Satellite imagery + geospatial analysis
Remote Sensing Labs
Concise field guides for imagery reasoning, geospatial systems, and reproducible remote sensing workflows.
Rebuild in progress
Platform-agnostic remote sensing, not product-specific docs.
Remote Sensing Labs is being rebuilt around durable principles: imagery reasoning, applied workflows, data sources, and geospatial engineering patterns. Earth Engine remains as one implementation track, but the site is moving toward examples that translate across open-source tools and platforms.
Direction
Build remote sensing workflows that are not tied to one product.
Earth Engine Track
Keep the existing course useful while it remains the first complete implementation path.
02Core Concepts
Organize lessons around imagery, resolution, projections, visualization, indices, and modeling.
03Open Stack Migration
Add Python, STAC, COG, raster, vector, and notebook workflows as concept-level companions.
04Applied Imagery
Use public datasets first, then evaluate a small licensed VHR sample for proof-of-concept labs.