TY - JOUR A1 - Senaratne, Hansi A1 - Mühlbauer, Martin A1 - Kiefl, Ralph A1 - Cárdenas, Andrea A1 - Prathapan, Lallu A1 - Riedlinger, Torsten A1 - Biewer, Carolin A1 - Taubenböck, Hannes T1 - The Unseen — an investigative analysis of thematic and spatial coverage of news on the ongoing refugee crisis in West Africa JF - ISPRS International Journal of Geo-Information N2 - The fastest growing regional crisis is happening in West Africa today, with over 8 million people considered persons of concern. A culmination of identity politics, climate-driven disasters, and extreme poverty has led to this humanitarian crisis in the region and is exacerbated by a lack of political will and misplaced media attention. The current state of the art does not present sufficient investigations of the thematic and spatial coverage of news media of this crisis in this region. This paper studies the spatial coverage of this crisis as reported in the media, and the themes associated with those locations, based on a curated dataset. For the time frame 12 March to 15 September 2021, 2017 news articles related to the refugee crisis in West Africa were examined and manually coded based on (1) the geographical locations mentioned in each article; (2) the themes found in the articles in reference to a location (e.g., Relocation of people in Abuja). The dataset introduces a thematic dimension, as never achieved before, to the conflict-ridden areas in West Africa. A comparative analysis with UNHCR (United Nations High Commissioner for Refugees) data showed that 96.8% of refugee-related locations in West Africa were not covered by news during the considered time frame. Contrastingly, 80.4% of locations mentioned in the news do not appear in the UNHCR repository. Most news articles published during this time frame reported on Development aid or Political statements. Linear multiple regression analysis showed GDP per capita and political stability to be among the most influential determinants of news coverage. KW - West African refugee crisis KW - news media reporting KW - spatio-thematic coverage Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313607 SN - 2220-9964 VL - 12 IS - 4 ER - TY - JOUR A1 - Dong, Ruirui A1 - Wurm, Michael A1 - Taubenböck, Hannes T1 - Seasonal and diurnal variation of land surface temperature distribution and its relation to land use/land cover patterns JF - International Journal of Environmental Research and Public Health N2 - 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. KW - surface urban heat island (SUHI) KW - land use/cover pattern (LUCP) KW - land surface temperature (LST) KW - seasonal KW - diurnal Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-290393 SN - 1660-4601 VL - 19 IS - 19 ER - TY - JOUR A1 - Weigand, Matthias A1 - Wurm, Michael A1 - Dech, Stefan A1 - Taubenböck, Hannes T1 - Remote sensing in environmental justice research—a review JF - ISPRS International Journal of Geo-Information N2 - 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. KW - satellite remote sensing KW - review KW - environmental justice KW - big earth data KW - urban environments Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-196950 SN - 2220-9964 VL - 8 IS - 1 ER - TY - JOUR A1 - Müller, Konstantin A1 - Leppich, Robert A1 - Geiß, Christian A1 - Borst, Vanessa A1 - Pelizari, Patrick Aravena A1 - Kounev, Samuel A1 - Taubenböck, Hannes T1 - Deep neural network regression for normalized digital surface model generation with Sentinel-2 imagery JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing N2 - In recent history, normalized digital surface models (nDSMs) have been constantly gaining importance as a means to solve large-scale geographic problems. High-resolution surface models are precious, as they can provide detailed information for a specific area. However, measurements with a high resolution are time consuming and costly. Only a few approaches exist to create high-resolution nDSMs for extensive areas. This article explores approaches to extract high-resolution nDSMs from low-resolution Sentinel-2 data, allowing us to derive large-scale models. We thereby utilize the advantages of Sentinel 2 being open access, having global coverage, and providing steady updates through a high repetition rate. Several deep learning models are trained to overcome the gap in producing high-resolution surface maps from low-resolution input data. With U-Net as a base architecture, we extend the capabilities of our model by integrating tailored multiscale encoders with differently sized kernels in the convolution as well as conformed self-attention inside the skip connection gates. Using pixelwise regression, our U-Net base models can achieve a mean height error of approximately 2 m. Moreover, through our enhancements to the model architecture, we reduce the model error by more than 7%. KW - Deep learning KW - multiscale encoder KW - sentinel KW - surface model Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349424 SN - 1939-1404 VL - 16 ER -