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Full catalog/barc-thomasfire
barc-thomasfire·dataset

Thomas Fire Burn Severity Map (2017)

Burn Area Reflectance Classification for Thomas Fire
biosphere NASA VEDA COG
In plain English

What it measures. A map grading how badly the land was burned by California's 2017 Thomas Fire, from lightly scorched to severely burned.

How it's made. Derived from satellite reflectance using the Burn Area Reflectance Classification method from the federal Burned Area Emergency Response program.

How & where you'd use it. Guides emergency teams in planning erosion control, flood risk, and land recovery after the fire.

What's measured

barcthomasfire

Coverage & cadence

  • Time span2017-12-01 → 2017-12-31
  • Spatial extent-119.728, 34.196, -118.887, 34.727
  • FormatsCOG

What you can do with it

  • Map vegetation, forests and biomass
  • Monitor ecosystem productivity and carbon
  • Support habitat and biodiversity studies
Official description

Burn Area Reflectance Classification (BARC) from the Burned Area Emergency Response (BAER) program for Thomas fire, 2017

Get the data

veda_access.py
# NASA VEDA — open STAC API, anonymous (cloud-optimized GeoTIFFs)
from pystac_client import Client

cat = Client.open("https://openveda.cloud/api/stac")
col = cat.get_collection("barc-thomasfire")
items = list(col.get_items())          # browse the analysis-ready COGs
# open an asset with rioxarray:
# import rioxarray; da = rioxarray.open_rasterio(items[0].assets["cog_default"].href)
NASA VEDA is an open STAC catalog — browse and stream the cloud-optimized GeoTIFFs anonymously (no login).