Data Transparency
Our predictive modeling pipeline is engineered exclusively on public geospatial and satellite datasets, ensuring that our methodology can be audited, reproduced, and scaled by the broader scientific community.
Hansen Global Forest Change
University of Maryland / GEE30m (resampled to 1km)
Baseline forest cover (treecover2000) and historical forest loss labels.
Open License
GFW Integrated Alerts
Global Forest WatchDaily/Weekly signals
Near-real-time deforestation evidence utilized as predictive features.
Open License
Sentinel-2 Multispectral
European Space Agency (ESA)10m-60m
Spectral bands (B2-B12) and derived indices including NDVI and NBR.
Open License
SRTM Digital Elevation
NASA / USGS30m
Terrain slope and accessibility pressure features derived from elevation.
Open License
Open Research Repository
The processed 1 km resolution analytical master tables for the K’Bang and Mang Yang pilot areas, which merge all aforementioned sources, are available directly within our GitHub repository.
Available for non-commercial academic research and replication.