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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Maximum Change Likelihood Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags... Bathymetry, Cape Cod National Seashore, Coastal Change Hazard Assessment, Coastal Fabric, Coastal Hazards, Coastal Vulnerability Index, Coastal and Marine Hazards Mission Area, Connecticut, Decision Tree Framework, Delaware, Elevation, Gateway National Recreation Area, George Washington Birthplace National Monument, High Tide Flooding, Interpretation, Land Cover, Landcover, Machine Learning, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Northeast US, Rhode Island, Sea Level Rise, Shoreline Change, St. Croix Island International Historic Site, Storm Overwash, Storm Recurrence, Supervised Classification, Support Vector Machine, Topography, Training Samples, U.S. Geological Survey, USGS, UVVR, Unvegetated-Vegetated Ratio, Virginia, Wave Power, Woods Hole Coastal and Marine Science Center, geoscientificInformation, marine geology, oceans, Fewer tags Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags... Bathymetry, Cape Cod National Seashore, Coastal Change Hazard Assessment, Coastal Fabric, Coastal Hazards, Coastal Vulnerability Index, Coastal and Marine Hazards Mission Area, Connecticut, Decision Tree Framework, Delaware, Elevation, Gateway National Recreation Area, George Washington Birthplace National Monument, High Tide Flooding, Interpretation, Land Cover, Landcover, Machine Learning, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Northeast US, Rhode Island, Sea Level Rise, Shoreline Change, St. Croix Island International Historic Site, Storm Overwash, Storm Recurrence, Supervised Classification, Support Vector Machine, Topography, Training Samples, U.S. Geological Survey, USGS, UVVR, Unvegetated-Vegetated Ratio, Virginia, Wave Power, Woods Hole Coastal and Marine Science Center, geoscientificInformation, marine geology, oceans, Fewer tags Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 – December 2020 These data were compiled for the creation of a continuous, transboundary land cover map of Bird Conservation Region 33, Sonoran and Mojave Deserts (BCR 33). Objective(s) of our study were to, 1) develop a machine learning (ML) algorithm trained to classify vegetation land cover using remote sensing spectral data and phenology metrics from 2013-2020, over a large subregion of the Sonoran and Mojave Deserts BCR, 2) Calibrate, validate, and refine the final ML-derived vegetation map using a collection of openly sourced remote sensing and ground-based ancillary data, images, and limited fieldwork, and 3) Harmonize a new transboundary classification system by expanding existing land cover mapping resources from the United... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Arizona, Baja California, Botany, California, Ecology, All tags... Forestry, Geography, Hermosillo, Information Sciences, Landsat images, Mexico, Mojave Desert, Phoenix, Remote Sensing, Sonora, Sonoran Desert, Southwest, US-Mexico Transboundary region, USGS Science Data Catalog (SDC), United States, artificial intelligence, biogeography, biota, classification, conservation, data release, desert ecosystems, ecosystem management, imageryBaseMapsEarthCover, land use and land cover, machine learning, modeling, natural resource management, phenology, phenology metrics, random forest model, remote sensing, remote sensing spectral data, time series datasets, transboundary, vegetation, Fewer tags Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Hazard Impact Type Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags... Bathymetry, Cape Cod National Seashore, Coastal Change Hazard Assessment, Coastal Fabric, Coastal Hazards, Coastal Vulnerability Index, Coastal and Marine Hazards Mission Area, Connecticut, Decision Tree Framework, Delaware, Elevation, Gateway National Recreation Area, George Washington Birthplace National Monument, High Tide Flooding, Interpretation, Land Cover, Landcover, Machine Learning, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Northeast US, Rhode Island, Sea Level Rise, Shoreline Change, St. Croix Island International Historic Site, Storm Overwash, Storm Recurrence, Supervised Classification, Support Vector Machine, Topography, Training Samples, U.S. Geological Survey, USGS, UVVR, Unvegetated-Vegetated Ratio, Virginia, Wave Power, Woods Hole Coastal and Marine Science Center, geoscientificInformation, marine geology, oceans, thbbt, Fewer tags Using Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018 Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (Rigge et al. 2020). We integrated remotely sensed data (250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) (https://earthexplorer.usgs.gov/)) with land cover, biogeophysical (i.e., soils, topography) and climate data into regression-tree software (Cubist®). We... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Arid, Arizona, Colorado, Ecology, Geography, All tags... Grass, LCMAP, Land Cover Monitoring Assessment & Projection, MTBS, Machine learning, Modeling, Monitoring Trends in Burn Severity, NLCD, National Land Cover Database, New Mexico, POLARIS Soils, PRISM Normals (1981 - 2010), Rangeland, Regression tree, Remote Sensing, Semiarid, Shrub, Spatial analysis, USGS Science Data Catalog (SDC), United States, Upper Colorado River Basin, Utah, West, Wyoming, geoscientificInformation, western United States, Fewer tags High-Resolution Land Cover Maps of Lāna‘i, Hawai‘i, 2020 - Class Probability Stack This raster stack contains 15 probability layers representing the pixel-level predicted probability of membership in each species-specific vegetation class from 0 to 1. These probability layers can be used to generate class membership uncertainty maps or probabilistic class cover maps from the model outputs. They provide additional information beyond the discrete categorial land cover assignments. Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Conservation, Hawaiian Islands, Hawai‘i, Invasive species, Land cover, All tags... Lāna‘i, Machine learning, Mapping, Pacific Islands, Remote sensing, Vegetation, biota, climatologyMeteorologyAtmosphere, Fewer tags Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Perpetual Hazards Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags... Bathymetry, Cape Cod National Seashore, Coastal Change Hazard Assessment, Coastal Fabric, Coastal Hazards, Coastal Vulnerability Index, Coastal and Marine Hazards Mission Area, Connecticut, Decision Tree Framework, Delaware, Elevation, Gateway National Recreation Area, George Washington Birthplace National Monument, High Tide Flooding, Interpretation, Land Cover, Landcover, Machine Learning, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Northeast US, Rhode Island, Sea Level Rise, Shoreline Change, St. Croix Island International Historic Site, Storm Overwash, Storm Recurrence, Supervised Classification, Support Vector Machine, Topography, Training Samples, U.S. Geological Survey, USGS, UVVR, Unvegetated-Vegetated Ratio, Virginia, Wave Power, Woods Hole Coastal and Marine Science Center, geoscientificInformation, marine geology, oceans, Fewer tags Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Fabric Dataset Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Acadia National Park, ArcGIS Pro, Arcpy, Autoclassification, Automation, All tags... Bathymetry, Cape Cod National Seashore, Coastal Change Hazard Assessment, Coastal Fabric, Coastal Hazards, Coastal Vulnerability Index, Coastal and Marine Hazards Mission Area, Connecticut, Decision Tree Framework, Delaware, Elevation, Gateway National Recreation Area, George Washington Birthplace National Monument, High Tide Flooding, Interpretation, Land Cover, Landcover, Machine Learning, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Northeast US, Rhode Island, Sea Level Rise, Shoreline Change, St. Croix Island International Historic Site, Storm Overwash, Storm Recurrence, Supervised Classification, Support Vector Machine, Topography, Training Samples, U.S. Geological Survey, USGS, UVVR, Unvegetated-Vegetated Ratio, Virginia, Wave Power, Woods Hole Coastal and Marine Science Center, geoscientificInformation, marine geology, oceans, Fewer tags