Projects
Terrestrial Plastic Detection (ongoing) – Research project on the potentials of detecting, differentiating and mapping terrestrial plastics from various Unoccupied Aerial Systems (UAS) using multi-spectral, thermal, LiDAR and hyper-spectral sensors. Forest Monitoring (ongoing) – Research project on the potentials of monitoring forests across Germany using Remote Sensing from Unoccupied Aerial Systems (UAS) and Earth Observation satellites PhD (ongoing) – Research project on the “Potentials of animal-environment interactions for remote sensing research”, supervised by Prof. Dr. Stefan Dech (Earth Observation Center at the German Aerospace Center, DLR) and Prof. Dr. Martin Wikelski (Max Planck Institute for Animal Behavior) MSc – Thesis: Schwalb-Willmann, J. (2018). A deep learning movement prediction framework for identifying anomalies in animal-environment interactions. Master’s, Julius Maximilians University Würzburg/German Aerospace Center (DLR). BSc – Thesis: Schwalb-Willmann, J. (2016). Comparison of different algorithms for calculating broadband albedo from AVHRR data. Bachelor’s, Ludwig Maximilians University Munich/German Aerospace Center (DLR). An Introduction to Spatial Data Analysis, a textbook for students, researchers or anyone else who want to learn working with spatial data from the ground up. Read more about it here or buy the book at Pelagic Publishing. Visit my GitHub profile for more details on my open source contributions: https://github.com/16EAGLEScientific
Writing
Open Source Software
moveVis, an R package providing tools to visualize movement data (e.g. from GPS tracking) and temporal changes of environmental data (e.g. from remote sensing) by creating video animations. A peer-reviewed open-access paper accompanying moveVis has been published in Methods in Ecology and Evolution.basemaps, an R package to download and cache spatial basemaps from open sources such as OpenStreetMap, Carto and Mapbox.RStoolbox, an R package providing a wide range of tools for every-day remote sensing processing needs (co-author).odcr, an R package that serves as an interface to the Open Data Cube.odcbox, a repository hosting everything needed to install an Open Data Cube instance as a docker container that serves a Jupyter notebook environment running both a Python kernel and an R kernel.getSpatialData, an R packaga making it easy to query, preview, download and preprocess multiple kinds of spatial data via R.