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DISASTERS_202506_FIRE_NM/2506_hls_dnbr (ImageServer)

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Service Description:

Dates of Images:

Post-Event: June 22, 2025; June 21, 2025

Pre-Event: June 19, 2024

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:

WMS Endpoint:



Name: DISASTERS_202506_FIRE_NM/2506_hls_dnbr

Description:

Dates of Images:

Post-Event: June 22, 2025; June 21, 2025

Pre-Event: June 19, 2024

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:

WMS Endpoint:



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 2.69494585235848E-4

Pixel Size Y: 2.6949458523584905E-4

Band Count: 1

Pixel Type: F64

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "", "help": "" }]}

Mensuration Capabilities: Basic

Inspection Capabilities:

Has Histograms: false

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Resampling: false

Copyright Text: NASA LP DAAC, USGS, FEMA (structures), UNM (roads), NASA Disasters Program

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: N/A

Max Values: N/A

Mean Values: N/A

Standard Deviation Values: N/A

Object ID Field: OBJECTID

Fields: Default Mosaic Method: Northwest

Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: 1000

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Statistics   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Query   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query GPS Info   Find Images   Image to Map   Map to Image   Measure from Image   Image to Map Multiray   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project