Data Sources

Annual tree cover loss (>30% canopy density) at 30 m resolution. On the map it's a pixel raster streamed live from GFW's tiles, coloured by density (amber → deep red) with a 2001–2025 timeline; also aggregated by region for the region-page chart. Tree cover loss is not always deforestation.

Concession boundaries for oil palm (1,855), pulpwood (295), and logging (259) in Indonesia.

688 WDPA protected areas and 42,027 KLHK forest moratorium (PIPPIB) polygons.

Indonesia's mangrove extent from satellite imagery (2020), a critical coastal habitat for proboscis monkeys, crocodiles, water birds, and fish nurseries.

Indonesia's peatland extent, a carbon-rich, fire-prone ecosystem and important habitat that vanishes when drained and burned.

Satellite-mapped mined land, the physical footprint of mining for ALL minerals, Aceh to Papua, peer-reviewed. This is our primary mining dataset (not permit boundaries).

Density areas of conservation-priority species (IUCN-threatened + flagship/endemic), all classes, derived from GBIF occurrence points (1990–present), NOT official range polygons. Density is weighted by natural-habitat cover (ESA WorldCover: forest, savanna, wetland, mangrove) with city points dropped, then contoured per island so each species stays on its island (a Sumatran tiger never bleeds into Java). Spans every region: Sundaland, Wallacea (anoa, maleo, Komodo), Papua (tree-kangaroo, echidna), and the sea & rivers. For cryptic species whose coordinates are withheld for protection (e.g. rhino), documented-range markers (IUCN/KLHK) are added, clearly flagged and not field records. IUCN's official range polygons are not used because their licence restricts redistribution.

Event-level flood/landslide records from the UNDRR mirror of DIBI. Location is the kabupaten centroid (an approximation), not the exact point.

Surface PM2.5 from the CAMS global atmospheric MODEL, not ground measurements. Shown as a colour field across Southeast Asia with 10 m wind particles (NOAA GFS) moving through it, because haze does not stop at borders: Riau's smoke reaches Kuala Lumpur and Singapore. The field is built on a schedule twice a day and served as a static file from the CDN, so the browser never calls a weather API. District points are NOT blended into the colour: they are the same CAMS model sampled at centroids, so mixing them in only produced a blob around each district centre without adding information. They remain the source of the per-region numbers in the popup. Opacity follows severity, so clean air is deliberately left transparent. Used because inland Riau, Jambi, and Central Kalimantan have almost no monitors — exactly where the smoke is thickest — so every station-based source is blank where it matters most. The trade-off: a 45 km cell smooths local peaks, so these values run LOWER than the air beside a burning block. The AQI shown alongside is computed by us from this PM2.5 using the official US EPA breakpoints (6 May 2024 revision); we do not take anyone's ready-made AQI. Values above AQI 500 are our own extension of the Hazardous segment, outside the range EPA defines, and are always flagged. The defensible number is µg/m³; the AQI is only its translation.

True-colour satellite mosaic for ONE chosen day, streamed straight from NASA GIBS tiles (keyless, not processed by us). Used to check land & forest fires: smoke and burn scars are visible to the naked eye, so a hotspot can be matched against what the sensor actually recorded. The product name shown on the map is the exact Worldview layer name, so the same day can be opened and compared in Worldview.

FIRMS thermal-anomaly detections for one chosen day, so a fire season can be replayed day by day — unlike the Hotspots (48h) layer, which is near-real-time only. Because GIBS publishes these vector tiles in EPSG:4326 only, this layer is drawn via the GIBS WMS as an image, and is therefore not clickable. A hotspot is an unverified heat detection, not proof of a fire nor of any party's involvement.

OpenStreetMap-derived place names, boundaries, roads, and coastlines served by NASA GIBS. Shown automatically with the NASA satellite imagery (not a separate layer): that imagery covers the basemap and its labels, so this overlay restores locational context. Orientation only — not an environmental data source, and not used in any calculation.

Province and district boundaries underpinning the map and aggregations.