{ "currentVersion": 10.91, "cimVersion": "2.9.0", "serviceDescription": "

Dates of Images:<\/SPAN><\/P>

Post-Event: Forthcoming<\/SPAN><\/P>

Pre-Event: June 19, 2025<\/SPAN><\/P>

Date of Next Image:<\/SPAN><\/P>

Unknown<\/SPAN><\/P>

Summary:<\/SPAN><\/P>

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. <\/SPAN><\/P>

NBR is defined mathematically as (NIR \u2013 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. <\/SPAN><\/P>

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. <\/SPAN><\/P>

Suggested Use:<\/SPAN><\/P>

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.<\/SPAN><\/P>

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:<\/SPAN><\/P>

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).<\/SPAN><\/P>

This dataset has not been validated by independent burn severity assessments.<\/SPAN><\/P>

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.<\/SPAN><\/P>

Satellite/Sensor:<\/SPAN><\/P>

Harmonized Landsat Sentinel-2 data: https://www.earthdata.nasa.gov/data/projects/hls<\/SPAN><\/P>

Resolution:<\/SPAN><\/P>

30 meters<\/SPAN><\/P>

Credits:<\/SPAN><\/P>

NASA LP DAAC: https://www.earthdata.nasa.gov/data/projects/hls<\/SPAN><\/P>

Esri REST Endpoint:<\/SPAN><\/P>

See URL section on right side of page<\/SPAN><\/P>

WMS Endpoint:<\/SPAN><\/P>

<\/P>

Data Download:<\/SPAN><\/P>

<\/DIV><\/DIV><\/DIV>", "mapName": "dnbr_hls", "description": "Dates of Images:Post-Event: ForthcomingPre-Event: June 19, 2025USGS National Elevation Dataset: U.S. Geological Survey, 20240416 (April 16, 2024), USGS 1/3 Arc Second n33w109 20240416: U.S. Geological SurveyDate of Next Image:UnknownSummary:The 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 \u2013 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.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: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/hlsUSGS elevation data: 1/3 arcsecond (roughly 10 m in this area of interest)Resolution:30 metersCredits:NASA LP DAAC: https://www.earthdata.nasa.gov/data/projects/hlsUSGS Elevation data: https://www.sciencebase.gov/catalog/item/662741a7d34ea70bd5efaee2Esri REST Endpoint:See URL section on right side of pageWMS Endpoint:Data Download:", "copyrightText": "NASA LP DAAC", "supportsDynamicLayers": true, "layers": [ { "id": 0, "name": "Binary slope and dNBR Exceedance", "parentLayerId": -1, "defaultVisibility": true, "subLayerIds": [ 1 ], "minScale": 0, "maxScale": 0, "type": "Group Layer", "supportsDynamicLegends": false }, { "id": 1, "name": "June 22, 2025", "parentLayerId": 0, "defaultVisibility": true, "subLayerIds": [ 2 ], "minScale": 0, "maxScale": 0, "type": "Group Layer", "supportsDynamicLegends": false }, { "id": 2, "name": "trout_fire_dnbr_slope_exceedance_20250622_final_v2", "parentLayerId": 1, "defaultVisibility": true, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Feature Layer", "geometryType": "esriGeometryPolygon", "supportsDynamicLegends": true }, { "id": 3, "name": "dNBR", "parentLayerId": -1, "defaultVisibility": false, "subLayerIds": [ 4, 5 ], "minScale": 0, "maxScale": 0, "type": "Group Layer", "supportsDynamicLegends": false }, { "id": 4, "name": "June 22, 2025", "parentLayerId": 3, "defaultVisibility": true, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Raster Layer", "supportsDynamicLegends": true }, { "id": 5, "name": "June 21, 2025", "parentLayerId": 3, "defaultVisibility": false, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Raster Layer", "supportsDynamicLegends": true } ], "tables": [], "spatialReference": { "wkid": 26713, "latestWkid": 26713, "xyTolerance": 0.001, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -5121000, "falseY": -9998000, "xyUnits": 10000, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 }, "singleFusedMapCache": false, "initialExtent": { "xmin": 198489.1265828719, "ymin": 3641790.0314393183, "xmax": 217825.31077413273, "ymax": 3655327.424000116, "spatialReference": { "wkid": 26713, "latestWkid": 26713, "xyTolerance": 0.001, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -5121000, "falseY": -9998000, "xyUnits": 10000, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 } }, "fullExtent": { "xmin": 197003.6818236162, "ymin": 3641137.995685173, "xmax": 218405.33922453935, "ymax": 3660367.2464817604, "spatialReference": { "wkid": 26713, "latestWkid": 26713, "xyTolerance": 0.001, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -5121000, "falseY": -9998000, "xyUnits": 10000, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 } }, "datesInUnknownTimezone": false, "minScale": 0, "maxScale": 0, "units": "esriMeters", "supportedImageFormatTypes": "PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP", "documentInfo": { "Title": "dnbr_hls", "Author": "", "Comments": "Dates of Images:Post-Event: ForthcomingPre-Event: June 19, 2025USGS National Elevation Dataset: U.S. Geological Survey, 20240416 (April 16, 2024), USGS 1/3 Arc Second n33w109 20240416: U.S. Geological SurveyDate of Next Image:UnknownSummary:The 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 \u2013 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.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: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/hlsUSGS elevation data: 1/3 arcsecond (roughly 10 m in this area of interest)Resolution:30 metersCredits:NASA LP DAAC: https://www.earthdata.nasa.gov/data/projects/hlsUSGS Elevation data: https://www.sciencebase.gov/catalog/item/662741a7d34ea70bd5efaee2Esri REST Endpoint:See URL section on right side of pageWMS Endpoint:Data Download:", "Subject": "Exceedance areas of Normalized Burn Ratio Difference (dNBR) and ground slope for Trout Fire, NM", "Category": "", "AntialiasingMode": "Fast", "TextAntialiasingMode": "Force", "Version": "2.9.0", "Keywords": "USA,New Mexico,NASA,NASA Disasters Program,Wildfires,NBR,dNBR,Normalized Burn Ratio" }, "supportsQueryDomains": true, "capabilities": "Query,Map,Data", "supportedQueryFormats": "JSON, geoJSON, PBF", "exportTilesAllowed": false, "referenceScale": 0.0, "datumTransformations": [ { "geoTransforms": [ { "wkid": 1693, "latestWkid": 1693, "transformForward": false, "name": "NAD_1927_To_WGS_1984_33" } ] }, { "geoTransforms": [ { "wkid": 1693, "latestWkid": 1693, "transformForward": true, "name": "NAD_1927_To_WGS_1984_33" } ] }, { "geoTransforms": [ { "wkid": 1693, "latestWkid": 1693, "transformForward": false, "name": "NAD_1927_To_WGS_1984_33" } ] }, { "geoTransforms": [ { "wkid": 1693, "latestWkid": 1693, "transformForward": true, "name": "NAD_1927_To_WGS_1984_33" } ] } ], "supportsDatumTransformation": true, "archivingInfo": {"supportsHistoricMoment": false}, "supportsClipping": true, "supportsSpatialFilter": true, "supportsTimeRelation": true, "supportsQueryDataElements": true, "maxRecordCount": 2000, "maxImageHeight": 4096, "maxImageWidth": 4096, "supportedExtensions": "WMSServer", "serviceItemId": "51604f81ceda461d9758b66b8ef9dfef" }