Exceedance areas of Normalized Burn Ratio Difference (dNBR) and ground slope for the California Fires May 2026

Dates of Images: Post-Event: May 24, 2026 Pre-Event: May 7, 2026 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Harmonized Landsat Sentinel-2 (HLS) dataset at 30m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Ground slopes were calculated using the slope algorithm in QGIS. This algorithm determined ground slopes in degrees by analyzing USGS 1/3 arcsecond (i.e. roughly 10m) digital elevation rasters in the NAD27 / UTM zone 13N projection. To produce the dNBR and ground slope exceedance map, dNBR data was filtered for values greater than 0.4 and ground slope data was filtered for areas greater than or equal to 23 degrees. These thresholds were defined by NASA subject matter expertise to indicate critical levels for enhanced debris flow risk where both are in exceedance. The locations where both dNBR and slope thresholds were exceeded were initially identified in a binary raster and then vectorized to polygons using 8-neighbor feature selection (data represented here). Suggested Use: dNBR is commonly used as a proxy to identify fire-affected areas. Higher dNBR value are statistically correlated with greater burn severity, where negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post-vegetation. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR will not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure), and the interpretation of dNBR values may vary widely based on the type of vegetation burned. This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: NASA Disasters/MSFC, USGS, ESA Copernicus Resolution: 10 meters Credits: NASA Disasters Program, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://maps.disasters.nasa.gov/ags03/services/NM_FIre_202506/dnbr_hls/MapServer/WMSServer

Dates of Images: Post-Event: May 20, 2026; May 19, 2026 Pre-Event: May 7, 2026; April 20, 2026 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Sentinel2- dataset at 10m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Check fire containment and image dates for further context on image timing. Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. Higher dNBR values represent a proxy for greater burn severity. Negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: Copernicus Sentinel-2 Resolution: 10 meters Credits: NASA/MSFC, USGS Service URL: See REST Endpoint to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_202605_FIRE_CA/202609_sentinel2_nbr/ImageServer/WMSServer

Dates of Images: Post-Event: May 20, 2026 Pre-Event: April 20, 2026 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Sentinel2- dataset at 10m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Check fire containment and image dates for further context on image timing. Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. Higher dNBR values represent a proxy for greater burn severity. Negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: Copernicus Sentinel-2 Resolution: 10 meters Credits: NASA/MSFC, USGS Service URL: See individual Layers. WMS Endpoint: See Descriptions of individual layers.

NOTE: this is exercise data and not representative of real events. The original data is from wildfires in New Mexico in June 2025. Dates of Images: Post-Event: May 23, 2026; May 22, 2026 Pre-Event: May 20, 2025 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Harmonized Landsat Sentinel-2 (HLS) dataset at 30m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Check fire containment and image dates for further context on image timing. Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. Higher dNBR values represent a proxy for greater burn severity. Negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: Harmonized Landsat Sentinel-2 data: https://www.earthdata.nasa.gov/data/projects/hls Resolution: 30 meters Credits: NASA LP DAAC: https://www.earthdata.nasa.gov/data/projects/hls Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=42dc8b50e387435ea4dc80a13c4ca9ca WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2604_202605_FIRE_CA/ex2604_hls_dnbr/MapServer/WMSServer

Date of Image(s): 12/18/2024; UTC: 183709 1/12/25; UTC: 183731 Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input imagers were generated from the ESA’s Sentinel-2’s Multi-Spectral imager. They were created from the Level 2A products which have been atmospherically corrected and orthorectified. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. For Sentinel 2, NIR = Band 8 and SWIR = Band 12. Using these definitions, the 20-meter resolution Band 8 and Band 12 images were used to generate these products. Sentinel-2 NBR methods: https://custom-scripts.sentinel-hub.com/custom-scripts/sentinel-2/nbr/ Finally dNBR is simply the difference between the pre-fire NBR and the post-fire NBR. Thus, we calculated dNBR as dNBR = NBR(12/18/2024) - NBR(01/12/2025). Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. More positive values in the dNBR analysis represent a proxy for greater burn severity. Negative values in dNBR represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity of the Los Angeles Fires at the time of posting this dataset should be strongly caveated. This is due to several dNBR Limitations: The spectral band selections used in the NBR and dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with the shortest time difference possible in the image pair; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: ESA Copernicus Sentinel-2 Resolution: 20 m in infrared bands Credits: Copernicus Sentinel-2 data was downloaded from the Sentinel-2 data explorer (https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-2) Data processed by Kyle Kabasares (ARC; kyle.k.kabasares@nasa.gov) References: Normalize Burn Ratio theory: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=3bc872886af24b799acd2ef881691a6a WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202501_FIRE_CA/2501_sentinel2_dnbr/ImageServer/WMSServer

Date of Image(s): 12/18/2024; UTC: 183709 1/12/25; UTC: 183731 Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input imagers were generated from the ESA’s Sentinel-2’s Multi-Spectral imager. They were created from the Level 2A products which have been atmospherically corrected and orthorectified. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. For Sentinel 2, NIR = Band 8 and SWIR = Band 12. Using these definitions, the 20-meter resolution Band 8 and Band 12 images were used to generate these products. Sentinel-2 NBR methods: https://custom-scripts.sentinel-hub.com/custom-scripts/sentinel-2/nbr/ Finally dNBR is simply the difference between the pre-fire NBR and the post-fire NBR. Thus, we calculated dNBR as dNBR = NBR(12/18/2024) - NBR(01/12/2025). Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. More positive values in the dNBR analysis represent a proxy for greater burn severity. Negative values in dNBR represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity of the Los Angeles Fires at the time of posting this dataset should be strongly caveated. This is due to several dNBR Limitations: The spectral band selections used in the NBR and dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with the shortest time difference possible in the image pair; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: ESA Copernicus Sentinel-2 Resolution: 20 m in infrared bands Credits: Copernicus Sentinel-2 data was downloaded from the Sentinel-2 data explorer (https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-2) Data processed by Kyle Kabasares (ARC; kyle.k.kabasares@nasa.gov) References: Normalize Burn Ratio theory: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=3bc872886af24b799acd2ef881691a6a WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202501_FIRE_CA/SENTINEL2_DNBR/ImageServer/WMSServer