07-01, 14:00–18:00 (Europe/Tallinn), Room 301
In this workshop, we will explore the combined use of GRASS GIS, Python and R in a workflow of species distribution modeling (SDM). We will use a time series of satellite land surface temperature data to derive relevant predictors. The satellite data processing will be performed using GRASS GIS software functionality within a JupyterLab environment, taking advantage of the latest GRASS GIS Python features for Jupyter. Then, we’ll read our predictors within R and perform SDM, visualize and analyze results there. Finally, we'll exemplify how to write the output distribution maps back into GRASS for further analysis.
Find the workshop material at: https://github.com/veroandreo/grass_foss4geu_2024. We will run all online using The Whole Tale platform (and hopefully it will work ;-)).
Veronica Andreo holds a PhD in Biology and an MSc in Remote Sensing and GIS Applications. She is part of the GRASS Dev Team, and serves as PSC chair since 2021. She currently works at the Center for Geospatial Analytics, in North Carolina State University (USA).