Planet makes available select imagery for major disaster events, including major earthquakes, floods, storms, wildfires, and human-made disasters. These are available here in a STAC Catalog under a CC-BY-NC license. See the Planet Disaster Data page for more information.
You are looking at a Portolan / STAC collection (collection.json, STAC 1.1.0, Portolan profile v0.1.0) — inside Disaster Data Releases from Planet Labs PBC: Planet Crisis Response imagery for major disaster events.
Very-high-resolution (~0.7 m) SkySat imagery acquired 29 July 2026, after the Gironde/Landes fire was contained, over the Le Porge → Arès pine-forest burn zone on the north shore of the Arcachon Basin. Visual and pansharpened products for detailed burn-severity and damage assessment. 3 scenes; each Item carries the available visual, pansharpened assets.
Everything is plain HTTPS — no credentials, no signing, no request-payer.
Two caveats worth knowing before you write a fetch loop:
Python-urllib User-Agent. Send a
browser or curl UA if you use urllib; requests, curl, GDAL/rasterio, rio-tiler and
DuckDB all work as-is.aws s3 ls; navigate the STAC
links instead — every object links to its parent, children and items.Each collection publishes a STAC-GeoParquet mirror of its items — one row per item, with geometry and all properties. Query it directly, no download:
That is almost always faster than walking the rel:"item" links, which are there for
STAC clients and for humans clicking through the browser.
Every raster is a cloud-optimized GeoTIFF, so read the window you need rather than the file:
Asset keys on each item (visual used above):
visual — Visual (true-colour RGB) ortho COG (roles: data, visual)pansharpened — Pansharpened multiband ortho COG (roles: data)file:size and file:checksum (sha256 multihash, 1220-prefixed) so a download can be verified.proj:code.