Scientific Data · 2018 · 20 citations · 27 references
Natural ResourcesEnvironmental ManagementForestryForest EcologyForest InventoryForest ManagementForest GeographyForest PlanningForest Resource ManagementRemote Sensing For Forest InventoryVegetation IndicesVegetation MonitoringAncillary Data IntegrationForest Inventory MappingForest Management Decision Making Under UncertaintyForest Resource MappingForest Service ManagementForest Type MappingRandom Forest ClassificationSeasonal Time Series Models
Forests in the United States are managed by multiple public and private entities making harmonization of available data and subsequent mapping of management challenging. We mapped four important types of forest management, production, ecological, passive, and preservation, at 250-meter spatial resolution in the Southeastern (SEUS) and Pacific Northwest (PNW) USA. Both ecologically and socio-economically dynamic regions, the SEUS and PNW forests represent, respectively, 22.0% and 10.4% of forests in the coterminous US. We built a random forest classifier using seasonal time-series analysis of 16 years of MODIS 16-day composite Enhanced Vegetation Index, and ancillary data containing forest ownership, roads, US Forest Service wilderness and forestry areas, proportion conifer and proportion riparian. The map accuracies for SEUS are 89% (10-fold cross-validation) and 67% (external validation) and PNW are 91% and 70% respectively with the same validation. The now publicly available forest management maps, probability surfaces for each management class and uncertainty layer for each region can be viewed and analysed in commercial and open-source GIS and remote sensing software.
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