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Filters: Tags: forest resources (X) > Types: OGC WMS Layer (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)

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The U.S. Geological Survey (USGS) computed rasters of pre-solved values for the watersheds draining to the pixel delineation point representing the watershed's percent forested land cover from the National Land Cover Dataset (NLCD) 2016 data (land cover values 41-43). These values, which cover the conterminous United States at a scale of 30m pixel size, will be served in the National StreamStats Fire-Hydrology application to describe delineated watersheds ( https://streamstats.usgs.gov/ ). The StreamStats application provides access to spatial analysis tools that are useful for water-resources planning and management, and for engineering and design purposes. The map-based user interface can be used to delineate...
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Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the central Cascade Mountain area, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest patches identified in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras...
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Mangrove species dominance on Pohnpei island, Federated States of Micronesia was modeled with two geospatial model types: k-nearest neighbor (KNN) and random forest (RF) and a common set of predictors. Dominant mangroves were defined as species comprising the largest basal area per field plot. The RF model predicted species dominance for each species separately, resulting in 8 maps (one for each species). The maps of Rhizophora stylosa and R. mucronata dominance were combined because these species were difficult to tell apart in field identification (resulting in the 7 maps presented here). The KNN model produced one map, which shows all species' dominance locations in one raster layer. The KNN model results were...
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The data are input data files to run the forest simulation model Landis-II for Isle Royale National Park. Files include: a) Initial_Comm, which includes the location of each mapcode, b) Cohort_ages, which includes the ages for each tree species-cohort within each mapcode, c) Ecoregions, which consist of different regions of soils and climate, d) Ecoregion_codes, which define the ecoregions, and e) Species_Params, which link the potential establishment and growth rates for each species with each ecoregion.
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Mangrove species dominance on Pohnpei island, Federated States of Micronesia was modeled with two geospatial model types: k-nearest neighbor (KNN) and random forest (RF) and a common set of predictors. Dominant mangroves were defined as species comprising the largest basal area per field plot. The KNN model produced one map, which shows all species' dominance locations in one raster layer. The KNN model results were the best based on field data and in field knowledge of the area. The KNN RStudio model and resulting map are shared here. The RF map and RStudio model can be found at https://doi.org/10.5066/P9JAE5JC.
    map background search result map search result map Isle Royale National Park: Input data to run Landis-II Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States Mangrove Species Dominance Map of Pohnpei, Federated States of Micronesia as Modeled by a K-Nearest Neighbor (KNN) Model Mangrove Species Dominance Map of Pohnpei, Federated States of Micronesia as Modeled by a Random Forest (RF) Model Isle Royale National Park: Input data to run Landis-II Mangrove Species Dominance Map of Pohnpei, Federated States of Micronesia as Modeled by a K-Nearest Neighbor (KNN) Model Mangrove Species Dominance Map of Pohnpei, Federated States of Micronesia as Modeled by a Random Forest (RF) Model Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA Precomputed Percent Forested-Area Rasters Derived from NLCD 2016 in Support of the StreamStats Fire-Hydrology Application, Conterminous United States