Title:

Geospatial data for 2017-2018 wildland fires in the southwestern United States used for region-specific Rapid Assessment of Vegetation Condition after Wildfire (RAVG) models: burned area boundaries and burn indices derived from Landsat and Sentinel-2 satellite imagery

Author(s):

Reiner, Alicia L.; Baker, Craig R.; Wahlberg, Maximillian M.

Publication Year:

2022

How to Cite:

These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Reiner, Alicia L.; Baker, Craig R.; Wahlberg, Maximillian M. 2022. Geospatial data for 2017-2018 wildland fires in the southwestern United States used for region-specific Rapid Assessment of Vegetation Condition after Wildfire (RAVG) models: burned area boundaries and burn indices derived from Landsat and Sentinel-2 satellite imagery. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0019

Abstract:

These data were derived to develop fire effects models tailored to the southwest U.S. for use in the Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program at the USDA Forest Service Geospatial Technology and Applications Center (GTAC). They include a vector dataset comprising boundaries for the 23 fires in Arizona and New Mexico that were sampled for this project and raster datasets containing burn-related indices for each fire. The raster data were derived from satellite imagery (Landsat-8 Optical Line Imager (OLI) or Landsat-7 Enhanced Thematic Mapper Plus (ETM+), and Sentinel-2 Multispectral Imager (MSI)) and include six indices derived from each of four pairs of images for a total of 24 raster datasets for each fire or cluster of adjacent fires. The indices are the dNBR (delta normalized burn ratio), the RdNBR (relativized dNBR), and the relative burn ratio (RBR), each calculated with and without a scene-pair-specific offset value used to account for non-fire differences between the two scenes. The four image pairs consist of two Landsat pairs and two Sentinel-2 pairs. Each pair includes one pre-fire scene and one post-fire scene. For each sensor (Landsat and Sentinel-2), one pair captures change visible within a few weeks after fire containment and the other captures change visible approximately one year after the fire. All fires occurred in 2017 or 2018. Imagery acquisition dates are from 2015 to 2019.

Keywords:

fire effects; composite burn index; CBI; burn severity; basal area; canopy cover; RAVG; satellite indices; environment; imageryBaseMapsEarthCover; Ecology, Ecosystems, & Environment; Fire; Fire ecology; Fire effects on environment; Inventory, Monitoring, & Analysis; Natural Resource Management & Use; Forest management; Arizona; New Mexico; southwest United States

Related publications:

• Reiner, Alicia L.; Baker, Craig R.; Wahlberg, Maximillian M. 2022. Field and plot data for 2017-2018 wildland fires in the southwestern United States collected for Rapid Assessment of Vegetation Condition after Wildfire (RAVG) models: burn severity and stand characteristics. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0018
• Reiner, Alicia L.; Baker, Craig R.; Wahlberg, Maxillian M.; Rau, Benjamin M.; Birch, Joseph D. 2022. Region-specific remote-sensing models for predicting burn severity, basal area change, and canopy cover change following fire in the southwestern United States. Fire. 5: 137. https://doi.org/10.3390/fire5050137

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