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    BAER Soil Burn Severity Classification (Map Service)

    • gimi9.com
    • agdatacommons.nal.usda.gov
    • +4more
    Updated Apr 16, 2019
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    (2019). BAER Soil Burn Severity Classification (Map Service) [Dataset]. https://gimi9.com/dataset/data-gov_baer-soil-burn-severity-classification-map-service/
    Explore at:
    Dataset updated
    Apr 16, 2019
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This soil burn severity dataset is a compilation of all USFS BAER assessment data produced by the U.S. Forest Service in 2018. Each soil burn severity dataset was derived from satellite imagery, primarily Landsat 8 and Sentinel 2, and field validated by a Forest Service Burned Area Emergency Response (BAER) team. It is based upon an initial Burned Area Reflectance Classification (BARC). The BARC is created by analyzing pre-fire and post-fire satellite scenes and then calculating a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire and captures the combined effects of the fire to vegetation and soil components of the ecosytem. The preliminary BARC dataset was assessed by a Forest Service BAER team and modified, if necessary, based on field conditions.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2019). BAER Soil Burn Severity Classification (Map Service) [Dataset]. https://gimi9.com/dataset/data-gov_baer-soil-burn-severity-classification-map-service/

BAER Soil Burn Severity Classification (Map Service)

Explore at:
Dataset updated
Apr 16, 2019
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This soil burn severity dataset is a compilation of all USFS BAER assessment data produced by the U.S. Forest Service in 2018. Each soil burn severity dataset was derived from satellite imagery, primarily Landsat 8 and Sentinel 2, and field validated by a Forest Service Burned Area Emergency Response (BAER) team. It is based upon an initial Burned Area Reflectance Classification (BARC). The BARC is created by analyzing pre-fire and post-fire satellite scenes and then calculating a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire and captures the combined effects of the fire to vegetation and soil components of the ecosytem. The preliminary BARC dataset was assessed by a Forest Service BAER team and modified, if necessary, based on field conditions.

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