Dates of Images:

Date of Next Image:

Unknown

Summary:

The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument.

These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Landsat 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 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. A threshold of the dNBR raster flagged all the pixels that had values of -0.15 or less. This threshold was manually defined through different iterations in an effort to balance the detection of actual burned areas compared to agricultural activities and other unwanted change detections. The resulting vector was clipped to include detections that were near known fires to further reduce noise and false detections. This was done with cloud masked data, which automatically excluded areas obscured by clouds or thick smoke

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:

The True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred.

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.

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.

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.

This dataset has not been validated by independent burn severity assessments.

Satellite/Sensor:

Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager (OLI-2)

Resolution:

30 meters

Esri REST Endpoint:

See Layers below.

WMS Endpoint:

See individual pages of layers below.

Dates of Images:

Date of Next Image:

Unknown

Summary:

The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument.

These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Landsat 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 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. A threshold of the dNBR raster flagged all the pixels that had values of -0.15 or less. This threshold was manually defined through different iterations in an effort to balance the detection of actual burned areas compared to agricultural activities and other unwanted change detections. The resulting vector was clipped to include detections that were near known fires to further reduce noise and false detections. This was done with cloud masked data, which automatically excluded areas obscured by clouds or thick smoke

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:

The True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred.

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.

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.

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.

This dataset has not been validated by independent burn severity assessments.

Satellite/Sensor:

Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager (OLI-2)

Resolution:

30 meters

Esri REST Endpoint:

See Layers below.

WMS Endpoint:

See individual pages of layers below.