ENV 320: Satellite Data for Agricultural and Environmental Economics
In this course, we use satellite data to monitor agriculture and the environment and evaluate policy. Specifically, we convert remote sensing data into information for policymakers to make informed decisions.
By the end of the session, participants will know how to leverage geospatial data to address critical environmental and agricultural challenges such as encroachment into protected areas and biodiversity loss.
Course Contents
Foundations
Workflows
Variables
Pitfalls and Remedies
Machine Learning
Deep Learning
Prerequisites
Participants are expected to have basic programming skills in R or Python. Skills in raster data processing would also be handy, but not explicitly necessary. All participants should have computers connected to the internet. Having a Google Earth Engine account would be beneficial for preprocessing and extraction of satellite images. Having QGIS will also be necessary for label data creation, though one can do this in GEE as well.
Dates and Schedule
The sessions will be held the winter semester of 2026/2027.
Tuesdays 12:00 - 14:00 CET
Thursdays 16:00 - 18:00 CET