@phdthesis{Uereyen2022,
  author    = {{\"U}reyen, Soner},
  title     = {Multivariate Time Series for the Analysis of Land Surface Dynamics - Evaluating Trends and Drivers of Land Surface Variables for the Indo-Gangetic River Basins},
  doi       = {10.25972/OPUS-29194},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-291941},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {The investigation of the Earth system and interplays between its components is of utmost importance to enhance the understanding of the impacts of global climate change on the Earth's land surface. In this context, Earth observation (EO) provides valuable long-term records covering an abundance of land surface variables and, thus, allowing for large-scale analyses to quantify and analyze land surface dynamics across various Earth system components. In view of this, the geographical entity of river basins was identified as particularly suitable for multivariate time series analyses of the land surface, as they naturally cover diverse spheres of the Earth. Many remote sensing missions with different characteristics are available to monitor and characterize the land surface. Yet, only a few spaceborne remote sensing missions enable the generation of spatio-temporally consistent time series with equidistant observations over large areas, such as the MODIS instrument. In order to summarize available remote sensing-based analyses of land surface dynamics in large river basins, a detailed literature review of 287 studies was performed and several research gaps were identified. In this regard, it was found that studies rarely analyzed an entire river basin, but rather focused on study areas at subbasin or regional scale. In addition, it was found that transboundary river basins remained understudied and that studies largely focused on selected riparian countries. Moreover, the analysis of environmental change was generally conducted using a single EO-based land surface variable, whereas a joint exploration of multivariate land surface variables across spheres was found to be rarely performed. To address these research gaps, a methodological framework enabling (1) the preprocessing and harmonization of multi-source time series as well as (2) the statistical analysis of a multivariate feature space was required. For development and testing of a methodological framework that is transferable in space and time, the transboundary river basins Indus, Ganges, Brahmaputra, and Meghna (IGBM) in South Asia were selected as study area, having a size equivalent to around eight times the size of Germany. These basins largely depend on water resources from monsoon rainfall and High Mountain Asia which holds the largest ice mass outside the polar regions. In total, over 1.1 billion people live in this region and in parts largely depend on these water resources which are indispensable for the world's largest connected irrigated croplands and further domestic needs as well. With highly heterogeneous geographical settings, these river basins allow for a detailed analysis of the interplays between multiple spheres, including the anthroposphere, biosphere, cryosphere, hydrosphere, lithosphere, and atmosphere. In this thesis, land surface dynamics over the last two decades (December 2002 - November 2020) were analyzed using EO time series on vegetation condition, surface water area, and snow cover area being based on MODIS imagery, the DLR Global WaterPack and JRC Global Surface Water Layer, as well as the DLR Global SnowPack, respectively. These data were evaluated in combination with further climatic, hydrological, and anthropogenic variables to estimate their influence on the three EO land surface variables. The preprocessing and harmonization of the time series was conducted using the implemented framework. The resulting harmonized feature space was used to quantify and analyze land surface dynamics by means of several statistical time series analysis techniques which were integrated into the framework. In detail, these methods involved (1) the calculation of trends using the Mann-Kendall test in association with the Theil-Sen slope estimator, (2) the estimation of changes in phenological metrics using the Timesat tool, (3) the evaluation of driving variables using the causal discovery approach Peter and Clark Momentary Conditional Independence (PCMCI), and (4) additional correlation tests to analyze the human influence on vegetation condition and surface water area. These analyses were performed at annual and seasonal temporal scale and for diverse spatial units, including grids, river basins and subbasins, land cover and land use classes, as well as elevation-dependent zones. The trend analyses of vegetation condition mostly revealed significant positive trends. Irrigated and rainfed croplands were found to contribute most to these trends. The trend magnitudes were particularly high in arid and semi-arid regions. Considering surface water area, significant positive trends were obtained at annual scale. At grid scale, regional and seasonal clusters with significant negative trends were found as well. Trends for snow cover area mostly remained stable at annual scale, but significant negative trends were observed in parts of the river basins during distinct seasons. Negative trends were also found for the elevation-dependent zones, particularly at high altitudes. Also, retreats in the seasonal duration of snow cover area were found in parts of the river basins. Furthermore, for the first time, the application of the causal discovery algorithm on a multivariate feature space at seasonal temporal scale revealed direct and indirect links between EO land surface variables and respective drivers. In general, vegetation was constrained by water availability, surface water area was largely influenced by river discharge and indirectly by precipitation, and snow cover area was largely controlled by precipitation and temperature with spatial and temporal variations. Additional analyses pointed towards positive human influences on increasing trends in vegetation greenness. The investigation of trends and interplays across spheres provided new and valuable insights into the past state and the evolution of the land surface as well as on relevant climatic and hydrological driving variables. Besides the investigated river basins in South Asia, these findings are of great value also for other river basins and geographical regions.},
  subject      = {Multivariate Analyse},
  language  = {en}
}
@phdthesis{Ziegler2022,
  author    = {Ziegler, Katrin},
  title     = {Implementierung von verbesserten Landoberfl{\"a}chenparametern und -prozessen in das hochaufgel{\"o}ste Klimamodell REMO},
  doi       = {10.25972/OPUS-26128},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-261285},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {Das Ziel dieser Arbeit war neue Eingangsdaten f{\"u}r die Landoberfl{\"a}chenbeschreibung des regionalen Klimamodells REMO zu finden und ins Modell zu integrieren, um die Vorhersagequalit{\"a}t des Modells zu verbessern. Die neuen Daten wurden so in das Modell eingebaut, dass die bisherigen Daten weiterhin als Option verf{\"u}gbar sind. Dadurch kann {\"u}berpr{\"u}ft werden, ob und in welchem Umfang sich die von jedem Klimamodell ben{\"o}tigten Rahmendaten auf Modellergebnisse auswirken. Im Zuge der Arbeit wurden viele unterschiedliche Daten und Methoden zur Generierung neuer Parameter miteinander verglichen, denn neben dem Ersetzen der konstanten Eingangswerte f{\"u}r verschiedene Oberfl{\"a}chenparameter und den damit verbundenen {\"A}nderungen wurden als zus{\"a}tzliche Verbesserung auch Ver{\"a}nderungen an der Parametrisierung des Bodens speziell in Hinblick auf die Bodentemperaturen in REMO vorgenommen. Im Rahmen dieser Arbeit wurden die durch die verschiedenen {\"A}nderungen ausgel{\"o}sten Auswirkungen f{\"u}r das CORDEX-Gebiet EUR-44 mit einer Aufl{\"o}sung von ca. 50km und f{\"u}r das in dem darin eingebetteten neu definierten Deutschlandgebiet GER-11 mit einer Aufl{\"o}sung von ca. 12km getestet sowie alle {\"A}nderungen anhand von verschiedenen Beobachtungsdatens{\"a}tzen validiert. Die vorgenommenen Arbeiten gliederten sich in drei Hauptteile. Der erste Teil bestand in dem vom eigentlichen Klimamodell unabh{\"a}ngigen Vergleich der verschiedenen Eingangsdaten auf unterschiedlichen Aufl{\"o}sungen und deren Performanz in allen Teilen der Erde, wobei ein besonderer Fokus auf der Qualit{\"a}t in den sp{\"a}teren Modellgebieten lag. Unter Ber{\"u}cksichtigung der Faktoren, wie einer globalen Verf{\"u}gbarkeit der Daten, einer verbesserten r{\"a}umlichen Aufl{\"o}sung und einer kostenlosen Nutzung der Daten sowie verschiedener Validationsergebnissen von anderen Studien, wurden in dieser Arbeit vier neue Topographiedatens{\"a}tze (SRTM, ALOS, TANDEM und ASTER) und drei neue Bodendatens{\"a}tze (FAOn, Soilgrid und HWSD) f{\"u}r die Verwendung im Pr{\"a}prozess von REMO aufbereitet und miteinander sowie mit den bisher in REMO verwendeten Daten verglichen. Auf Grundlage dieser Vergleichsstudien schieden bei den Topographiedaten die verwendeten Datensatz-Versionen von SRTM, ALOS und TANDEM f{\"u}r die in dieser Arbeit durchgef{\"u}hrten REMO-L{\"a}ufe aus. Bei den neuen Bodendatens{\"a}tzen wurde ausgenutzt, dass diese verschiedenen Bodeneigenschaften f{\"u}r unterschiedliche Tiefen als Karten zur Verf{\"u}gung stellen. In REMO wurden bisher alle ben{\"o}tigten Bodenparameter abh{\"a}ngig von f{\"u}nf verschiedenen Bodentexturklassen und einer zus{\"a}tzlichen Torfklasse ausgewiesen und als konstant {\"u}ber die gesamte Modellbodens{\"a}ule (bis ca. 10m) angenommen. Im zweiten Teil wurden auf Basis der im ersten Teil ausgew{\"a}hlten neuen Datens{\"a}tze und den neu verf{\"u}gbaren Bodenvariablen verschiedene Sensitivit{\"a}tsstudien {\"u}ber das Beispieljahr 2000 durchgef{\"u}hrt. Dabei wurden verschiedene neue Parametrisierungen f{\"u}r die bisher aus der Textur abgeleiteten Bodenvariablen und die Parametrisierung von weiteren hydrologischen und thermalen Bodeneigenschaften verglichen. Ferner wurde aufgrund der neuen nicht {\"u}ber die Tiefe konstanten Bodeneigenschaften eine neue numerische Methode zur Berechnung der Bodentemperaturen der f{\"u}nf Schichten in REMO getestet, welche wiederum andere Anpassungen erforderte. Der Test und die Auswahl der verschiedenen Datensatz- und Parametrisierungsversionen auf die Modellperformanz wurde in drei Experimentpl{\"a}ne unterteilt. Im ersten Plan wurden die Auswirkungen der ausgew{\"a}hlten Topographie- und Bodendatens{\"a}tze {\"u}berpr{\"u}ft. Der zweite Plan behandelte die Unterschiede der verschiedenen Parametrisierungsarten der Bodenvariablen hinsichtlich der verwendeten Variablen zur Berechnung der Bodeneigenschaften, der {\"u}ber die Tiefe variablen oder konstanten Eigenschaften und der verwendeten Berechnungsmethode der Bodentemperatur{\"a}nderungen. Durch die Erkenntnisse aus diesen beiden Experimentpl{\"a}nen, die f{\"u}r beide Untersuchungsgebiete durchgef{\"u}hrt wurden, ergaben sich im dritten Plan weitere Parametrisierungs{\"a}nderungen. Alle {\"A}nderungen dieses dritten Experimentplans wurden sukzessiv getestet, sodass der paarweise Vergleich von zwei aufeinanderfolgenden Modelll{\"a}ufen die Auswirkungen der Neuerung im jeweils zweiten Lauf widerspiegelt. Der letzte Teil der Arbeit bestand aus der Analyse von f{\"u}nf l{\"a}ngeren Modelll{\"a}ufen (2000-2018), die zur {\"U}berpr{\"u}fung der Ergebnisse aus den Sensitivit{\"a}tsstudien sowie zur Einsch{\"a}tzung der Performanz in weiteren teilweise extremen atmosph{\"a}rischen Bedingungen durchgef{\"u}hrt wurden. Hierf{\"u}r wurden die bisherige Modellversion von REMO (id01) f{\"u}r die beiden Untersuchungsgebiete EUR-44 und GER-11 als Referenzl{\"a}ufe, zwei aufgrund der Vergleichsergebnisse von Experimentplan 3 selektierte Modellversionen (id06 und id15a f{\"u}r GER-11) sowie die finale Version (id18a f{\"u}r GER-11), die alle vorgenommenen {\"A}nderungen dieser Arbeit enth{\"a}lt, ausgew{\"a}hlt. Es stellte sich heraus, dass sowohl die neuen Topographiedaten als auch die neuen Bodendaten große Differenzen zu den bisherigen Daten in REMO haben. Zudem {\"a}nderten sich die von diesen konstanten Eingangsdaten abgeleiteten Hilfsvariablen je nach verwendeter Parametrisierung sehr deutlich. Dies war besonders gut anhand der Bodenparameter zu erkennen. Sowohl die r{\"a}umliche Verteilung als auch der Wertebereich der verschiedenen Modellversionen unterschieden sich stark. Eine Einsch{\"a}tzung der Qualit{\"a}t der resultierenden Parameter wurde jedoch dadurch erschwert, dass auch die verschiedenen zur Validierung herangezogenen Bodendatens{\"a}tze f{\"u}r diese Parameter deutlich voneinander abweichen. Die finale Modellversion id18a {\"a}hnelte trotz der umfassenden {\"A}nderungen in den meisten Variablen den Ergebnissen der bisherigen REMO-Version. Je nach zeitlicher und r{\"a}umlicher Aggregation sowie unterschiedlichen Regionen und Jahreszeiten wurden leichte Verbesserungen, aber auch leichte Verschlechterungen im Vergleich zu den klimatologischen Validationsdaten festgestellt. Gr{\"o}ßere Ver{\"a}nderungen im Vergleich zur bisherigen Modellversion konnten in den tieferen Bodenschichten aufgezeigt werden, welche allerdings aufgrund von fehlenden Validationsdaten nicht beurteilt werden konnten. F{\"u}r alle 2m-Temperaturen konnte eine tendenzielle leichte Erw{\"a}rmung im Vergleich zum bisherigen Modelllauf beobachtet werden, was sich einerseits negativ auf die ohnehin durchschnittlich zu hohe Minimumtemperatur, aber andererseits positiv auf die bisher zu niedrige Maximumtemperatur des Modells in den betrachteten Gebieten auswirkte. Im Niederschlagssignal und in den 10m-Windvariablen konnten keine signifikanten {\"A}nderungen nachgewiesen werden, obwohl die neue Topographie an manchen Stellen im Modellgebiet deutlich von der bisherigen abweicht. Des Weiteren variierte das Ranking der verschiedenen Modellversionen jeweils nach dem angewendeten Qualit{\"a}tsindex. Um diese Ergebnisse besser einordnen zu k{\"o}nnen, muss ber{\"u}cksichtigt werden, dass die neuen Daten f{\"u}r Modellgebiete mit 50 bzw. 12km r{\"a}umlicher Aufl{\"o}sung und der damit verbundenen hydrostatischen Modellversion getestet wurden. Zudem sind vor allem in Fall der Topographie die bisher enthaltenen GTOPO-Daten (1km Aufl{\"o}sung) f{\"u}r die Aggregation auf diese gr{\"o}bere Modellaufl{\"o}sung geeignet. Die bisherigen Bodendaten stoßen jedoch mit 50km Aufl{\"o}sung bereits an ihre Grenzen. Zus{\"a}tzlich ist zu beachten, dass nicht nur die Mittelwerte dieser Daten, sondern auch deren Subgrid-Variabilit{\"a}t als Variablen im Modell f{\"u}r verschiedene Parametrisierungen verwendet werden. Daher ist es essentiell, dass die Eingangsdaten eine deutlich h{\"o}here Aufl{\"o}sung bereitstellen als die zur Modellierung definierte Aufl{\"o}sung. F{\"u}r lokale Klimasimulationen mit Aufl{\"o}sungen im niedrigen Kilometerbereich spielen auch die Vertikalbewegungen (nicht-hydrostatische Modellversion) eine wichtige Rolle, die stark von der Topographie sowie deren horizontaler und vertikaler {\"A}nderungsrate beeinflusst werden, was die in dieser Arbeit eingebauten wesentlich h{\"o}her aufgel{\"o}sten Daten f{\"u}r die zuk{\"u}nftige Weiterentwicklung von REMO wertvoll machen kann.},
  subject      = {Klimamodell},
  language  = {de}
}
@article{YangYaoLietal.2022,
  author    = {Yang, Xuting and Yao, Wanqiang and Li, Pengfei and Hu, Jinfei and Latifi, Hooman and Kang, Li and Wang, Ningjing and Zhang, Dingming},
  title     = {Changes of SOC content in China's Shendong coal mining area during 1990-2020 investigated using remote sensing techniques},
  series = {Sustainability},
  volume    = {14},
  journal   = {Sustainability},
  number    = {12},
  issn      = {2071-1050},
  doi       = {10.3390/su14127374},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-278939},
  year      = {2022},
  abstract  = {Coal mining, an important human activity, disturbs soil organic carbon (SOC) accumulation and decomposition, eventually affecting terrestrial carbon cycling and the sustainability of human society. However, changes of SOC content and their relation with influential factors in coal mining areas remained unclear. In the study, predictive models of SOC content were developed based on field sampling and Landsat images for different land-use types (grassland, forest, farmland, and bare land) of the largest coal mining area in China (i.e., Shendong). The established models were employed to estimate SOC content across the Shendong mining area during 1990-2020, followed by an investigation into the impacts of climate change and human disturbance on SOC content by a Geo-detector. Results showed that the models produced satisfactory results (R\(^2\) > 0.69, p < 0.05), demonstrating that SOC content over a large coal mining area can be effectively assessed using remote sensing techniques. Results revealed that average SOC content in the study area rose from 5.67 gC·kg\(^{-1}\) in 1990 to 9.23 gC·kg\(^{-1}\) in 2010 and then declined to 5.31 gC·Kg\(^{-1}\) in 2020. This could be attributed to the interaction between the disturbance of soil caused by coal mining and the improvement of eco-environment by land reclamation. Spatially, the SOC content of farmland was the highest, followed by grassland, and that of bare land was the lowest. SOC accumulation was inhibited by coal mining activities, with the effect of high-intensity mining being lower than that of moderate- and low-intensity mining activities. Land use was found to be the strongest individual influencing factor for SOC content changes, while the interaction between vegetation coverage and precipitation exerted the most significant influence on the variability of SOC content. Furthermore, the influence of mining intensity combined with precipitation was 10 times higher than that of mining intensity alone.},
  language  = {en}
}
@phdthesis{Wilde2022,
  author    = {Wilde, Martina},
  title     = {Landslide susceptibility assessment in the Chiconquiaco Mountain Range area, Veracruz (Mexico)},
  doi       = {10.25972/OPUS-27608},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-276085},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {In Mexico, numerous landslides occur each year and Veracruz represents the state with the third highest number of events. Especially the Chiconquiaco Mountain Range, located in the central part of Veracruz, is highly affected by landslides and no detailed information on the spatial distribution of existing landslides or future occurrences is available. This leaves the local population exposed to an unknown threat and unable to react appropriately to this hazard or to consider the potential landslide occurrence in future planning processes. Thus, the overall objective of the present study is to provide a comprehensive assessment of the landslide situation in the Chiconquiaco Mountain Range area. Here, the combination of a site-specific and a regional approach enables to investigate the causes, triggers, and process types as well as to model the landslide susceptibility for the entire study area. For the site-specific approach, the focus lies on characterizing the Capul{\´i}n landslide, which represents one of the largest mass movements in the area. In this context, the task is to develop a multi-methodological concept, which concentrates on cost-effective, flexible and non-invasive methods. This approach shows that the applied methods complement each other very well and their combination allows for a detailed characterization of the landslide. The analyses revealed that the Capul{\´i}n landslide is a complex mass movement type. It comprises rotational movement in the upper parts and translational movement in the lower areas, as well as flow processes at the flank and foot area and therefore, is classified as a compound slide-flow according to Cruden and Varnes (1996). Furthermore, the investigations show that the Capul{\´i}n landslide represents a reactivation of a former process. This is an important new information, especially with regard to the other landslides identified in the study area. Both the road reconstructed after the landslide, which runs through the landslide mass, and the stream causing erosion processes at the foot of the landslide severely affect the stability of the landslide, making it highly susceptible to future reactivation processes. This is particularly important as the landslide is located only few hundred meters from the village El Capul{\´i}n and an extension of the landslide area could cause severe damage. The next step in the landslide assessment consists of integrating the data obtained in the site-specific approach into the regional analysis. Here, the focus lies on transferring the generated data to the entire study area. The developed methodological concept yields applicable results, which is supported by different validation approaches. The susceptibility modeling as well as the landslide inventory reveal that the highest probability of landslides occurrence is related to the areas with moderate slopes covered by slope deposits. These slope deposits comprise material from old mass movements and erosion processes and are highly susceptible to landslides. The results give new insights into the landslide situation in the Chiconquiaco Mountain Range area, since previously landslide occurrence was related to steep slopes of basalt and andesite. The susceptibility map is a contribution to a better assessment of the landslide situation in the study area and simultaneously proves that it is crucial to include specific characteristics of the respective area into the modeling process, otherwise it is possible that the local conditions will not be represented correctly.},
  subject      = {Naturgefahren},
  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}
}
@article{SognoKleinKuenzer2022,
  author    = {Sogno, Patrick and Klein, Igor and Kuenzer, Claudia},
  title     = {Remote sensing of surface water dynamics in the context of global change — a review},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {10},
  issn      = {2072-4292},
  doi       = {10.3390/rs14102475},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275274},
  year      = {2022},
  abstract  = {Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource — if not overexploited — sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution.},
  language  = {en}
}
@article{RoeschPlank2022,
  author    = {R{\"o}sch, Moritz and Plank, Simon},
  title     = {Detailed mapping of lava and ash deposits at Indonesian volcanoes by means of VHR PlanetScope change detection},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {5},
  issn      = {2072-4292},
  doi       = {10.3390/rs14051168},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-262232},
  year      = {2022},
  abstract  = {Mapping of lava flows in unvegetated areas of active volcanoes using optical satellite data is challenging due to spectral similarities of volcanic deposits and the surrounding background. Using very high-resolution PlanetScope data, this study introduces a novel object-oriented classification approach for mapping lava flows in both vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes (Karangetang 2018/2019, Agung 2017, Krakatau 2018/2019). For this, change detection analysis based on PlanetScope imagery for mapping loss of vegetation due to volcanic activity (e.g., lava flows) is combined with the analysis of changes in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. Qualitative comparison of the mapped lava flows showed good agreement with multispectral false color time series (Sentinel-2 and Landsat-8). Reports of the Global Volcanism Program support the findings, indicating the developed lava mapping approach produces valuable results for monitoring volcanic hazards. Despite the lack of bands in infrared wavelengths, PlanetScope proves beneficial for the assessment of risk and near-real-time monitoring of active volcanoes due to its high spatial (3 m) and temporal resolution (mapping of all subaerial volcanoes on a daily basis).},
  language  = {en}
}
@article{LappeUllmannBachofer2022,
  author    = {Lappe, Ronja and Ullmann, Tobias and Bachofer, Felix},
  title     = {State of the Vietnamese coast — assessing three decades (1986 to 2021) of coastline dynamics using the Landsat archive},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {10},
  issn      = {2072-4292},
  doi       = {10.3390/rs14102476},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275281},
  year      = {2022},
  abstract  = {Vietnam's 3260 km coastline is densely populated, experiences rapid urban and economic growth, and faces at the same time a high risk of coastal hazards. Satellite archives provide a free and powerful opportunity for long-term area-wide monitoring of the coastal zone. This paper presents an automated analysis of coastline dynamics from 1986 to 2021 for Vietnam's entire coastal zone using the Landsat archive. The proposed method is implemented within the cloud-computing platform Google Earth Engine to only involve publicly and globally available datasets and tools. We generated annual coastline composites representing the mean-high water level and extracted sub-pixel coastlines. We further quantified coastline change rates along shore-perpendicular transects, revealing that half of Vietnam's coast did not experience significant change, while the remaining half is classified as erosional (27.7\%) and accretional (27.1\%). A hotspot analysis shows that coastal segments with the highest change rates are concentrated in the low-lying deltas of the Mekong River in the south and the Red River in the north. Hotspots with the highest accretion rates of up to +47 m/year are mainly associated with the construction of artificial coastlines, while hotspots with the highest erosion rates of -28 m/year may be related to natural sediment redistribution and human activity.},
  language  = {en}
}
@article{KoehlerBauerDietzetal.2022,
  author    = {Koehler, Jonas and Bauer, Andr{\´e} and Dietz, Andreas J. and Kuenzer, Claudia},
  title     = {Towards forecasting future snow cover dynamics in the European Alps — the potential of long optical remote-sensing time series},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {18},
  issn      = {2072-4292},
  doi       = {10.3390/rs14184461},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-288338},
  year      = {2022},
  abstract  = {Snow is a vital environmental parameter and dynamically responsive to climate change, particularly in mountainous regions. Snow cover can be monitored at variable spatial scales using Earth Observation (EO) data. Long-lasting remote sensing missions enable the generation of multi-decadal time series and thus the detection of long-term trends. However, there have been few attempts to use these to model future snow cover dynamics. In this study, we, therefore, explore the potential of such time series to forecast the Snow Line Elevation (SLE) in the European Alps. We generate monthly SLE time series from the entire Landsat archive (1985-2021) in 43 Alpine catchments. Positive long-term SLE change rates are detected, with the highest rates (5-8 m/y) in the Western and Central Alps. We utilize this SLE dataset to implement and evaluate seven uni-variate time series modeling and forecasting approaches. The best results were achieved by Random Forests, with a Nash-Sutcliffe efficiency (NSE) of 0.79 and a Mean Absolute Error (MAE) of 258 m, Telescope (0.76, 268 m), and seasonal ARIMA (0.75, 270 m). Since the model performance varies strongly with the input data, we developed a combined forecast based on the best-performing methods in each catchment. This approach was then used to forecast the SLE for the years 2022-2029. In the majority of the catchments, the shift of the forecast median SLE level retained the sign of the long-term trend. In cases where a deviating SLE dynamic is forecast, a discussion based on the unique properties of the catchment and past SLE dynamics is required. In the future, we expect major improvements in our SLE forecasting efforts by including external predictor variables in a multi-variate modeling approach.},
  language  = {en}
}
@article{KleemannZamoraVillacisChiluisaetal.2022,
  author    = {Kleemann, Janina and Zamora, Camilo and Villacis-Chiluisa, Alexandra Belen and Cuenca, Pablo and Koo, Hongmi and Noh, Jin Kyoung and F{\"u}rst, Christine and Thiel, Michael},
  title     = {Deforestation in continental Ecuador with a focus on protected areas},
  series = {Land},
  volume    = {11},
  journal   = {Land},
  number    = {2},
  issn      = {2073-445X},
  doi       = {10.3390/land11020268},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-262078},
  year      = {2022},
  abstract  = {Forest conservation is of particular concern in tropical regions where a large refuge of biodiversity is still existing. These areas are threatened by deforestation, forest degradation and fragmentation. Especially, pressures of anthropogenic activities adjacent to these areas significantly influence conservation effectiveness. Ecuador was chosen as study area since it is a globally relevant center of forest ecosystems and biodiversity. We identified hotspots of deforestation on the national level of continental Ecuador between 1990 and 2018, analyzed the most significant drivers of deforestation on national and biome level (the Coast, the Andes, The Amazon) as well as inside protected areas in Ecuador by using multiple regression analysis. We separated the national system of protected areas (SNAP) into higher and lower protection levels. Besides SNAP, we also considered Biosphere Reserves (BRs) and Ramsar sites. In addition, we investigated the rates and spatial patterns of deforestation in protected areas and buffer zones (5 km and 10 km outwards the protected area boundaries) using landscape metrics. Between 1990 and 2018, approximately 4\% of the accumulated deforestation occurred within the boundaries of SNAP, and up to 25.5\% in buffer zones. The highest rates of deforestation have been found in the 5 km buffer zone around the protected areas with the highest protection level. Protected areas and their buffer zones with higher protection status were identified as the most deforested areas among SNAP. BRs had the highest deforestation rates among all protected areas but most of these areas just became BRs after the year 2000. The most important driver of deforestation is agriculture. Other relevant drivers differ between the biomes. The results suggest that the SNAP is generally effective to prevent deforestation within their protection boundaries. However, deforestation around protected areas can undermine conservation strategies to sustain biodiversity. Actions to address such dynamics and patterns of deforestation and forest fragmentation, and developing conservation strategies of their landscape context are urgently needed especially in the buffer zones of areas with the highest protection status.},
  language  = {en}
}
@phdthesis{Kawohl2022,
  author    = {Kawohl, Alexander},
  title     = {The Petrology and Geochemistry of Igneous Dykes above the Temagami Anomaly (Ontario, Canada) and their Relationship to the 1.85 Ga Sudbury Impact},
  doi       = {10.25972/OPUS-27961},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-279617},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {The area northeast of Sudbury, Ontario, is known for one of the largest unexplained geophysical anomalies on the Canadian Shield, the 1,200 km2 Temagami Anomaly. The geological cause of this regional magnetic, conductive and gravity feature has previously been modelled to be a mafic-ultramafic body at relatively great depth (2-15 km) of unknown age and origin, which may or may not be related to the meteorite impact-generated Sudbury Igneous Complex in its immediate vicinity. However, with a profound lack of outcrops and drill holes, the geological cause of the anomaly remains elusive, a genetic link to the 1.85 Ga Sudbury impact event purely speculative. In search for any potential surface expression of the deep-seated cause of the Temagami Anomaly, this study provides a first, yet comprehensive petrological and geochemical assessment of exotic igneous dykes recently discovered in outcrops above, and drill cores into, the Temagami Anomaly. Based on cross-cutting field relations, petrographic studies, lithogeochemistry, whole-rock Nd-Sr-Pb isotope systematics, and U-Pb geochronology, it was possible to identify, and distinguish between, at least six different groups of igneous dykes: (i) Calc-alkaline quartz diorite dykes related to the 1.85 Ga Sudbury Igneous Complex (locally termed Offset Dykes); (ii) tholeiitic quartz diabase of the regional 2.22 Ga Nipissing Suite/Senneterre Dyke Swarm; (iii) calc-alkaline quartz diabase of the regional 2.17 Ga Biscotasing Dyke Swarm; (iv) alkaline ultrabasic dykes correlated with the 1.88-1.86 Ga Circum-Superior Large Igneous Province (LIP); and (v) aplitic dykes as well as (vi) a hornblende syenite, the latter two of more ambiguous age and stratigraphic position. The findings presented in this study - the discovery of three new Offset Dykes in particular - offer some unexpected insights into the geology and economic potential of one of the least explored areas of the world-class Sudbury Mining Camp as well as into the nature and distribution of both allochthonous and autochthonous impactites within one of the oldest and largest impact structures known on Earth. Not only do the geometric patterns of dyke (and breccia) distribution reaffirm previous notions of the existence of discrete ring structures in the sense of a ~200-km multi-ring basin, but they provide critical constraints as to the pre-erosional thickness and extent of the impact melt sheet, thus helping to identity new areas for Ni-Cu-PGE exploration. Furthermore, this study provides important insights into the pre-impact stratigraphy and the magmatic evolution of the region in general, which reveals to be much more complex, compositionally divers, and protracted than initially assumed. Of note is the discovery of rocks related to the 2.17 Ga Biscotasing and the 1.88-1.86 Ga Circum-Superior magmatic events, as these were not previously known to occur on the southeast margin of the Superior Craton. Shortly predating the Sudbury impact and being contemporaneous with ore-forming events at Thompson (Manitoba) and Raglan (Cape Smith), these magmatic rocks could provide the missing link between unusual mafic, pre-enriched, crustal target rocks, and the unique metal endowment of the Sudbury Impact Structure. The actual geological cause of the Temagami Anomaly remains open to debate and requires the downward extension of existing bore holes as well as more detailed geophysical investigations. The hypothesis of a genetic relationship between Sudbury impact event and Temagami Anomaly is neither borne out by any evidence nor particularly realistic, even in case of an oblique impact, and should thus be abandoned. It is instead proposed, based on circumstantial evidence, that the anomaly might be explained by an ultramafic complex of the 1.88-1.86 Ga Circum-Superior LIP.},
  subject      = {Impaktstruktur},
  language  = {en}
}
@article{KacicKuenzer2022,
  author    = {Kacic, Patrick and Kuenzer, Claudia},
  title     = {Forest biodiversity monitoring based on remotely sensed spectral diversity — a review},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {21},
  issn      = {2072-4292},
  doi       = {10.3390/rs14215363},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290535},
  year      = {2022},
  abstract  = {Forests are essential for global environmental well-being because of their rich provision of ecosystem services and regulating factors. Global forests are under increasing pressure from climate change, resource extraction, and anthropologically-driven disturbances. The results are dramatic losses of habitats accompanied with the reduction of species diversity. There is the urgent need for forest biodiversity monitoring comprising analysis on α, β, and γ scale to identify hotspots of biodiversity. Remote sensing enables large-scale monitoring at multiple spatial and temporal resolutions. Concepts of remotely sensed spectral diversity have been identified as promising methodologies for the consistent and multi-temporal analysis of forest biodiversity. This review provides a first time focus on the three spectral diversity concepts "vegetation indices", "spectral information content", and "spectral species" for forest biodiversity monitoring based on airborne and spaceborne remote sensing. In addition, the reviewed articles are analyzed regarding the spatiotemporal distribution, remote sensing sensors, temporal scales and thematic foci. We identify multispectral sensors as primary data source which underlines the focus on optical diversity as a proxy for forest biodiversity. Moreover, there is a general conceptual focus on the analysis of spectral information content. In recent years, the spectral species concept has raised attention and has been applied to Sentinel-2 and MODIS data for the analysis from local spectral species to global spectral communities. Novel remote sensing processing capacities and the provision of complementary remote sensing data sets offer great potentials for large-scale biodiversity monitoring in the future.},
  language  = {en}
}
@phdthesis{Hein2022,
  author    = {Hein, Niklas},
  title     = {Gesellschaftliche Implikationen nachhaltiger Nischenakteure - auf dem Weg in eine Postwachstumsgesellschaft?},
  edition   = {1. Auflage},
  publisher = {W{\"u}rzburg University Press},
  address   = {W{\"u}rzburg},
  isbn      = {978-3-95826-178-5},
  issn      = {0510-9833},
  doi       = {10.25972/WUP-978-3-95826-179-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-250737},
  school      = {W{\"u}rzburg University Press},
  pages     = {VIII, 222},
  year      = {2022},
  abstract  = {Die imperiale Lebensweise westlicher Industrienationen, die sich durch ein permanentes Streben nach Wirtschaftswachstum ausdr{\"u}ckt, bringt den Planeten an die Grenzen seiner Tragf{\"a}higkeit. In den letzten Jahren wurden jedoch - best{\"a}rkt durch die Weltwirtschaftskrise 2007/08 - Alternativen zum Modell des permanenten Wachstums immer popul{\"a}rer, die sich anstatt auf {\"o}konomischen Wohlstand vermehrt auf soziale und {\"o}kologische Belange des gesellschaftlichen Zusammenlebens fokussierten. Unter dem Begriff der Postwachstumsbewegung sammelten sich Ans{\"a}tze, Ideen und Akteure, die gemeinsam f{\"u}r eine Zukunft fernab jeglicher Wachstumszw{\"a}nge und innerhalb der planetaren Grenzen k{\"a}mpfen. Vor dem Hintergrund der zunehmenden sozialen und {\"o}kologischen Herausforderungen wurden nun erstmals sozial-{\"o}kologische Nischenakteure aus drei unterschiedlichen Bereichen der Postwachstumsbewegung gemeinsam in einem Forschungsvorhaben - unter besonderer Ber{\"u}cksichtigung gesellschaftlicher, organisatorischer und territorialer Einbettungsprozesse - untersucht. Eingebettet ist diese Untersuchung in den theoretisch-konzeptionellen Ansatz der sozial-{\"o}kologischen Transformation, deren inkrementeller Wandel mithilfe der Multi-Level-Perspektive beschrieben werden kann. Die Kombination dieses spezifischen theoretisch-konzeptionellen Ansatzes und der empirischen Erhebung ist das Alleinstellungsmerkmal der vorliegenden Untersuchung. Es zeigte sich, dass alle untersuchten Nischenakteure eine deutlich progressive Unternehmungsphilosophie vertreten, die h{\"a}ufig in einer Unternehmungsorganisation mit flachen Hierarchien und konsensbasierten Entscheidungsfindungen m{\"u}ndet. Besonders gesellschaftliche Einbettungsprozesse bedingen den Erfolg oder Misserfolg der Nischenentwicklung. Organisatorische Einbettung kommt derweil vor allem im Aufbau weitreichender Netzwerkstrukturen zum Tragen, die die Innovationsf{\"a}higkeit und Stabilit{\"a}t der Nische unterst{\"u}tzen. Eine starke territoriale Einbettung steigert den lokal-regionalen Einfluss der Nischeninnovationen und generiert R{\"u}ckhalt in der Bev{\"o}lkerung.},
  subject      = {Transformation},
  language  = {de}
}
@article{Hardaker2022,
  author    = {Hardaker, Sina},
  title     = {More Than Infrastructure Providers - Digital Platforms' Role and Power in Retail Digitalisation in Germany},
  series = {Tijdschrift voor Economische en Sociale Geografie},
  volume    = {113},
  journal   = {Tijdschrift voor Economische en Sociale Geografie},
  number    = {3},
  doi       = {10.1111/tesg.12511},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-287297},
  pages     = {310 -- 328},
  year      = {2022},
  abstract  = {Digital platforms, such as Amazon, represent the major beneficiaries of the Covid-19 crisis. This study examines the role of digital platforms and their engagement in digitalisation initiatives targeting (small) brick-and-mortar retailers in Germany, thereby contributing to a better understanding of how digital platforms augment, substitute or reorganise physical retail spaces. This study applies a mixed-method approach based on qualitative interviews, participant observation as well as media analysis. First, the study illustrates the controversial role of digital platforms by positioning themselves as supporting partners of the (offline) retailers, while simultaneously shifting power towards the platforms themselves. Second, digital platforms have established themselves not only as infrastructure providers but also as actors within these infrastructures, framing digital as well as physical retail spaces, inter alia due to their role as publicly legitimised retail advisers. Third, while institutions want to help retailers to survive, they simultaneously enhance retailers' dependency on digital platforms.},
  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{DongWurmTaubenboeck2022,
  author    = {Dong, Ruirui and Wurm, Michael and Taubenb{\"o}ck, Hannes},
  title     = {Seasonal and diurnal variation of land surface temperature distribution and its relation to land use/land cover patterns},
  series = {International Journal of Environmental Research and Public Health},
  volume    = {19},
  journal   = {International Journal of Environmental Research and Public Health},
  number    = {19},
  issn      = {1660-4601},
  doi       = {10.3390/ijerph191912738},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290393},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Dirscherl2022,
  author    = {Dirscherl, Mariel Christina},
  title     = {Remote Sensing of Supraglacial Lake Dynamics in Antarctica - Exploiting Methods from Artificial Intelligence for Derivation of Antarctic Supraglacial Lake Extents in Multi-Sensor Remote Sensing Data},
  doi       = {10.25972/OPUS-27950},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-279505},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {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.},
  subject      = {Optische Fernerkundung},
  language  = {en}
}
@article{AyalaCarrilloFarfanCardenasNielsenetal.2022,
  author    = {Ayala-Carrillo, Mariana and Farf{\´a}n, Michelle and C{\´a}rdenas-Nielsen, Anah{\´i} and Lemoine-Rodr{\´i}guez, Richard},
  title     = {Are wildfires in the wildland-urban interface increasing temperatures? A land surface temperature assessment in a semi-arid Mexican city},
  series = {Land},
  volume    = {11},
  journal   = {Land},
  number    = {12},
  issn      = {2073-445X},
  doi       = {10.3390/land11122105},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297308},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{AppelHardaker2022,
  author    = {Appel, Alexandra and Hardaker, Sina},
  title     = {Einzelhandel als Katalysator f{\"u}r nachhaltige urbane Radlogistik? - W{\"u}Livery, ein Fallbeispiel aus W{\"u}rzburg},
  series = {Standort},
  volume    = {46},
  journal   = {Standort},
  number    = {1},
  issn      = {1432-220X},
  doi       = {10.1007/s00548-021-00758-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-268437},
  pages     = {9-15},
  year      = {2022},
  abstract  = {Die Covid-19-Pandemie gilt in vielen gesellschaftlichen Teilbereichen als Beschleuniger f{\"u}r Transformationsprozesse. Auch im Bereich der Organisation urbaner Logistik und Einzelhandelslandschaften etablieren sich neue Akteur*innen und Funktionen. Logistiker*innen integrieren lokale Onlinemarktpl{\"a}tze in ihre Profile und der station{\"a}re Einzelhandel generiert Wettbewerbsf{\"a}higkeit gegen{\"u}ber großen Onlineh{\"a}ndler*innen {\"u}ber die Nutzung lokaler Radlogistiknetzwerke, mittels derer Lieferungen noch am Tag der Bestellung (Same-Day-Delivery) verteilt werden k{\"o}nnen. Damit leisten die involvierten Akteur*innen potenziell auch einen Beitrag zur Nachhaltigkeitstransformation im Bereich urbaner Logistiksysteme. Im Fokus steht das Fallbeispiel W{\"u}Livery, ein Kooperationsprojekt des Stadtmarketingvereins, der Wirtschaftsf{\"o}rderung, Radlogistiker*innen sowie Einzelh{\"a}ndler*innen in W{\"u}rzburg, welches w{\"a}hrend des zweiten coronabedingten Lockdowns im November 2020 umgesetzt wurde. Die entstehenden Dynamiken und Organisationsformen werden auf Basis von 11 Expert*inneninterviews dargestellt und analysiert. Es kann gezeigt werden, dass st{\"a}dtische Akteur*innen grundlegende Mediator*innen f{\"u}r Transformationsprozesse darstellen und Einzelh{\"a}ndler*innen und lokale Onlinemarktpl{\"a}tze als Katalysator*innen fungieren k{\"o}nnen. Das ist auch vor dem Hintergrund planerischer und politischer Kommunikationsprozesse zur Legitimation neuer Verkehrsinfrastrukturen nutzbar, da die einzelnen Akteur*innengruppen in Austausch kommen und ein gesteigertes Bewusstsein f{\"u}r die jeweiligen Bedarfe entsteht.},
  language  = {de}
}
@article{AnsahAbuKleemannetal.2022,
  author    = {Ansah, Christabel Edena and Abu, Itohan-Osa and Kleemann, Janina and Mahmoud, Mahmoud Ibrahim and Thiel, Michael},
  title     = {Environmental contamination of a biodiversity hotspot — action needed for nature conservation in the Niger Delta, Nigeria},
  series = {Sustainability},
  volume    = {14},
  journal   = {Sustainability},
  number    = {21},
  issn      = {2071-1050},
  doi       = {10.3390/su142114256},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297214},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}