Stepwise Refinement Of Low Resolution Labels For Earth Observation Data: Part 2

Abstract

This paper describes the contribution of the DLR team ranking 3 rd in Track 1 of the 2020 IEEE GRSS Data Fusion Contest, with results ranking 2 nd in Track 2 of the same contest are reported in a companion paper. The classifications are based on refinements of low-resolution MODIS labeling on available higher resolution Sentinel-1 and Sentinel-2 data. Results are initialized with a handcrafted decision tree integrating output from a random forest classifier, and subsequently boosted by detectors for specific classes.