| Summary: | We developed a compound modeling approach that enabled us to refine the available evergreen forest category in the original Arctic Boreal Vulnerability Experiment (ABoVE) dataset (https://daac.ornl.gov/ABOVE/guides/Annual_Landcover_ABoVE.html) to include black and white spruce. The data is a geotiff (30 meter resolution) with 16 land cover classes. The published paper with the methods can be found at: https://doi.org/10.3390/f14081577. This archive includes 1984, 1994, 2003, 2014 and predicted 2024, 2034, 2044, and 2054. The year 2003 was used because 2004 had a large fire from that year already in the landsat imagery. Most years the fires show up the next year in the imagery. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas. These data will then be used to assess wildfire hazards and risk.
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