Andreas Rabe

TL;DR: An overview of the main characteristics and current status of the EnMAP mission is provided, which will contribute to the development and exploitation of spaceborne imaging spectroscopy applications by making high-quality data freely available to scientific users worldwide.

TL;DR: Experimental results clearly demonstrate that the generation of an SVM-based classifier system with RFS significantly improves overall classification accuracy as well as producer's and user's accuracies.

TL;DR: It is noted that chain classification can only be applied when land cover classes are well represented in the overlap area of neighboring Landsat scenes, but as long as this constraint is met, chain classification is a powerful approach for large area land cover classifications, especially in areas of varying training data availability.

TL;DR: An overview of the EnMAP-Box is given, typical workflows along an application example are explained, and the concept for making it a frequently used and constantly extended platform for imaging spectroscopy applications is exemplified.

TL;DR: In this article, the authors analyzed the potential of combining the large European-wide land survey LUCAS (Land Use/Cover Area frame Survey) and Landsat-8 data for mapping pan-European land cover and land use.