Profile

Abstract

PhD student at RSC4Earth (University of Leipzig) working on the “Remote Sensing and Machine Learning” subproject of the Digital Forest project. My work consists on deriving reliable and interpretable forest stress indicators from satellite imagery by using state-of-art Machine Learning methods. I’ve worked on Remote Sensing, Photogrammetry, GIS and Data Science applied to Land Use Land Cover (LULC), agriculture and water resources. Lately, I’ve been working on the development of open-source software for geospatial data processing using cloud-based services such as Google Earth Engine (e.g. eemont, spectral, eeExtra).