Using Satellite Data for Species Distribution Modeling with GRASS GIS and R

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Summary: Species distribution models (SDM) have traditionally used climatic data as predictors of habitat suitability for the target species. In this hands-on studio, we will explore the use of satellite data to derive relevant predictors. We will perform satellite data processing, from download to analysis, using GRASS GIS software functionality. Then, we’ll read our predictors within R and perform SDM, visualize and analyze results. Finally, we will write the output distribution maps back into GRASS.

About the speaker: Dr. Verónica Andreo is a biologist and holds a PhD in Biological Sciences and an MSc in Remote Sensing and GIS applications. She is a researcher for CONICET and a lecturer at Gulich Institute – Argentinian Space Agency (CONAE) in Córdoba, Argentina. Her research focuses on uncovering environmental drivers of vector-borne disease outbreaks. She is most interested in those environmental features that can be derived by means of satellite image analysis, remote sensing time series and GIS-based techniques.

Dr. Andreo is part of the GRASS GIS Development team and is chair of the GRASS GIS Project Steering Committee. She is a strong advocate for OSGeo and free and open source software for geo-spatial (FOSS4G). Among other things, she has served as Program Committee chair for FOSS4G 2021 and volunteered as a mentor for GRASS GIS in the Google Code-In contest introducing high school students into the Open Source world.