@article{KoehlerKuenzer2020, author = {Koehler, Jonas and Kuenzer, Claudia}, title = {Forecasting spatio-temporal dynamics on the land surface using Earth Observation data — a review}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {21}, issn = {2072-4292}, doi = {10.3390/rs12213513}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-216285}, year = {2020}, abstract = {Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods. Geospatial Earth Observation (EO) data from remote sensing satellites has been collected continuously for 40 years and has the potential to facilitate the spatio-temporal forecasting of land surface dynamics. In this review we compiled 143 papers on EO-based forecasting of all aspects of the land surface published in 16 high-ranking remote sensing journals within the past decade. We analyzed the literature regarding research focus, the spatial scope of the study, the forecasting method applied, as well as the temporal and technical properties of the input data. We categorized the identified forecasting methods according to their temporal forecasting mechanism and the type of input data. Time-lagged regressions which are predominantly used for crop yield forecasting and approaches based on Markov Chains for future land use and land cover simulation are the most established methods. The use of external climate projections allows the forecasting of numerical land surface parameters up to one hundred years into the future, while auto-regressive time series modeling can account for intra-annual variances. Machine learning methods have been increasingly used in all categories and multivariate modeling that integrates multiple data sources appears to be more popular than univariate auto-regressive modeling despite the availability of continuously expanding time series data. Regardless of the method, reliable EO-based forecasting requires high-level remote sensing data products and the resulting computational demand appears to be the main reason that most forecasts are conducted only on a local scale. In the upcoming years, however, we expect this to change with further advances in the field of machine learning, the publication of new global datasets, and the further establishment of cloud computing for data processing.}, language = {en} } @article{ThonfeldSteinbachMuroetal.2020, author = {Thonfeld, Frank and Steinbach, Stefanie and Muro, Javier and Kirimi, Fridah}, title = {Long-term land use/land cover change assessment of the Kilombero catchment in Tanzania using random forest classification and robust change vector analysis}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {7}, issn = {2072-4292}, doi = {10.3390/rs12071057}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203513}, year = {2020}, abstract = {Information about land use/land cover (LULC) and their changes is useful for different stakeholders to assess future pathways of sustainable land use for food production as well as for nature conservation. In this study, we assess LULC changes in the Kilombero catchment in Tanzania, an important area of recent development in East Africa. LULC change is assessed in two ways: first, post-classification comparison (PCC) which allows us to directly assess changes from one LULC class to another, and second, spectral change detection. We perform LULC classification by applying random forests (RF) on sets of multitemporal metrics that account for seasonal within-class dynamics. For the spectral change detection, we make use of the robust change vector analysis (RCVA) and determine those changes that do not necessarily lead to another class. The combination of the two approaches enables us to distinguish areas that show (a) only PCC changes, (b) only spectral changes that do not affect the classification of a pixel, (c) both types of change, or (d) no changes at all. Our results reveal that only one-quarter of the catchment has not experienced any change. One-third shows both, spectral changes and LULC conversion. Changes detected with both methods predominantly occur in two major regions, one in the West of the catchment, one in the Kilombero floodplain. Both regions are important areas of food production and economic development in Tanzania. The Kilombero floodplain is a Ramsar protected area, half of which was converted to agricultural land in the past decades. Therefore, LULC monitoring is required to support sustainable land management. Relatively poor classification performances revealed several challenges during the classification process. The combined approach of PCC and RCVA allows us to detect spatial patterns of LULC change at distinct dimensions and intensities. With the assessment of additional classifier output, namely class-specific per-pixel classification probabilities and derived parameters, we account for classification uncertainty across space. We overlay the LULC change results and the spatial assessment of classification reliability to provide a thorough picture of the LULC changes taking place in the Kilombero catchment.}, language = {en} } @article{AkhundzadahSoltaniAich2020, author = {Akhundzadah, Noor Ahmad and Soltani, Salim and Aich, Valentin}, title = {Impacts of climate change on the water resources of the Kunduz River Basin, Afghanistan}, series = {Climate}, volume = {8}, journal = {Climate}, number = {10}, issn = {2225-1154}, doi = {10.3390/cli8100102}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-213199}, year = {2020}, abstract = {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.}, language = {en} } @article{UlloaTorrealbaStahlmannWegmannetal.2020, author = {Ulloa-Torrealba, Yrneh and Stahlmann, Reinhold and Wegmann, Martin and Koellner, Thomas}, title = {Over 150 years of change: object-oriented analysis of historical land cover in the Main river catchment, Bavaria/Germany}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {24}, issn = {2072-4292}, doi = {10.3390/rs12244048}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-220029}, year = {2020}, abstract = {The monitoring of land cover and land use change is critical for assessing the provision of ecosystem services. One of the sources for long-term land cover change quantification is through the classification of historical and/or current maps. Little research has been done on historical maps using Object-Based Image Analysis (OBIA). This study applied an object-based classification using eCognition tool for analyzing the land cover based on historical maps in the Main river catchment, Upper Franconia, Germany. This allowed land use change analysis between the 1850s and 2015, a time span which covers the phase of industrialization of landscapes in central Europe. The results show a strong increase in urban area by 2600\%, a severe loss of cropland (-24\%), a moderate reduction in meadows (-4\%), and a small gain in forests (+4\%). The method proved useful for the application on historical maps due to the ability of the software to create semantic objects. The confusion matrix shows an overall accuracy of 82\% for the automatic classification compared to manual reclassification considering all 17 sample tiles. The minimum overall accuracy was 65\% for historical maps of poor quality and the maximum was 91\% for very high-quality ones. Although accuracy is between high and moderate, coarse land cover patterns in the past and trends in land cover change can be analyzed. We conclude that such long-term analysis of land cover is a prerequisite for quantifying long-term changes in ecosystem services.}, language = {en} } @phdthesis{Buedel2020, author = {B{\"u}del, Christian}, title = {Quaternary alluvial fan morphodynamics and basin sedimentation in North Iran}, edition = {1. Auflage}, publisher = {W{\"u}rzburg University Press}, address = {W{\"u}rzburg}, isbn = {978-3-95826-114-3}, issn = {0510-9833}, doi = {10.25972/WUP-978-3-95826-115-0}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-184508}, school = {W{\"u}rzburg University Press}, pages = {XI, 124}, year = {2020}, abstract = {Several hundred meter thick alluvial fans are dominating the landscape of semiarid plains of north-eastern Iranian mountain-talus. These fans developed since Miocene times and are still prograding today. They are storing and transporting major amount of weathered debris from the mountain ranges and sediments are directed to the depressions of the endorheic basins. In this course, the debris gets increasingly weathered and abraded to sand silt and clay fractions, which finally constitute the fine loamy layers of the typical central playa lakes and playas. The study focused on the detailed investigation of a characteristic section of this prominent sediment cascades. The sediments were planned be comprehensively documented by using a fully analytical geomorphological mapping approach, also suitable for the classification of the sediment's geomorphological system contexts. Therefore, a geodatabase structure was developed, which is capable of managing and analyzing geomorphological data. The corresponding data was acquired using remote sensing imagery, digital elevation models and field mapping campaigns. Additionally, mapped sediments were selected and analyzed to reveal representative stratigraphic and sedimentologic characteristics. The fieldwork was conducted in Damghan Basin on sections in geomorphologically subdivided alluvial apron sediments. The corresponding, more regularly layered and partly laminated sediments from the central playa, were also investigated and comparably described. Attending to the preparation of profile sections and the percussion core probing, samples from both origins were taken. Detailed lithostratigraphical and geochemical analyses were carried out in the laboratory, in order to develop sound comparable sediment and sediment alteration indices. In addition, OSL sampling was done on distinct alluvial fan surfaces, and the samples were measured and dated in the laboratory in order to develop a functional chronostratigraphy. The results of the geomorphological and stratigraphical investigations reveal five classes of surface ages on the alluvial apron. Parallel to that observation, the ramming core samples exhibit four main phases of sediment development in the playa, each with internal differentiation. This brings up opportunities for a valid correlation of continuously deposited playa sediments, with widespread alluvial surfaces. By considering the OSL ages of selected terrestrial and lacustrine layers, the stratigraphy and relative chronological order of the studied sediments, are aligned to Pleistocene and mid to late Holocene periods. This is also confirmed by proxy ages from the chronological framework of the landscape development, within the basin. Geophysical and geochemical data reveals roughly cyclic sedimentation and sediment alteration that can also be observed in genetically differing geoarchives from alluvial fan surfaces to the playa sediments. These parallel developments are confirmed by the sequence-stratigraphic order of the archives which is derived from geomorphological mapping. We postulate a time span covered by the playa sediments from today to late Pleistocene times. Drying and Lake level retreat at the end of Pleistocene is documented in parallel geoarchives of terrestrial and lacustrine origin. Thus, geomorphologic landform-succession and alluvial fan morphogenesis, as well as geochemical and geophysical fingerprinting data of playa sediments characterize this development. Therefore, it is present in the two youngest generations of alluvial fans, which deposited at the toe of the alluvial apron and which incorporate reworked still water deposits of a former lake level terrace. The geochemical parameters, like pH-value and Ca/S-ratio, in both, sediments of a former lake level and those from the recent playa extent exhibit a similar development. In addition, Ti/Al-ratio shows the potential for quantifying lake level retreat, as it seems to be tightly depending on lake level and increasing transportation distances along the sediment cascade. Major Findings - Analytical geomorphological mapping is a key tool for understanding the sedimentation history of the Iranian Quaternary and for describing Quaternary stratigraphic units of North Iran. - The younger playa deposits in Damghan Basin cover a time span from today to late Pleistocene. They are 10 meters thick and reveal very low organic matter contents throughout the core. - Drying and Lake level retreat is documented in parallel geoarchives (1) in geomorphologic landform-succession and alluvial fan morphogenesis and (2) in geochemical and geophysical fingerprinting data of playa sediments - Sequences of torrential sedimentation are detectable signals and can be correlated in both: playa sediments and landform morphology}, subject = {Quart{\"a}rgeomorphologie}, language = {en} } @article{DirscherlDietzKneiseletal.2020, author = {Dirscherl, Mariel and Dietz, Andreas J. and Kneisel, Christof and Kuenzer, Claudia}, title = {Automated mapping of Antarctic supraglacial lakes using a Machine Learning approach}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {7}, issn = {2072-4292}, doi = {10.3390/rs12071203}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203735}, year = {2020}, abstract = {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.}, language = {en} } @article{StereńczakLaurinChiricietal.2020, author = {Stereńczak, Krzysztof and Laurin, Gaia Vaglio and Chirici, Gherardo and Coomes, David A. and Dalponte, Michele and Latifi, Hooman and Puletti, Nicola}, title = {Global Airborne Laser Scanning Data Providers Database (GlobALS) — a new tool for monitoring ecosystems and biodiversity}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {11}, issn = {2072-4292}, doi = {10.3390/rs12111877}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207819}, year = {2020}, abstract = {Protection and recovery of natural resource and biodiversity requires accurate monitoring at multiple scales. Airborne Laser Scanning (ALS) provides high-resolution imagery that is valuable for monitoring structural changes to vegetation, providing a reliable reference for ecological analyses and comparison purposes, especially if used in conjunction with other remote-sensing and field products. However, the potential of ALS data has not been fully exploited, due to limits in data availability and validation. To bridge this gap, the global network for airborne laser scanner data (GlobALS) has been established as a worldwide network of ALS data providers that aims at linking those interested in research and applications related to natural resources and biodiversity monitoring. The network does not collect data itself but collects metadata and facilitates networking and collaborative research amongst the end-users and data providers. This letter describes this facility, with the aim of broadening participation in GlobALS.}, language = {en} } @article{HuthGessnerKleinetal.2020, author = {Huth, Juliane and Gessner, Ursula and Klein, Igor and Yesou, Herv{\´e} and Lai, Xijun and Oppelt, Natascha and Kuenzer, Claudia}, title = {Analyzing water dynamics based on Sentinel-1 time series — a study for Dongting Lake wetlands in China}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {11}, issn = {2072-4292}, doi = {10.3390/rs12111761}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-205977}, year = {2020}, abstract = {In China, freshwater is an increasingly scarce resource and wetlands are under great pressure. This study focuses on China's second largest freshwater lake in the middle reaches of the Yangtze River — the Dongting Lake — and its surrounding wetlands, which are declared a protected Ramsar site. The Dongting Lake area is also a research region of focus within the Sino-European Dragon Programme, aiming for the international collaboration of Earth Observation researchers. ESA's Copernicus Programme enables comprehensive monitoring with area-wide coverage, which is especially advantageous for large wetlands that are difficult to access during floods. The first year completely covered by Sentinel-1 SAR satellite data was 2016, which is used here to focus on Dongting Lake's wetland dynamics. The well-established, threshold-based approach and the high spatio-temporal resolution of Sentinel-1 imagery enabled the generation of monthly surface water maps and the analysis of the inundation frequency at a 10 m resolution. The maximum extent of the Dongting Lake derived from Sentinel-1 occurred in July 2016, at 2465 km\(^2\), indicating an extreme flood year. The minimum size of the lake was detected in October, at 1331 km\(^2\). Time series analysis reveals detailed inundation patterns and small-scale structures within the lake that were not known from previous studies. Sentinel-1 also proves to be capable of mapping the wetland management practices for Dongting Lake polders and dykes. For validation, the lake extent and inundation duration derived from the Sentinel-1 data were compared with excerpts from the Global WaterPack (frequently derived by the German Aerospace Center, DLR), high-resolution optical data, and in situ water level data, which showed very good agreement for the period studied. The mean monthly extent of the lake in 2016 from Sentinel-1 was 1798 km\(^2\), which is consistent with the Global WaterPack, deviating by only 4\%. In summary, the presented analysis of the complete annual time series of the Sentinel-1 data provides information on the monthly behavior of water expansion, which is of interest and relevance to local authorities involved in water resource management tasks in the region, as well as to wetland conservationists concerned with the Ramsar site wetlands of Dongting Lake and to local researchers.}, language = {en} } @article{ForkuorUllmannGriesbeck2020, author = {Forkuor, Gerald and Ullmann, Tobias and Griesbeck, Mario}, title = {Mapping and monitoring small-scale mining activities in Ghana using Sentinel-1 time series (2015-2019)}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {6}, issn = {2072-4292}, doi = {10.3390/rs12060911}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203204}, year = {2020}, abstract = {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.}, language = {en} } @article{HeinemannSiegmannThonfeldetal.2020, author = {Heinemann, Sascha and Siegmann, Bastian and Thonfeld, Frank and Muro, Javier and Jedmowski, Christoph and Kemna, Andreas and Kraska, Thorsten and Muller, Onno and Schultz, Johannes and Udelhoven, Thomas and Wilke, Norman and Rascher, Uwe}, title = {Land surface temperature retrieval for agricultural areas using a novel UAV platform equipped with a thermal infrared and multispectral sensor}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {7}, issn = {2072-4292}, doi = {10.3390/rs12071075}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203557}, year = {2020}, abstract = {Land surface temperature (LST) is a fundamental parameter within the system of the Earth's surface and atmosphere, which can be used to describe the inherent physical processes of energy and water exchange. The need for LST has been increasingly recognised in agriculture, as it affects the growth phases of crops and crop yields. However, challenges in overcoming the large discrepancies between the retrieved LST and ground truth data still exist. Precise LST measurement depends mainly on accurately deriving the surface emissivity, which is very dynamic due to changing states of land cover and plant development. In this study, we present an LST retrieval algorithm for the combined use of multispectral optical and thermal UAV images, which has been optimised for operational applications in agriculture to map the heterogeneous and diverse agricultural crop systems of a research campus in Germany (April 2018). We constrain the emissivity using certain NDVI thresholds to distinguish different land surface types. The algorithm includes atmospheric corrections and environmental thermal emissions to minimise the uncertainties. In the analysis, we emphasise that the omission of crucial meteorological parameters and inaccurately determined emissivities can lead to a considerably underestimated LST; however, if the emissivity is underestimated, the LST can be overestimated. The retrieved LST is validated by reference temperatures from nearby ponds and weather stations. The validation of the thermal measurements indicates a mean absolute error of about 0.5 K. The novelty of the dual sensor system is that it simultaneously captures highly spatially resolved optical and thermal images, in order to construct the precise LST ortho-mosaics required to monitor plant diseases and drought stress and validate airborne and satellite data.}, language = {en} } @article{HolzwarthThonfeldAbdullahietal.2020, author = {Holzwarth, Stefanie and Thonfeld, Frank and Abdullahi, Sahra and Asam, Sarah and Da Ponte Canova, Emmanuel and Gessner, Ursula and Huth, Juliane and Kraus, Tanja and Leutner, Benjamin and Kuenzer, Claudia}, title = {Earth Observation based monitoring of forests in Germany: a review}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {21}, issn = {2072-4292}, doi = {10.3390/rs12213570}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-216334}, year = {2020}, abstract = {Forests in Germany cover around 11.4 million hectares and, thus, a share of 32\% of Germany's surface area. Therefore, forests shape the character of the country's cultural landscape. Germany's forests fulfil a variety of functions for nature and society, and also play an important role in the context of climate levelling. Climate change, manifested via rising temperatures and current weather extremes, has a negative impact on the health and development of forests. Within the last five years, severe storms, extreme drought, and heat waves, and the subsequent mass reproduction of bark beetles have all seriously affected Germany's forests. Facing the current dramatic extent of forest damage and the emerging long-term consequences, the effort to preserve forests in Germany, along with their diversity and productivity, is an indispensable task for the government. Several German ministries have and plan to initiate measures supporting forest health. Quantitative data is one means for sound decision-making to ensure the monitoring of the forest and to improve the monitoring of forest damage. In addition to existing forest monitoring systems, such as the federal forest inventory, the national crown condition survey, and the national forest soil inventory, systematic surveys of forest condition and vulnerability at the national scale can be expanded with the help of a satellite-based earth observation. In this review, we analysed and categorized all research studies published in the last 20 years that focus on the remote sensing of forests in Germany. For this study, 166 citation indexed research publications have been thoroughly analysed with respect to publication frequency, location of studies undertaken, spatial and temporal scale, coverage of the studies, satellite sensors employed, thematic foci of the studies, and overall outcomes, allowing us to identify major research and geoinformation product gaps.}, language = {en} } @article{UsmanMahmoodConradetal.2020, author = {Usman, Muhammad and Mahmood, Talha and Conrad, Christopher and Bodla, Habib Ullah}, title = {Remote Sensing and modelling based framework for valuing irrigation system efficiency and steering indicators of consumptive water use in an irrigated region}, series = {Sustainability}, volume = {12}, journal = {Sustainability}, number = {22}, issn = {2071-1050}, doi = {10.3390/su12229535}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-219358}, year = {2020}, abstract = {Water crises are becoming severe in recent times, further fueled by population increase and climate change. They result in complex and unsustainable water management. Spatial estimation of consumptive water use is vital for performance assessment of the irrigation system using Remote Sensing (RS). For this study, its estimation is done using the Soil Energy Balance Algorithm for Land (SEBAL) approach. Performance indicators including equity, adequacy, and reliability were worked out at various spatiotemporal scales. Moreover, optimization and sustainable use of water resources are not possible without knowing the factors mainly influencing consumptive water use of major crops. For that purpose, random forest regression modelling was employed using various sets of factors for site-specific, proximity, and cropping system. The results show that the system is underperforming both for Kharif (i.e., summer) and Rabi (i.e., winter) seasons. Performance indicators highlight poor water distribution in the system, a shortage of water supply, and unreliability. The results are relatively good for Rabi as compared to Kharif, with an overall poor situation for both seasons. Factors importance varies for different crops. Overall, distance from canal, road density, canal density, and farm approachability are the most important factors for explaining consumptive water use. Auditing of consumptive water use shows the potential for resource optimization through on-farm water management by the targeted approach. The results are based on the present situation without considering future changes in canal water supply and consumptive water use under climate change.}, language = {en} } @phdthesis{Emmert2020, author = {Emmert, Adrian Alexander}, title = {The Internal Structure of Periglacial Landforms - Assessments of Subsurface Variations in Permafrost-related and Frost-related Phenomena by Multi-dimensional Geophysical Investigations}, edition = {1. Auflage}, publisher = {W{\"u}rzburg University Press}, address = {W{\"u}rzburg}, isbn = {978-3-95826-138-9}, doi = {10.25972/WUP-978-3-95826-139-6}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-202437}, school = {W{\"u}rzburg University Press}, pages = {xix, 167}, year = {2020}, abstract = {The internal structure of periglacial landforms contains valuable information on past and present environmental conditions. To benefit from this archive, however, an enhanced understanding of subsurface variations is crucial. This enables to assess the influence of the internal structure on prevailing process regimes and to evaluate the sensitivity of different landform units to environmental changes. This thesis investigates structural variations in the subsurface of (i) rock glaciers,(ii) solifluction lobes, (iii) palsas/ lithalsas and (iv) patterned ground, which occur between the different landform types, but also between landform units of the same type. Investigated variables comprise (i) the spatial distribution of permafrost, (ii) ground ice content, (iii) the origin of ground ice, (iv) thickness of the active layer and (v) frost table topography. Multi-dimensional investigations by the geophysical methods Electrical Resistivity Imaging (ERI) and Ground-Penetrating Radar (GPR) were performed in six study areas (a-f): four of them are located in high-alpine environments in Switzerland and two of them are located in the subarctic highlands of Iceland. Additionally, surface and subsurface temperature values were continuously recorded at selected study sites. At one study site, pF-values, representing the matric potential (or water potential), were recorded. From a methodological view, this thesis focuses on the application of quasi-3-D ERI, an approach in which many two-dimensional data sets are combined to create one three-dimensional data set. This permits e.g., a three-dimensional delimitation of subsurface structures and a spatial investigation of the distribution of ground ice. Besides the analysis of field data, this thesis incudes a comparison between inversion models produced with different software products, based on two synthetic data sets. The detection of resistivity structures and reflection patterns provides valuable insights into the internal structure of the investigated landform units: At the high-alpine study site at (a) Piz Nair, a highly variable ice content indicates a complex development of the investigated rock glacier assembly. The local formation of ground ice is attributed to an embedding of surface patches of snow or ice into the subsurface by rockfall. Results of geoelectric monitoring surveys on selected rock glaciers show the influence of seasonal alterations in the internal structure on subsurface meltwater flow. At the study site at (b) Piz {\"U}ertsch, results indicate the occurrences of isolated ground ice patches in a significantly larger rock glacier. Detected characteristics of the internal structure enable to reconstruct the development of the rock glacier, in which a temporary override of an adjacent glacier tongue on the rock glacier is considered crucial for the current distribution of ground ice. However, results of this thesis clearly show the absence of buried glacier ice in the subsurface of the rock glacier. Results from a rock glacier near the (c) Las Trais Fluors mountain ridge affirm the existence of a water-permeable frozen layer, which was assumed in previous studies. Furthermore, results show that the rock glacier contains large amounts of rockfall deposits. A joint interpretation of ERI and GPR results from the investigated scree slope at the mountain (d) Blauberg (Furka Pass) reveals characteristic structures in the subsurface, which enable a differentiation between solifluction lobes and pebbly rock glaciers. At the subarctic study site (e) Orravatnsr{\´u}stir, results show that the internal structure of palsas can be used to deduce their current development stage and to assess past and future developments. Presented results affirm a long history of palsa development at the study site, as assumed in previous studies, but indicate recently changing environmental conditions. The investigated occurrences of patterned ground in the proglacial area of the glacier (f) Hofsj{\"o}kull are currently not influenced by the detected occurrence of permafrost, according to the presented results. Therefore, a temporary formation of pattered ground is assumed, which is linked to the retreat of the glacier. This thesis shows discrepancies between the internal structure of some of the investigated landform units and the recent environmental conditions. This indicates a delayed adaption and a low sensitivity of the landform units to environmental changes. Findings indicate that the future development of permafrost will be strongly affected by variations in snowfall. Furthermore, the detection of isolated occurrences of ground ice at several study sites contradicts the widely assumed effectivity of balancing heat fluxes to create homogenous subsurface conditions in relatively fine-grained subsurface materials.}, subject = {Permafrost}, language = {en} } @article{RemelgadoSafiWegmann2020, author = {Remelgado, Ruben and Safi, Kamran and Wegmann, Martin}, title = {From ecology to remote sensing: using animals to map land cover}, series = {Remote Sensing in Ecology and Conservation}, volume = {6}, journal = {Remote Sensing in Ecology and Conservation}, number = {1}, doi = {10.1002/rse2.126}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-225200}, pages = {93-104}, year = {2020}, abstract = {Land cover is a key variable in monitoring applications and new processing technologies made deriving this information easier. Yet, classification algorithms remain dependent on samples collected on the field and field campaigns are limited by financial, infrastructural and political boundaries. Here, animal tracking data could be an asset. Looking at the land cover dependencies of animal behaviour, we can obtain land cover samples over places that are difficult to access. Following this premise, we evaluated the potential of animal movement data to map land cover. Specifically, we used 13 White Storks (Cicona cicona) individuals of the same population to map agriculture within three test regions distributed along their migratory track. The White Stork has adapted to foraging over agricultural lands, making it an ideal source of samples to map this land use. We applied a presence-absence modelling approach over a Normalized Difference Vegetation Index (NDVI) time series and validated our classifications, with high-resolution land cover information. Our results suggest White Stork movement is useful to map agriculture, however, we identified some limitations. We achieved high accuracies (F1-scores > 0.8) for two test regions, but observed poor results over one region. This can be explained by differences in land management practices. The animals preferred agriculture in every test region, but our data showed a biased distribution of training samples between irrigated and non-irrigated land. When both options occurred, the animals disregarded non-irrigated land leading to its misclassification as non-agriculture. Additionally, we found difference between the GPS observation dates and the harvest times for non-irrigated crops. Given the White Stork takes advantage of managed land to search for prey, the inactivity of these fields was the likely culprit of their underrepresentation. Including more species attracted to agriculture - with other land-use dependencies and observation times - can contribute to better results in similar applications.}, language = {en} } @article{ZieglerPollingerBoelletal.2020, author = {Ziegler, Katrin and Pollinger, Felix and B{\"o}ll, Susanne and Paeth, Heiko}, title = {Statistical modeling of phenology in Bavaria based on past and future meteorological information}, series = {Theoretical and Applied Climatology}, volume = {140}, journal = {Theoretical and Applied Climatology}, issn = {0177-798X}, doi = {10.1007/s00704-020-03178-4}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232717}, pages = {1467-1481}, year = {2020}, abstract = {Plant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases arecommonly considered some of the most obvious effects of climate change. However, current climate models lack a representationof vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modelingapproach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data foranalyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of severalmeteorological variables were used as predictors and phenological anomalies of the flowering date of the test plantForsythiasuspensaas predictand. Several cross-validated prediction models using various numbers and differently constructed predictorswere developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observationsper phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust andsuccessful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its averagecoefficient of determination and root mean square error (RMSE) per station are 60\% and ± 8.6 days, respectively. However, theprediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparablelevel of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants andregions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century comparedto the phenology of the reference period (1961-1990).}, language = {en} } @article{GeyerPaisWotte2020, author = {Geyer, Gerd and Pais, Miguel Caldeira and Wotte, Thomas}, title = {Unexpectedly curved spines in a Cambrian trilobite: considerations on the spinosity in Kingaspidoides spinirecurvatus sp. nov. from the Anti-Atlas, Morocco, and related Cambrian ellipsocephaloids}, series = {PalZ}, volume = {94}, journal = {PalZ}, issn = {0031-0220}, doi = {10.1007/s12542-020-00514-x}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231873}, pages = {645-660}, year = {2020}, abstract = {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.}, language = {en} }