How severe was this wildfire's burn?
Analysis-ready products for actual events that this question maps to — open each in the catalog, or browse them on the NASA Disasters Portal.
Draw a rectangle to pick your area of interest, then see what NASA data covers it (live, here in your browser) or download a ready-to-run notebook with your AOI pre-filled. The notebook runs in any Python environment — it needs a free Earthdata Login to fetch the data.
-120.6, 38.5 → -120, 38.9 (Caldor Fire, California)Once a fire is out, recovery planning needs a map of *how badly* each patch burned — light scorch vs total stand-replacement. Satellites read that from how charred vegetation reflects infrared light, and it's the Disasters Portal's headline fire product.
Once a fire is out, recovery planning needs a map of how badly each patch burned — light scorch vs total stand-replacement. Satellites read that from how charred vegetation reflects infrared light, and it’s the Disasters Portal’s headline fire product.
What you can answer
- A burn-severity map. The Normalized Burn Ratio contrasts near-infrared (healthy vegetation reflects it) with shortwave-infrared (char and dry ground reflect it): NBR = (NIR − SWIR) / (NIR + SWIR). Burning drops NBR.
- Severity, not just extent. Difference pre- and post-fire NBR — dNBR = NBR_before − NBR_after. Bigger dNBR = more severe burn, binned into unburned / low / moderate / high classes.
- Knock-on effects — paired MODIS LST and NDVI differences show the heat and greenness change the fire left behind.
What you can NOT answer (easily)
- Cause or behaviour during the fire — this is an after-the-fact severity map, not fire spread.
- Under fresh smoke or cloud — use the first clear post-fire scene; smoke biases the bands.
- Soil vs canopy effects precisely — dNBR is a proxy; field plots (CBI) calibrate it.
How you’d approach it
Compute NBR on a clear pre-fire and post-fire Sentinel-2/HLS scene, difference them, threshold into severity classes, and clip to the perimeter. The notebook below scaffolds it. See the interactive NDVI guide — NBR is its close sibling. Supports the Recover phase of the NASA Disasters program.
Make it yours → Set the fire perimeter and the pre-fire and post-fire scene dates, and adjust the dNBR class thresholds to match local field calibration.
The thresholding a measurement into classes at the heart of this question — runnable on synthetic data, right here. The full earthaccess code template further down does it on real NASA data (needs an Earthdata login).