Sen4AgriNet is a harmonized multi-country, multi-temporal benchmark dataset for agricultural earth observation machine learning applications. Learn more here.
Agriculture
- Check out this workflow demo for generating cropland maps with machine learning and CropHarvest, a global dataset for crop-type classification. Link to end-to-end workflow resources included.
- This workflow generates automatic contours for agricultural parcels, given Sentinel-2 images. It uses Sentinel Hub to download the imagery and a ResUnet-a architecture.
- This tutorial provides step-by-step instructions on the way in which an open-source, generic GIS software package could be used to process geospatial data for agricultural data management.
