Presented at FOSS4G North America 2026 in Sacramento, California.
This talk explores how GIS, drought data, and satellite observations can be combined to monitor California rice production and identify early signals of supply change.
The workflow combines USDA NASS agricultural statistics, California DWR rice-field polygons, U.S. Drought Monitor data, Sentinel-2 optical indicators, and Sentinel-1 SAR observations processed with Google Earth Engine and Python.
A 2021–2023 case study highlights the sharp reduction in California rice acreage and production in 2022, while satellite indicators suggest that the rice fields actually planted followed broadly similar seasonal crop-condition patterns. The analysis motivates a framework that combines water availability, planted acreage, and in-season satellite signals for future GeoAI and machine-learning applications.
Event: FOSS4G North America 2026
Location: Sacramento, California
Tools: Python, GeoPandas, Google Earth Engine, Sentinel-1, Sentinel-2, USDA NASS, California DWR, U.S. Drought Monitor