@article{WeigandWurmDechetal.2019, author = {Weigand, Matthias and Wurm, Michael and Dech, Stefan and Taubenb{\"o}ck, Hannes}, title = {Remote sensing in environmental justice research—a review}, series = {ISPRS International Journal of Geo-Information}, volume = {8}, journal = {ISPRS International Journal of Geo-Information}, number = {1}, issn = {2220-9964}, doi = {10.3390/ijgi8010020}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-196950}, year = {2019}, abstract = {Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people's physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using "essentially aspatial" data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of 'big earth data' for future environmental justice analyses.}, 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{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{ReinersSobrinoKuenzer2023, author = {Reiners, Philipp and Sobrino, Jos{\´e} and Kuenzer, Claudia}, title = {Satellite-derived land surface temperature dynamics in the context of global change — a review}, series = {Remote Sensing}, volume = {15}, journal = {Remote Sensing}, number = {7}, issn = {2072-4292}, doi = {10.3390/rs15071857}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311120}, year = {2023}, abstract = {Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites.}, language = {en} } @article{FleuchausBlumWildeetal.2021, author = {Fleuchaus, Paul and Blum, Philipp and Wilde, Martina and Terhorst, Birgit and Butscher, Christoph}, title = {Retrospective evaluation of landslide susceptibility maps and review of validation practice}, series = {Environmental Earth Sciences}, volume = {80}, journal = {Environmental Earth Sciences}, issn = {1866-6280}, doi = {10.1007/s12665-021-09770-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-308911}, year = {2021}, abstract = {Despite the widespread application of landslide susceptibility analyses, there is hardly any information about whether or not the occurrence of recent landslide events was correctly predicted by the relevant susceptibility maps. Hence, the objective of this study is to evaluate four landslide susceptibility maps retrospectively in a landslide-prone area of the Swabian Alb (Germany). The predictive performance of each susceptibility map is evaluated based on a landslide event triggered by heavy rainfalls in the year 2013. The retrospective evaluation revealed significant variations in the predictive accuracy of the analyzed studies. Both completely erroneous as well as very precise predictions were observed. These differences are less attributed to the applied statistical method and more to the quality and comprehensiveness of the used input data. Furthermore, a literature review of 50 peer-reviewed articles showed that most landslide susceptibility analyses achieve very high validation scores. 73\% of the analyzed studies achieved an area under curve (AUC) value of at least 80\%. These high validation scores, however, do not reflect the high uncertainty in statistical susceptibility analysis. Thus, the quality assessment of landslide susceptibility maps should not only comprise an index-based, quantitative validation, but also an additional qualitative plausibility check considering local geomorphological characteristics and local landslide mechanisms. Finally, the proposed retrospective evaluation approach cannot only help to assess the quality of susceptibility maps and demonstrate the reliability of such statistical methods, but also identify issues that will enable the susceptibility maps to be improved in the future.}, language = {en} }