Disaster Data Releases from Planet Labs PBC

# Disaster Data Releases from Planet Labs PBC (llms.txt)

> Imagery from the Planet Crisis Response Program (https://www.planet.com/disasterdata/) for major disaster events —
> earthquakes, floods, storms, wildfires and human-made disasters — as a single browsable
> STAC / Portolan catalog on Source Cooperative. Each event is a self-contained sub-catalog
> with pre- and post-event high-resolution Cloud-Optimized GeoTIFFs (visual, pansharpened
> analytic, and usable-data masks) organised by affected location. Imagery © Planet Labs PBC,
> licensed CC-BY-NC-4.0 (non-commercial).

This file describes the catalog for machines and AI assistants. Built with Portolan
(https://portolan-sdi.org), a framework for cloud-native geospatial catalogs.

Base URL: https://data.source.coop/planet/disasterdata
Root catalog: https://data.source.coop/planet/disasterdata/catalog.json
Human landing page: https://source.coop/planet/disasterdata

## How to navigate

Nested STAC structure:
- `catalog.json` (this umbrella) → one `child` link per disaster event
- each event `<slug>/catalog.json` → pre-event and post-event sub-catalogs/collections,
  organised by affected location
- each collection has a `collection.json` (metadata), an `items.parquet` (STAC-GeoParquet
  index of its scenes), and per-scene Items whose assets are the COGs
- most levels carry their own `README.md` and `llms.txt` — read the event-level llms.txt for
  event-specific detail (sensors, dates, locations, queries)

## Events (each a self-contained sub-catalog)
- **venezuela-earthquake-2026-06-24/** — Planet Crisis Response — Venezuela Earthquake (2026)
  - catalog: https://data.source.coop/planet/disasterdata/venezuela-earthquake-2026-06-24/catalog.json
  - llms.txt: https://data.source.coop/planet/disasterdata/venezuela-earthquake-2026-06-24/llms.txt
- **philippines-earthquake-2026-06-08/** — Planet Crisis Response — Philippines Earthquake (2026)
  - catalog: https://data.source.coop/planet/disasterdata/philippines-earthquake-2026-06-08/catalog.json
  - llms.txt: https://data.source.coop/planet/disasterdata/philippines-earthquake-2026-06-08/llms.txt
- **hurricane-melissa-2025/** — Planet Crisis Response — Hurricane Melissa, Jamaica (2025)
  - catalog: https://data.source.coop/planet/disasterdata/hurricane-melissa-2025/catalog.json
  - llms.txt: https://data.source.coop/planet/disasterdata/hurricane-melissa-2025/llms.txt

## Items & assets

- One STAC Item per scene; the Item id is the Planet scene id.
- Per-scene asset keys (subset present per scene):
  - `visual` — true-colour RGB COG (uint8), ready for display
  - `analytic` — pansharpened multiband COG (uint16), for analysis
  - `udm2` — Usable Data Mask 2 (clear/cloud/shadow/haze + confidence)
  - `udm` — Unusable Data Mask (single band)
  - `thumbnail` — small PNG preview
- Asset hrefs are absolute public https URLs to COGs — stream byte ranges with /vsicurl,
  rio-tiler, rasterio or GDAL. No account or API key required.

## Data access

Query a collection's scenes with DuckDB (only the parquet is read):

```sql
INSTALL spatial; LOAD spatial; INSTALL httpfs; LOAD httpfs;
SELECT id, datetime, properties['eo:cloud_cover'] AS cloud
FROM read_parquet('https://data.source.coop/planet/disasterdata/<event-slug>/post-event/items.parquet');
```

Open a COG window without downloading the whole file:

```python
import rasterio
from rasterio.windows import from_bounds
url = "https://data.source.coop/planet/disasterdata/<event-slug>/post-event/<loc>/items/<scene>/<scene>_visual.tif"
with rasterio.open(url) as ds:
    rgb = ds.read(window=from_bounds(*bbox, ds.transform))
```

## Notes

- Non-commercial license: CC-BY-NC-4.0. Attribution: © Planet Labs PBC — Crisis Response Program.
- Contact: crisis-response@planet.com
- Pre-event imagery is for before/after comparison (a basemap or an earlier clean collect).