@article{PhilippDietzUllmannetal.2023,
  author    = {Philipp, Marius and Dietz, Andreas and Ullmann, Tobias and Kuenzer, Claudia},
  title     = {A circum-Arctic monitoring framework for quantifying annual erosion rates of permafrost coasts},
  series = {Remote Sensing},
  volume    = {15},
  journal   = {Remote Sensing},
  number    = {3},
  issn      = {2072-4292},
  doi       = {10.3390/rs15030818},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304447},
  year      = {2023},
  abstract  = {This study demonstrates a circum-Arctic monitoring framework for quantifying annual change of permafrost-affected coasts at a spatial resolution of 10 m. Frequent cloud coverage and challenging lighting conditions, including polar night, limit the usability of optical data in Arctic regions. For this reason, Synthetic Aperture RADAR (SAR) data in the form of annual median and standard deviation (sd) Sentinel-1 (S1) backscatter images covering the months June-September for the years 2017-2021 were computed. Annual composites for the year 2020 were hereby utilized as input for the generation of a high-quality coastline product via a Deep Learning (DL) workflow, covering 161,600 km of the Arctic coastline. The previously computed annual S1 composites for the years 2017 and 2021 were employed as input data for the Change Vector Analysis (CVA)-based coastal change investigation. The generated DL coastline product served hereby as a reference. Maximum erosion rates of up to 67 m per year could be observed based on 400 m coastline segments. Overall highest average annual erosion can be reported for the United States (Alaska) with 0.75 m per year, followed by Russia with 0.62 m per year. Out of all seas covered in this study, the Beaufort Sea featured the overall strongest average annual coastal erosion of 1.12 m. Several quality layers are provided for both the DL coastline product and the CVA-based coastal change analysis to assess the applicability and accuracy of the output products. The predicted coastal change rates show good agreement with findings published in previous literature. The proposed methods and data may act as a valuable tool for future analysis of permafrost loss and carbon emissions in Arctic coastal environments.},
  language  = {en}
}
@article{UereyenBachoferKuenzer2022,
  author    = {Uereyen, Soner and Bachofer, Felix and Kuenzer, Claudia},
  title     = {A framework for multivariate analysis of land surface dynamics and driving variables — a case study for Indo-Gangetic river basins},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {1},
  issn      = {2072-4292},
  doi       = {10.3390/rs14010197},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-255295},
  year      = {2022},
  abstract  = {The analysis of the Earth system and interactions among its spheres is increasingly important to improve the understanding of global environmental change. In this regard, Earth observation (EO) is a valuable tool for monitoring of long term changes over the land surface and its features. Although investigations commonly study environmental change by means of a single EO-based land surface variable, a joint exploitation of multivariate land surface variables covering several spheres is still rarely performed. In this regard, we present a novel methodological framework for both, the automated processing of multisource time series to generate a unified multivariate feature space, as well as the application of statistical time series analysis techniques to quantify land surface change and driving variables. In particular, we unify multivariate time series over the last two decades including vegetation greenness, surface water area, snow cover area, and climatic, as well as hydrological variables. Furthermore, the statistical time series analyses include quantification of trends, changes in seasonality, and evaluation of drivers using the recently proposed causal discovery algorithm Peter and Clark Momentary Conditional Independence (PCMCI). We demonstrate the functionality of our methodological framework using Indo-Gangetic river basins in South Asia as a case study. The time series analyses reveal increasing trends in vegetation greenness being largely dependent on water availability, decreasing trends in snow cover area being mostly negatively coupled to temperature, and trends of surface water area to be spatially heterogeneous and linked to various driving variables. Overall, the obtained results highlight the value and suitability of this methodological framework with respect to global climate change research, enabling multivariate time series preparation, derivation of detailed information on significant trends and seasonality, as well as detection of causal links with minimal user intervention. This study is the first to use multivariate time series including several EO-based variables to analyze land surface dynamics over the last two decades using the causal discovery algorithm PCMCI.},
  language  = {en}
}
@phdthesis{Wijnen2002,
  author    = {Wijnen, Jeroen Johan Andreas},
  title     = {A groundwater flow and particle tracking model of the Ira{\´i}-basin, Paran{\´a}, Brazil},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-531},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2002},
  abstract  = {Die Bev{\"o}lkerungsexplosion in der Region von Curitiba w{\"a}hrend der letzten Jahre verursachte eine große Zunahme des Wasserbedarfs; die zunehmend unkontrollierte Besiedlung stellt dabei ein großes Problem f{\"u}r die Umwelt dar. Die gr{\"o}ßte Bedrohung f{\"u}r die Wasserversorgung dieser Region ist die urbane Invasion in Gebiete, wo die Herkunft der Wasserressourcen liegen. Diese Invasion geht langsam aber stetig voran und bedroht kostbare und nicht ersetzbare Ressourcen. Vor diesem Hintergrund wurde ein Gebiet in der direkten N{\"a}he der Großstadt Curitiba als Studienobjekt ausgew{\"a}hlt. In diesem Gebiet, dem Ira{\´i}-Becken, wurde w{\"a}hrend der Untersuchungszeit ein Trinkwasserspeicher geplant und gebaut. Es besteht die große Gefahr, dass das Ira{\´i}-Reservoir kontaminiert wird, obwohl das engere Gebiet rundum den See gesch{\"u}tzt werden soll. Die Verschmutzungsgefahr geht haupts{\"a}chlich von zwei Nebenfl{\"u}ssen aus, die durch mehr oder weniger besiedeltes Gebiet str{\"o}men. Im Arbeitsgebiet befinden sich Brunnen, die der Trinkwasserversorgung dienen. Um die negativen Folgen einer m{\"o}glichen Verschmutzung des Reservoirs absch{\"a}tzen zu k{\"o}nnen, wurde ein Grundwasserfließmodell erstellt. Die erforderliche Wasserbilanz und die r{\"a}umliche Verteilung der Verschmutzungsempfindlichkeit wurde mit dem hydrologischen Modell "MODBIL" abgesch{\"a}tzt. Weitere Methoden zur Absch{\"a}tzung der Verschmutzungs-empfindlichkeit wurden angewandt, um die differierenden Ergebnisse der angewendeten unterschiedlichen Methoden mit einander vergleichen und bewerten zu k{\"o}nnen. Mit dem kalibrierten Grundwasserfließmodell ist mit der gegebenen hydraulischen Situation vor und nach der Konstruktion des Reservoirs, ein einfaches Particle Tracking Transport Modell eingesetzt worden, um mit unterschiedlichen Szenarien die Beeinflussung vom Reservoirwasser auf das Grundwasser zu simulieren.},
  subject      = {Curitiba <Region>},
  language  = {en}
}
@article{DirscherlDietzKneiseletal.2021,
  author    = {Dirscherl, Mariel and Dietz, Andreas J. and Kneisel, Christof and Kuenzer, Claudia},
  title     = {A novel method for automated supraglacial lake mapping in Antarctica using Sentinel-1 SAR imagery and deep learning},
  series = {Remote Sensing},
  volume    = {13},
  journal   = {Remote Sensing},
  number    = {2},
  issn      = {2072-4292},
  doi       = {10.3390/rs13020197},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-222998},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Kukulus2004,
  author    = {Kukulus, Matthias},
  title     = {A quantitative approach to the evolution of the central Walvis Basin offshore NW-Namibia : structure, mass balancing, and hydrocarbon potential},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-11075},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2004},
  abstract  = {Rifting and breakup of Westgondwana in the Late Jurassic/ Early Cretaceous initiated the formation of the South Atlantic and its conjugated pair of passive continental margins. The Walvis Basin offshore NW-Namibia is an Early Cretaceous to recent depositional centre with a typically wedge-shaped postrift sedimentary succession covering an area of 105000km2. A 2D model transect across the central Walvis Basin and adjacent onshore areas is used as a case study to investigate quantitatively the denudational history of the evolving passive margin and the related contemporaneous depositional postrift evolution offshore. The database for both the onshore and offshore part of the model traverse is well constrained by own field work, published data as well as by seismic and well data supported by samples. The ultimate goal of this project is to present an integrated approach towards a quantitative link between surface processes and internal processes in terms of a mass and process balance.},
  subject      = {Namibia <Nordwest>},
  language  = {en}
}
@article{HaHuthBachoferetal.2022,
  author    = {Ha, Tuyen V. and Huth, Juliane and Bachofer, Felix and Kuenzer, Claudia},
  title     = {A review of Earth observation-based drought studies in Southeast Asia},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {15},
  issn      = {2072-4292},
  doi       = {10.3390/rs14153763},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-286258},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{FekriLatifiAmanietal.2021,
  author    = {Fekri, Erfan and Latifi, Hooman and Amani, Meisam and Zobeidinezhad, Abdolkarim},
  title     = {A training sample migration method for wetland mapping and monitoring using Sentinel data in Google Earth Engine},
  series = {Remote Sensing},
  volume    = {13},
  journal   = {Remote Sensing},
  number    = {20},
  issn      = {2072-4292},
  doi       = {10.3390/rs13204169},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248542},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@article{Schamel2015,
  author    = {Schamel, Johannes},
  title     = {Ableitung von Pr{\"a}ferenzen aus GPS-Trajektorien bei landschaftsbezogenen Erholungsaktivit{\"a}ten},
  series = {AGIT - Journal f{\"u}r Angewandte Geoinformatik},
  volume    = {2015},
  journal   = {AGIT - Journal f{\"u}r Angewandte Geoinformatik},
  number    = {1},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-153590},
  pages     = {9},
  year      = {2015},
  abstract  = {No abstract available.},
  language  = {de}
}
@phdthesis{Allgaier2004,
  author    = {Allgaier, Axel},
  title     = {Aeolian sand movement in an arid linear dune ecosystem, Nizzana, Western Negev, Israel},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-14727},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2004},
  abstract  = {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.},
  subject      = {Negev},
  language  = {en}
}
@article{KumarKhamzinaKnoefeletal.2021,
  author    = {Kumar, Navneet and Khamzina, Asia and Kn{\"o}fel, Patrick and Lamers, John P. A. and Tischbein, Bernhard},
  title     = {Afforestation of degraded croplands as a water-saving option in irrigated region of the Aral Sea Basin},
  series = {Water},
  volume    = {13},
  journal   = {Water},
  number    = {10},
  issn      = {2073-4441},
  doi       = {10.3390/w13101433},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-239626},
  year      = {2021},
  abstract  = {Climate change is likely to decrease surface water availability in Central Asia, thereby necessitating land use adaptations in irrigated regions. The introduction of trees to marginally productive croplands with shallow groundwater was suggested for irrigation water-saving and improving the land's productivity. Considering the possible trade-offs with water availability in large-scale afforestation, our study predicted the impacts on water balance components in the lower reaches of the Amudarya River to facilitate afforestation planning using the Soil and Water Assessment Tool (SWAT). The land-use scenarios used for modeling analysis considered the afforestation of 62\% and 100\% of marginally productive croplands under average and low irrigation water supply identified from historical land-use maps. The results indicate a dramatic decrease in the examined water balance components in all afforestation scenarios based largely on the reduced irrigation demand of trees compared to the main crops. Specifically, replacing current crops (mostly cotton) with trees on all marginal land (approximately 663 km\(^2\)) in the study region with an average water availability would save 1037 mln m\(^3\) of gross irrigation input within the study region and lower the annual drainage discharge by 504 mln m\(^3\). These effects have a considerable potential to support irrigation water management and enhance drainage functions in adapting to future water supply limitations.},
  language  = {en}
}