Two-volume book: Vol. I teaches geospatial Python from scratch (pandas, geopandas, rasterio, spatial statistics); Vol. II introduces DisSModel, our discrete spatial modeling framework. Work in progress, AI-assisted writing.
External executor registry for DisSModel — TOML-based, PR-reviewed.
Canonical reference outputs of TerraME 2.0.1 + LuccME 3.1 (21 labs, per-year goldens, fill datasets, timing), generated in Docker and pinned by SHA-256 for reproducible parity benchmarks.
Domain-decomposition engine (blocks + halo/ghost cells) for cellular automata on rasters larger than RAM, integrated with dissmodel.
Organization website for the DisSModel ecosystem.
Spatial data catalog and raster derivation pipeline for simulation workflows.
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