Matthias Weigand

TL;DR: Using transfer learning capabilities of FCNs to slum mapping in various satellite images is found to be extremely valuable in retrieving information on small-scaled urban structures such as slum patches even in satellite images of decametric resolution.

TL;DR: In this paper, a methodology for delimiting morphological urban areas (MUAs) is presented, which can be seen as a territorially contiguous settlement area that can be distinguished from low density peripheral and rural hinterlands.

TL;DR: The capabilities of dual-polarized (HH/VV and VV/VH) X-band Synthetic Aperture Radar (SAR) from TerraSAR-X images for slum extent mapping using the Kennaugh element framework for image preprocessing is explored.

TL;DR: LUCAS in-situ data is a suitable source for reference information for large scale high resolution LC mapping using Sentinel-2 imagery, and existing sample selection approaches developed for Landsat imagery can be transferred to Sentinel- 2 imagery, achieving comparable semantic accuracies while increasing the spatial resolution.

TL;DR: It is argued that modern earth observation data can represent an important data source for research on environmental justice and health due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics.