Not just crop or forest: building an integrated land cover map for agricultural and natural areas

crossref(2022)

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摘要
Abstract. Due to our increasing understanding of the role the surrounding landscape plays in ecological processes, a detailed characterization of land cover, including both agricultural and natural habitats, is ever more important for both researchers and conservation practitioners. Unfortunately, in the United States, different types of land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this data gap and reduce duplicative efforts in geospatial processing, we merged two major datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce an integrated land cover map. Our workflow leveraged strengths of the NVC and the CDL to produce detailed rasters comprising both agricultural and natural land-cover classes. We generated these maps for each year from 2012–2021 for the conterminous United States, quantified agreement between input layers and accuracy of our merged product and published the complete workflow necessary to update these data. In our validation analyses, we found that approximately 5.5 % of NVC agricultural pixels conflicted with the CDL, but we resolved most of these conflicts based on surrounding agricultural land, leaving only 0.6 % of agricultural pixels unresolved in our merged product. These ready-to-use rasters characterizing both agricultural and natural land cover will be widely useful in environmental research and management.
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