for large-scale application over Amery Ice Shelf where we calculated interannual supraglacial lake dynamics between 2017 and 2020 at full ice shelf coverage. To validate our supraglacial lake detection algorithm, we randomly created point samples over our classification results and compared them to Sentinel-2 imagery. The point comparisons were evaluated using a confusion matrix for calculation of selected accuracy metrics. Our analysis revealed wide-spread supraglacial lake occurrence in all three Antarctic regions. For the first time, we identified supraglacial meltwater features on Abbott, Hull and Cosgrove Ice Shelves in West Antarctica as well as for the entire Amery Ice Shelf for years 2017–2020. Over Amery Ice Shelf, maximum lake extent varied strongly between the years with the 2019 melt season characterized by the largest areal coverage of supraglacial lakes (~763 km\(^2\)). The accuracy assessment over the test regions revealed an average Kappa coefficient of 0.86 where the largest value of Kappa reached 0.98 over George VI Ice Shelf. Future developments will involve the generation of circum-Antarctic supraglacial lake mapping products as well as their use for further methodological developments using Sentinel-1 SAR data in order to characterize intraannual supraglacial meltwater dynamics also during polar night and independent of meteorological conditions. In summary, the implementation of the Random Forest classifier enabled the development of the first automated mapping method applied to Sentinel-2 data distributed across all three Antarctic regions.
Supraglacial meltwater accumulation on ice sheets can be a main driver for accelerated ice discharge, mass loss, and global sea-level-rise. With further increasing surface air temperatures, meltwater-induced hydrofracturing, basal sliding, or surface thinning will cumulate and most likely trigger unprecedented ice mass loss on the Greenland and Antarctic ice sheets. While the Greenland surface hydrological network as well as its impacts on ice dynamics and mass balance has been studied in much detail, Antarctic supraglacial lakes remain understudied with a circum-Antarctic record of their spatio-temporal development entirely lacking. This study provides the first automated supraglacial lake extent mapping method using Sentinel-1 synthetic aperture radar (SAR) imagery over Antarctica and complements the developed optical Sentinel-2 supraglacial lake detection algorithm presented in our companion paper. In detail, we propose the use of a modified U-Net for semantic segmentation of supraglacial lakes in single-polarized Sentinel-1 imagery. The convolutional neural network (CNN) is implemented with residual connections for optimized performance as well as an Atrous Spatial Pyramid Pooling (ASPP) module for multiscale feature extraction. The algorithm is trained on 21,200 Sentinel-1 image patches and evaluated in ten spatially or temporally independent test acquisitions. In addition, George VI Ice Shelf is analyzed for intra-annual lake dynamics throughout austral summer 2019/2020 and a decision-level fused Sentinel-1 and Sentinel-2 maximum lake extent mapping product is presented for January 2020 revealing a more complete supraglacial lake coverage (~770 km\(^2\)) than the individual single-sensor products. Classification results confirm the reliability of the proposed workflow with an average Kappa coefficient of 0.925 and a F\(_1\)-score of 93.0% for the supraglacial water class across all test regions. Furthermore, the algorithm is applied in an additional test region covering supraglacial lakes on the Greenland ice sheet which further highlights the potential for spatio-temporal transferability. Future work involves the integration of more training data as well as intra-annual analyses of supraglacial lake occurrence across the whole continent and with focus on supraglacial lake development throughout a summer melt season and into Antarctic winter.
The Bafoussam area in west Cameroon is located within the Cameroon Neoproterozoic orogenic belt (north of the Congo craton) which is part of the Central African Fold Belt (CAFB).The evolution of the CAFB is related to the collision between the convergent West African craton, the São Francisco – Congo cratons and the Sahara Metacraton. The outcrop area stretches over a surface of ~1000 km2 and dominantly consists of granitoids which intruded wall-rocks of gneiss and migmatite during the Pan-African orogeny. The Bafoussam granitoid emplacement was influenced by the N 30 °E strike-slip shear zone in the prolongation of the Cameroon Volcanic Line, but also by the N 70 °E Central Cameroon Shear Zone. In the field, these two shear directions are expressed in the schistosity and foliation trajectories, fault orientation and the alignment of the volcanic cones as well. In the Bafoussam area, four types of granitoids can be distinguished, including: (i) the biotite granitoid, (ii) the deformed biotite granitoid, (iii) the mega feldspar granitoid, and (iv) the two-mica granitoid. These granitoids occur as elongated plutons hosting irregular mafic enclaves (amphibole-bearing, biotite-rich, and metagabbroic types) and are frequently cut by late pegmatites, aplite dykes and quartz veins. Petrographically, they range in composition from syenogranite (major), alkali-feldspar granite, granodiorite, monzogranite, quartz-syenite, quartzmonzonite to quartz-monzodiorite. Potassium feldspar, quartz, plagioclase and biotite are the principal phases, in cases accompanied by amphibole and accessory minerals such as apatite,zircon, monazite, titanite, allanite, ilmenite and magnetite. Sericite, epidote and chlorite are secondary minerals. In addition, the two-mica granitoid contains primary muscovite and sometimes igneous garnet. In the granitoids, potassium feldspar is orthoclase (microcline and orthoclase: Or81–97Ab19–3), and plagioclase is mainly oligoclase with some albite and andesine (An3–35Ab96–64).Biotite is Fe-rich (meroxene and lepidomelane, with some siderophyllite), having high Fe2+/(Fe2+ + Mg) ratios of 0.40–0.80. It is a re-equilibrated primary biotite and suggests calc-alkaline and peraluminous nature of the host granitoids. Amphibole is edenitic and magnesian hastingsitic hornblende, with high Mg/(Mg + Fe2+) ratios of 0.50–0.62. The evolution of the hornblende was dominated by the edenitic, tschermakitic, pargasitic and hastingsitic substitution types. Primary muscovite is iron-rich [Fe2+/(Fe2+ + Mg) = 0.52–0.82] and has experienced celadonite and paragonite substitutions. Igneous garnet is almandine–spessartine (XFe = 0.99 and XMn = 0.46–0.56). The euhedral grain shapes of garnet crystals and the absence of inclusions coupled with the high Mn and Fe2+contents (2.609–3.317 a.p.f.u and 2.646–3.277 a.p.f.u,respectively) and low Mg contents (0.012–0.038 a.p.f.u) clearly point to its plutonic origin. The Mn-depletion crystallization model is suggested for the origin of the analyzed garnet, i.e. initial crystallization of garnet inducing early decrease of Mn in the original melt. Aluminum-in-hornblende and phengite barometric estimates show that the granitoids crystallized at 4.2 ± 1.1 to 6.6 ± 1.0 kbar, corresponding to emplacement depths of 15–24 km.Zircon and apatite saturation temperature calibrations and hornblende–plagioclase thermometry yielded emplacement temperatures between 772 ± 41 and 808 ± 34 °C. Except the two-mica granitoid, the titanite–magnetite–quartz assemblage gives oxygen fugacities ranging from 10–17 to 10–13, suggesting that the granitoids were produced by an oxidized magma. Since the twomica granitoid lacks magnetite, it was originated from a magma under reducing conditions, below the quartz–fayalite–magnetite buffer. Fluid inclusions in quartz from hydrothermal veins are secondary in nature and are found in trails along healed microcracks or in clusters. Two types of fluid inclusion have been recognized, mixed aqueous–non-aqueous volatile fluid inclusions subdivided into aqueous-rich mixed and non-aqueous volatile-rich mixed fluid inclusions, and pure aqueous fluid inclusions.The non-aqueous volatile-rich mixed fluid inclusions are one-, two-, or three-phase inclusions, whereas the aqueous-rich mixed fluid inclusions are exclusively three-phase inclusions. Both have similar low to moderate salinities (1 to 10 equiv. wt. %). The total homogenization temperatures of the aqueous-rich mixed fluid inclusions are slightly lower than those of the nonaqueous volatile-rich mixed fluid inclusions, ranging from 150 to 250 °C and 170 to 300 °C,respectively. They contain nearly pure CO2, or CO2 with addition of 4.1–13.5 mole % CH4 as volatile constituents. Pure aqueous fluid inclusions are two-phase with lower total homogenization temperatures (130–150 °C) and salinities ranging from 3 to 8 equiv. wt. %. They display mixing salt system characteristics, having NaCl as the dominant salt and considerable amounts of other divalent cations. Aqueous-rich mixed fluid inclusions and pure aqueous fluid inclusions exhibit a low geothermal gradient value of 18 °C/km, whereas the non-aqueous volatiles-rich mixed fluid inclusions have a high density which correspond to high geothermal gradient of 68 °C/km. The studied granitoids are intermediate to felsic in compositions (56.9–74.6 wt. % SiO2)and have high contents of alkalis K2O (1.73–7.32 wt. %) and Na2O (1.25–5.13 wt. %) but low abundances in MnO (0.01–0.20 wt. %), MgO (0.10–3.97 wt. %), CaO (0.37–4.85 wt. %), P2O5(up to 0.90 wt. %). They display variable contents in TiO2 (0.07–0.91 wt. %), Fe2O3* (total Fe = 0.96–7.79 wt. %) and Al2O3 (12.0–17.6 wt. %) contents. The granitoids show a wide range of high-field-strength elements (HFSE) and large ion lithophile elements (LILE) contents, with felsic granitoids being enriched in HFSE and the intermediate granitoids displaying in contrast high LILE concentrations. They exhibit chemical characteristics of non-alkaline to mid-alkaline, alkali-calcic, calc-alkaline, K-rich to shoshonitic, ferriferous affinities. Chondrite-normalized rare earth element (REE) patterns are characterized by a strong enrichment in light compared to heavy REEs [(La/Sm)N = 3.23–9.65 and (Ga/Lu)N = 1.45–5.54, respectively], with small to significant negative Eu anomalies (Eu/Eu* = 0.28–1.08). Ocean ridge granites (ORG)normalized multi-elements spidergrams display typical collision-related granites pattern, with characteristic negative anomalies of Ba, Nb and Y, and positive anomalies in Rb, Th and Sm. The granitoids under study are genetically I-type granitoids (biotite granitoid, deformed biotite granitoid and mega feldspar granitoid) and one S-type granitoid (two-mica granitoid). The I-type granitoids are metaluminous (ASI: 0.70–1.00) or moderately peraluminous if highly fractionated (ASI: 1.01–1.06). The geochemistry and petrological features of these I-type granitoids argue for close genetic relationships and it is suggest that they originated from a single parent magma. The observed variability in mineralogy and major and trace element compositions in these granitoids are then the reflection of the fractional crystallization that evolved separation of plagioclase, biotite, K-feldspar and accessory minerals at the level of emplacement. The two mica S-type granitoid is exclusively peraluminous (ASI: 1.07–1.25) and classified as a peraluminous leucocratic granitoid or leucogranite. It is marked in its CIPW normative composition by the permanent presence of corundum, ranging between 0.12 and 3.03. The Bafoussam granitoids were emplaced in a syn- to post-collisional tectonic environment. The observed deformational features and the concentrations in Y, less than 40 ppm, confirm that they are related to an orogenesis. Whole-rock Rb–Sr isochrons defines an igneous crystallization ages of 540 ± 27 Ma for the biotite granitoid and 587 ± 41 Ma for the mega feldspar granitoid. These ages fit with the range of Pan-African granitoid ages (650–530 Ma) in West Cameroon and correspond to the Pan-African D2 deformation event in the Neoproterozoic Cameroon orogenic belt. The two-mica granitoid yields an older Rb–Sr isochron age of 663 ± 62 Ma which is considered to be probably a mixing age. The Nd–Sr isotopic compositions indicate that the I-type granitoids have been produced by partial melting of a tonalite–granodiorite source in the lower crust. This is supported by their initial 87Sr/86Sr(600 Ma) ratios (0.705–0.709) and by their WNd(600 Ma) values (0.2 to –6.3, mainly < 0). The two-mica granitoid was generated by partial melting of a greywacke-dominated source involving biotite-limited, biotite dehydration melting. Chemical data of the two-mica granitoid that support this hypothesis are low CaO/Na2O (0.11–0.38) and Sr/Ba (0.20–0.30), the high Rb/Sr (2.26–7.00), the high initial 87Sr/86Sr(600 Ma) ratios ranging from 0.708 to 0.720, the large range in Al2O3/TiO2 (47–204) and the negative WNd(600 Ma) values (–9.9 to –14.0). Moreover,the higher initial 87Sr/86Sr(600 Ma) ratios of the two-mica granitoid are consistent with an upper crust origin. The depleted mantle Nd model ages (TDM) of 1.3–2.3 Ga indicate that the studied granitoids originated by partial melting of Paleoproterozoic and Mesoproterozoic crust, with limited mantle-derived magma contribution. The high initial 87Sr/86Sr(600 Ma) ratios of these granitoids coupled with the wide negative WNd(600 Ma) values strongly suggest a very long residence time in the crust of their protoliths before the melting event. The petrologic signatures of the Bafoussam granitoids are similar to those described in other Pan-African belts of western Gondwanaland such as the neighbouring provinces of Nigeria and the Central African Republic, as well as in the Borborema Province of northeastern Brazil. This supports the previous hypothesis that the Central African fold Belt including Cameroon, Nigeria and the Central African Republic provinces has a continuation in Brazil.
The surface urban heat island (SUHI) affects the quality of urban life. Because varying urban structures have varying impacts on SUHI, it is crucial to understand the impact of land use/land cover characteristics for improving the quality of life in cities and urban health. Satellite-based data on land surface temperatures (LST) and derived land use/cover pattern (LUCP) indicators provide an efficient opportunity to derive the required data at a large scale. This study explores the seasonal and diurnal variation of spatial associations from LUCP and LST employing Pearson correlation and ordinary least squares regression analysis. Specifically, Landsat-8 images were utilized to derive LSTs in four seasons, taking Berlin as a case study. The results indicate that: (1) in terms of land cover, hot spots are mainly distributed over transportation, commercial and industrial land in the daytime, while wetlands were identified as hot spots during nighttime; (2) from the land composition indicators, the normalized difference built-up index (NDBI) showed the strongest influence in summer, while the normalized difference vegetation index (NDVI) exhibited the biggest impact in winter; (3) from urban morphological parameters, the building density showed an especially significant positive association with LST and the strongest effect during daytime.
During the Mesoproterozoic large volumes of magma were repeatedly emplaced within the basement of NW Namibia. Magmatic activity started with the intrusion of the anorthositic rocks of the Kunene Intrusive Complex (KIC) at 1,385-1,347 Ma. At its south-eastern margin the KIC was invaded by syenite dykes (1,380-1,340 Ma) and younger carbonatites (1,140-1,120 Ma) along ENE and SE trending faults. Older ferrocarbonatite intrusions, the ‘carbonatitic breccia’, frequently contain wallrock fragments, whereas subordinate ferrocarbonatite veins are almost xenolith-free. Metasomatic interaction between carbonatite-derived fluids and the neighbouring and incorporated anorthosites led to the formation of economically important sodalite deposits. Investigated anorthosite samples display the magmatic mineral assemblage of Pl (An37-75) ± Ol ± Opx ± Cpx + Ilm + Mag + Ap ± Zrn. Ilmenite and pyroxene are surrounded by narrow reaction rims of biotite and pargasite. During the subsolidus stage sporadic coronitic garnet-orthopyroxene-quartz assemblages were produced. Thermobarometry studies on amphiboles yield temperatures of 985-950°C whereas the chemical composition of coronitic garnet and orthopyroxene indicate a subsolidus re-equilibration of the KIC at conditions of 760 ± 100°C and 7.3 ± 1 kbar. In the syenites Kfs, Pl, Hbl and/or Cpx crystallized first, followed by a second generation of Kfs, Hbl, Fe-Ti oxides and Ttn. Crystallization of potassium feldspar occurred under temperatures of 890-790°C. For the crystallization of hastingsite pressures of 6.5 ± 0.6 kbar are obtained. In order to constrain the source rocks of the two suites, oxygen isotope analyses of feldspar as well as geochemical bulk rock analyses were carried out. In case of the anorthosites, the general geochemical characteristics are in excellent agreement with their derivation from fractionated basaltic liquids, with the d18O values (5.88 ± 0.19 ‰) proving their derivation from mantle-derived magmas. The results obtained for the felsic suite, provide evidence against consanguinity of the anorthosites and the syenites, i.e. (1) compositional gaps between the geochemical data of the two suites, (2) trace element data of the felsic suite points to a mixed crustal-mantle source, (3) syenites do not exhibit ubiquitous negative Eu-anomalies in their REE patterns, which would be expected from fractionation products of melts that previously formed plagioclase cumulates and (4) feldspar d18O values from the syenites fall in a range of 7.20-7.92 ‰, which, however, is about 1.6 ‰ higher than the average d18O of the anorthosites. Conformably, the crustal-derived felsic and the mantle-derived anorthositic suite are suggested to be coeval but not consanguineous. Their spatial and temporal association can be accounted for, if the heat necessary for crustal melting is provided by the upwelling and emplacement of mantle-derived melts, parental to the anorthosites. In order to constrain the source of the 1,140-1,120 Ma carbonatites and to elucidate the fenitizing processes, which led to the formation of the sodalite, detailed mineralogical and geochemical investigations, stable isotope (C,O,S) analyses and fluid inclusion measurements (microthermometrical studies and synchrotron-micro-XRF analyses) have been combined. There is striking evidence that carbonatites of both generations are magmatic in origin. They occur as dykes with cross-cutting relationships and margins disturbed by fenitic aureoles, and contain abundant flow-oriented xenoliths. The mineral assemblage of both carbonatite generations of Ank + Cal + Ilm + Mag + Bt ± Ap ± pyrochlore ± sulphides in the main carbonatite body and Ank + Cal + Mag ± pyrochlore ± rutile in the ferrocarbonatite veins, their geochemical characteristics and the O and C isotope values of ankerite (8.91 to 9.73 and –6.73 to –6.98, respectively) again indicate igneous derivation, with the 18O values suggesting minor subsolidus alteration. NaCl-rich fluids, released from the carbonatite melt mainly caused the fenitization of both, the incorporated and the bordering anorthosite. This process is characterized by the progressive transformation of Ca-rich plagioclase into albite and sodalite. Applying conventional geothermobarometry combined with fluid-inclusion isochore data, it was possible to reconstruct the P-T conditions for the carbonatite emplacement and crystallization (1200-630°C, 4-5 kbar) and for several mineral-forming processes during metasomatism (e.g. formation of sodalite: 800-530°C). The composition and evolutionary trends of the fenitizing solution were estimated from both the sequence of metasomatic reactions within wallrock xenoliths in the carbonatitic breccia and fluid inclusion data. The fenitizing solutions responsible for the transformation of albite into sodalite can be characterised as of NaCl-rich aqueous brines (19-30 wt.% NaCl eq.), that contained only minor amounts of Sr, Ba, Fe, Nb, and LREE.
A completely revised and enhanced version of the water balance model MODBIL of the regional water balance dynamics of Cyprus was developed for this study. The model is based on a physical, process-oriented, spatially distributed concept and is applied for the calculation of all important water balance components of the island for the time period of 1961-2004. The calibrated results are statistically analysed and visualised for the whole island area, and evaluated with respect to the renewability of natural water resources. Climate variability and changes of the past decades are analysed with regard to their influence on water balances. A further part of the study focusses on the simulation of impacts of potential climate change. The water balances are simulated under changing climatic conditions on the base of theoretical precipitation, temperature and relative humidity changes and the revealed impacts on the water balances and renewable resources are discussed. Furthermore, a first principal water balance scenario is developed for the assessment of the regional hydrological changes expected for Cyprus by the end of the 21st century. The scenarios are based on recently calculated climate change assessments for this part of the Mediterranean, under an assumed further increase of greenhouse gasses in the atmosphere.
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.
Periglacial environments are facing dramatic changes. Warming air temperatures and strong snow cover variations fundamentally affect landforming processes in this hotspot region of Climate Change. But before we can assess the response of landform development to a changing climate, we need to enhance our understanding of the internal structure of those landforms. Within this study, a broad scope of landform types from alpine and subarctic regions is investigated: rock glaciers, solifluction lobes, palsas and patterned ground. By using the geophysical methods 2-D and 3-D ERI, as well as GPR surveying, structural differences and similarities between landform units of different or the same landform types are highlighted. This enables a reconstruction of their past and a projection of their future development.
The natural cyclical development of palsas makes it difficult to use visible signs of decay as reference points for environmental change. Thus, to determine the actual development stage of a palsa, investigations of the internal structure are crucial. Our study presents 2‐D and 3‐D electrical resistivity imaging (ERI) and 2‐D ground‐penetrating radar (GPR) results, measurements of surface and subsurface temperatures, and of the soil matric potential from Orravatnsrústir Palsa Site in Central Iceland. By a joint interpretation of the results, we deduce the internal structure (i.e., thickness of thaw zone and permafrost, ice/water content) of five palsas of different size and shape. The results differentiate between initial and mature development stages and show that palsas of different development stages can exist in close proximity. While internal characteristics indicate undisturbed development of four palsas, one palsa shows indications of environmental change. Our study shows the value of the multimethod geophysical approach and introduces measurements of the soil matric potential as a promising method to assess the current state of the subsurface.
Wetlands are one of the most important ecosystems due to their critical services to both humans and the environment. Therefore, wetland mapping and monitoring are essential for their conservation. In this regard, remote sensing offers efficient solutions due to the availability of cost-efficient archived images over different spatial scales. However, a lack of sufficient consistent training samples at different times is a significant limitation of multi-temporal wetland monitoring. In this study, a new training sample migration method was developed to identify unchanged training samples to be used in wetland classification and change analyses over the International Shadegan Wetland (ISW) areas of southwestern Iran. To this end, we first produced the wetland map of a reference year (2020), for which we had training samples, by combining Sentinel-1 and Sentinel-2 images and the Random Forest (RF) classifier in Google Earth Engine (GEE). The Overall Accuracy (OA) and Kappa coefficient (KC) of this reference map were 97.93% and 0.97, respectively. Then, an automatic change detection method was developed to migrate unchanged training samples from the reference year to the target years of 2018, 2019, and 2021. Within the proposed method, three indices of the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and the mean Standard Deviation (SD) of the spectral bands, along with two similarity measures of the Euclidean Distance (ED) and Spectral Angle Distance (SAD), were computed for each pair of reference–target years. The optimum threshold for unchanged samples was also derived using a histogram thresholding approach, which led to selecting the samples that were most likely unchanged based on the highest OA and KC for classifying the test dataset. The proposed migration sample method resulted in high OAs of 95.89%, 96.83%, and 97.06% and KCs of 0.95, 0.96, and 0.96 for the target years of 2018, 2019, and 2021, respectively. Finally, the migrated samples were used to generate the wetland map for the target years. Overall, our proposed method showed high potential for wetland mapping and monitoring when no training samples existed for a target year.
Despite the widespread application of landslide susceptibility analyses, there is hardly any information about whether or not the occurrence of recent landslide events was correctly predicted by the relevant susceptibility maps. Hence, the objective of this study is to evaluate four landslide susceptibility maps retrospectively in a landslide-prone area of the Swabian Alb (Germany). The predictive performance of each susceptibility map is evaluated based on a landslide event triggered by heavy rainfalls in the year 2013. The retrospective evaluation revealed significant variations in the predictive accuracy of the analyzed studies. Both completely erroneous as well as very precise predictions were observed. These differences are less attributed to the applied statistical method and more to the quality and comprehensiveness of the used input data. Furthermore, a literature review of 50 peer-reviewed articles showed that most landslide susceptibility analyses achieve very high validation scores. 73% of the analyzed studies achieved an area under curve (AUC) value of at least 80%. These high validation scores, however, do not reflect the high uncertainty in statistical susceptibility analysis. Thus, the quality assessment of landslide susceptibility maps should not only comprise an index-based, quantitative validation, but also an additional qualitative plausibility check considering local geomorphological characteristics and local landslide mechanisms. Finally, the proposed retrospective evaluation approach cannot only help to assess the quality of susceptibility maps and demonstrate the reliability of such statistical methods, but also identify issues that will enable the susceptibility maps to be improved in the future.
Illegal small-scale mining (galamsey) in South-Western Ghana has grown tremendously in the last decade and caused significant environmental degradation. Excessive cloud cover in the area has limited the use of optical remote sensing data to map and monitor the extent of these activities. This study investigated the use of annual time-series Sentinel-1 data to map and monitor illegal mining activities along major rivers in South-Western Ghana between 2015 and 2019. A change detection approach, based on three time-series features — minimum, mean, maximum — was used to compute a backscatter threshold value suitable to identify/detect mining-induced land cover changes in the study area. Compared to the mean and maximum, the minimum time-series feature (in both VH and VV polarization) was found to be more sensitive to changes in backscattering within the period of investigation. Our approach permitted the detection of new illegal mining areas on an annual basis. A backscatter threshold value of +1.65 dB was found suitable for detecting illegal mining activities in the study area. Application of this threshold revealed illegal mining area extents of 102 km\(^2\), 60 km\(^2\) and 33 km\(^2\) for periods 2015/2016–2016/2017, 2016/2017–2017/2018 and 2017/2018–2018/2019, respectively. The observed decreasing trend in new illegal mining areas suggests that efforts at stopping illegal mining yielded positive results in the period investigated. Despite the advantages of Synthetic Aperture Radar data in monitoring phenomena in cloud-prone areas, our analysis revealed that about 25% of the Sentinel-1 data, mostly acquired in March and October (beginning and end of rainy season respectively), were unusable due to atmospheric effects from high intensity rainfall events. Further investigation in other geographies and climatic regions is needed to ascertain the susceptibility of Sentinel-1 data to atmospheric conditions.
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.
For many active volcanoes all over the world a civil protection program, normally combined with hazard maps, exists. Optimising of hazard maps and the associated hazard assessment implies a detailed knowledge of the volcanostratigraphy, because the deposits provoke information on the potential behaviour during a new activity cycle. Pyroclastic deposits, however, may vary widely in thickness and distribution over very short lateral distances. High resolution characterisation of single strata often cannot be archived, if solely sedimentological and geochemical methods are used. Gamma-ray measurements taken in the field combined with grain-size depended magnetic susceptibility measurements made in the laboratory are used in this work to optimise the resolution of volcanostratigraphic investigations. The island of Vulcano is part of the Aeolian Archipelago sited of the northern coast of Sicily. La Fossa cone is the active centre of Vulcano, where fumarolic and seismic activity can be observed. The cone was built up during the last 6,000 years, whereby the last eruption period is dated to historic times (1888-1890). For the tuff cone La Fossa the most likely volcanic hazards are the emplacement of pyroclastic deposits as well as gas hazards (especially SOx and CO2), due to this the detailed knowledge of the stratigraphy is mandatory. Most of the population resides in Vulcano Porto and the nearby sited peninsula of Vulcanello, which are highly endangered locations for a future eruption scenario. Measurements, made in standard outcrops, allow a characterisation of the successions Punte Nere, Tufi Varicolori, Palizzi, Commenda, and Cratere Attuale. A discrimination of all successions by solely one of the methods is rarely possible. In some cases, however, the combination of the methods leads to clear results. It can also be noticed that the exposition as well as the sedimentation type (wet-surge or dry-surge deposits) affect the measurements. In general it can be assumed that the higher the magma is evolved the higher the g -ray values and the lower the susceptibility values. Measurements from the Wingertsberg (Laacher See deposits, Eifel, W-Germany) show clearly that a higher degree of magma evolution correlates with lower susceptibility and higher gamma-ray values. Variations of the values can be observed not only by the change of the degree of magmatic evolution but also by the inhomogeneous deposition conditions. Particularly the gamma-ray measurements show lower values for the wet-surge deposits than for the dry-surge deposits, even though the erupted material has the same geochemical composition. This can be explained especially by reactions inside of the moist eruption cloud and short-time after deposition, when easily soluble elements like K, U, and Th can be leached by these aggressive fluids. Even extended exposition and high water content can provoke depletion of various elements within the complete or parts of the outcrop, too. If the deposits are affected by a fumarolic activity especially the susceptibility values show significant variations, whereas in general extreme low values are observed. Contamination of deposits also can occur, if they are overlain by weathered deposits of higher concentration of K, U, and Th. Weathering and mobilisation within the upper deposits can generate an element enrichment within the lower deposits. In general the element ratios of the barried underlying deposits are less affected than the exposed ones. After gauging the values of the well defined succession for standard outcrops undefined outcrops were measured. These outcrops are not clearly classified by sedimentological and geochemical methods, thus a correlation with the combined geophysical methods is useful. In general the combination of the methods allows a correlation, although in some cases more than one interpretation is possible. But in connection with time marker horizons as well as sedimentological features an interpretation is feasible. These situations show that a classification solely based on geophysical methods is possible for many cases but, if the volcanic system is more complex, a combination with sedimentological and geochemical methods may be needed. The investigations on Vulcano, documented in this work, recommend a re-interpretation of the dispersial of some successions of La Fossa cone, especially the presumption that Tufi Varicolori only exist inside of the Caldera of La Fossa. As a consequence the eruption and energy model especially for Tufi Varicolori have to be reviewed.
At Zwartbas, about 10 km west of Vioolsdrif, southern Namibia, the Dwyka succession is composed of tillites and distal fossiliferous dropstone-bearing glacio-marine shales. The completely exposed Dwyka succession is interbedded with thin bentonites, altered distal pyroclastic deposits, which were derived from the magmatic arc at the southern rim of Gondwana. Dropstone-bearing and dropstonefree sequences intercalate with four diamictites, of which the two lowest were certainly recognised as tillites. Four events of deglaciation were proven at Zwartbas and thus consist with correlative deposits in southern Africa. Numerous fossilised fishes, trace fossils, and plant fragments appear frequently within the lower half of the Dwyka succession whereas trace fossils were principally found in the complete succession. Although the environmental determination is quite problematic, the fossil assemblage rather implies proximal, shallow water conditions with temporary restricted oxygenation. The hinterland was covered with considerable vegetation, which points to a moderate climate. Water salinity determinations based on shale geochemistry rectify contrary palaeontological results and point to rather brackish or non-marine conditions in comparison to present-day salinites. Geochemical analyses of the bentonites relate the pyroclastic deposits with acid to intermediate source magmas, as they are known from the magmatic arc in present-day Patagonia. Tectono-magmatic comparisons furthermore emphasise a syn-collision or volcanic-arc situation of the magma source. However, significant cyclicity in the production of the pyroclastic deposits was not observed. Radiometric age determinations of two tuff beds clearly date the onset of glacial activity into the Late Carboniferous.
The locality of Zwartbas is situated at the border of Namibia and South Africa about 15 km west of Noordoewer. The mapped area is confined by the Tandjieskoppe Mountains in the north and the Orange River in the south. Outcropping rocks are predominantly sediments of the Nama Group and of the Karoo Supergroup. During the compilation of this paper doubts arose about the correct classification of the Nama rocks as it is found in literature. Since no certain clues were found to revise the classification of the Nama rocks, the original classification remains still valid. Thus the Kuibis and Schwarzrand Subgroup constitute the Nama succession and date it to Vendian age. A glacial unconformity represents a hiatus for about 260 Ma. This is covered by sediments of the Karoo Supergroup. Late Carboniferous and early Permian glacial deposits of diamictitic shale of the Dwyka and shales of the Ecca Group overlie the unconformity. The shales of the Dwyka Group contain fossiliferous units and volcanic ash-layers. A sill of the Jurassic Tandjiesberg Dolerite Complex (also Karoo Supergroup) intruded rocks at the Dwyka-Ecca-boundary. Finally fluvial and aeolian deposits and calcretes of the Cretaceous to Tertiary Kalahari Group and recent depositionary events cover the older rocks occasionally.
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.
Episodic low oxygenated conditions on the sea-floor are likely responsible for exceptional preservation of animal remains in the upper Amouslek Formation (lower Cambrian, Stage 3) on the northern slope of the western Anti-Atlas, Morocco. This stratigraphic interval has yielded trilobite, brachiopod, and hyolith fossils with preserved soft parts, including some of the oldest known trilobite guts. The "Souss fossil lagerstatte" (newly proposed designation) represents the first Cambrian fossil lagerstatte in Cambrian strata known from Africa and is one of the oldest trilobite-bearing fossil lagerstatten on Earth. Inter-regional correlation of the Souss fossil lagerstatte in West Gondwana suggests its development during an interval of high eustatic levels recorded by dark shales that occur in informal upper Cambrian Series 2 in Siberia, South China, and East Gondwana.
The new ellipsocephaloid trilobite species Kingaspidoides spinirecurvatus has a spectacular morphology because of a unique set of two long and anteriorly recurved spines on the occipital ring and the axial ring of thoracic segment 8. Together with the long genal spines this whimsical dorsally directed spine arrangement is thought to act as a non-standard protective device against predators. This is illustrated by the body posture during different stages of enrolment, contrasting with the more sophisticated spinosities seen in later trilobites, which are discussed in brief. Kingaspidoides spinirecurvatus from the lower–middle Cambrian boundary interval of the eastern Anti-Atlas in Morocco has been known for about two decades, with specimens handled as precious objects on the fossil market. Similar, but far less spectacular, spine arrangements on the thoracic axial rings are known from other ellipsocephaloid trilobites from the Anti-Atlas of Morocco and the Franconian Forest region of Germany. This suggests that an experimental phase of spine development took place within the Kingaspi-doides clade during the early–middle Cambrian boundary interval.
By 2050, two-third of the world’s population will live in cities. In this study, we develop a framework for analyzing urban growth-related imperviousness in North Rhine-Westphalia (NRW) from the 1980s to date using Landsat data. For the baseline 2017-time step, official geodata was extracted to generate labelled data for ten classes, including three classes representing low, middle, and high level of imperviousness. We used the output of the 2017 classification and information based on radiometric bi-temporal change detection for retrospective classification. Besides spectral bands, we calculated several indices and various temporal composites, which were used as an input for Random Forest classification. The results provide information on three imperviousness classes with accuracies exceeding 75%. According to our results, the imperviousness areas grew continuously from 1985 to 2017, with a high imperviousness area growth of more than 167,000 ha, comprising around 30% increase. The information on the expansion of urban areas was integrated with population dynamics data to estimate the progress towards SDG 11. With the intensity analysis and the integration of population data, the spatial heterogeneity of urban expansion and population growth was analysed, showing that the urban expansion rates considerably excelled population growth rates in some regions in NRW. The study highlights the applicability of earth observation data for accurately quantifying spatio-temporal urban dynamics for sustainable urbanization and targeted planning.
Drought is a recurring natural climatic hazard event over terrestrial land; it poses devastating threats to human health, the economy, and the environment. Given the increasing climate crisis, it is likely that extreme drought phenomena will become more frequent, and their impacts will probably be more devastating. Drought observations from space, therefore, play a key role in dissimilating timely and accurate information to support early warning drought management and mitigation planning, particularly in sparse in-situ data regions. In this paper, we reviewed drought-related studies based on Earth observation (EO) products in Southeast Asia between 2000 and 2021. The results of this review indicated that drought publications in the region are on the increase, with a majority (70%) of the studies being undertaken in Vietnam, Thailand, Malaysia and Indonesia. These countries also accounted for nearly 97% of the economic losses due to drought extremes. Vegetation indices from multispectral optical remote sensing sensors remained a primary source of data for drought monitoring in the region. Many studies (~21%) did not provide accuracy assessment on drought mapping products, while precipitation was the main data source for validation. We observed a positive association between spatial extent and spatial resolution, suggesting that nearly 81% of the articles focused on the local and national scales. Although there was an increase in drought research interest in the region, challenges remain regarding large-area and long time-series drought measurements, the combined drought approach, machine learning-based drought prediction, and the integration of multi-sensor remote sensing products (e.g., Landsat and Sentinel-2). Satellite EO data could be a substantial part of the future efforts that are necessary for mitigating drought-related challenges, ensuring food security, establishing a more sustainable economy, and the preservation of the natural environment in the region.