Vegetation characterization across scales – from citizen science photographs, to drone and satellite remote sensing acquisitions
At the example of my past research activities, this talk aims to demonstrate how Machine and Deep Learning are advancing our capabilities to understand the Earth´s flora in the context of various research questions.
This includes mapping the spatial distribution of plant species, tracking daily plant movements or revealing the global distribution of plant structural and biochemical properties. The presented methods and approaches highlight several common challenges of Machine Learning in the geosciences, such limited, sparse and spatially autocorrelated observations.
- Studied Environmental Sciences (Uni Freiburg)
- Since > 10 years freelancer in drone-based remote sensing (geocopter.eu)
- 2015-18 PhD in Remote Sensing and Geoecology (KIT, Karlsruhe)
- since 2018 PostDoc (KIT, Karlsruhe, Uni Leipzig)