Build, debug, and run Google Earth Engine Python and geemap workflows. Use for Earth Engine/geemap authorization, authentication, Cloud project setup, quotas, notebooks, browser map previews, Python scripts, 5,000+ official/community GEE dataset discovery, bilingual dataset selection by id/theme/task, dataset recommendation/comparison/verification, geospatial export, Sentinel/Landsat/MODIS/VIIRS/SAR/population collections, interactive maps, JavaScript-to-Python migration, local GIS integration, remote-sensing AI methods such as detection, segmentation, change detection, pixel regression, SAM, embeddings, vision-language models, QGIS GeoAI, or OpenGeo/opengeos patterns such as GeoAgent, GeoLibre, leafmap, anymap, GEE agents, and catalog-driven assistants. Prefer this skill for reproducible GEE/geemap setup, notebooks, batch exports, map-first AI workflows, GeoAI method execution, and auth/quota/project troubleshooting.
Use when Codex needs to detect, count, outline, segment, or localize visible targets in local or Google Earth Engine remote-sensing imagery and deliver CRS-aware GeoPackage or GeoJSON vectors, including fields, vehicles, vessels, tree crowns, buildings, roads, water bodies, or other objects.
Execute open-source GeoAI workflows from Qiusheng Wu's GeoAI with Python: acquire and inspect geospatial data, prepare training chips, train or apply models for recognition, detection, segmentation, translation, change detection, and pixel regression, use foundation models and embeddings, and run the same workflows in QGIS.