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Geomorphometry for Streams and Floodplains in the Chesapeake and Delaware Watersheds was generated as part of the project Quantifying Floodplain Ecological Processes and Ecosystem Services in the Delaware River Watershed funded through the William Penn Foundation' Delaware Watershed Research fund. This dataset contains geomorphometry for streams and floodplains in the Chesapeake and Delaware River watersheds. Geomorphometry is a quantitative representation of landscape surface form (e.g., channel width and depth) obtained from digital elevation models (DEMs). The dataset contains geomorphometry derived from running 3-m DEMs through the Floodplain and Channel Evaluation Tool (FACET) version 0.1.0. FACET generates...
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Geomorphometry for Streams and Floodplains in the Chesapeake and Delaware Watersheds was generated as part of the project Quantifying Floodplain Ecological Processes and Ecosystem Services in the Delaware River Watershed funded through the William Penn Foundation' Delaware Watershed Research fund. This dataset contains geomorphometry for streams and floodplains in the Chesapeake and Delaware River watersheds. Geomorphometry is a quantitative representation of landscape surface form (e.g., channel width and depth) obtained from digital elevation models (DEMs). The dataset contains geomorphometry derived from running 3-m DEMs through the Floodplain and Channel Evaluation Tool (FACET) version 0.1.0. FACET generates...
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Geomorphometry for Streams and Floodplains in the Chesapeake and Delaware Watersheds was generated as part of the project Quantifying Floodplain Ecological Processes and Ecosystem Services in the Delaware River Watershed funded through the William Penn Foundation' Delaware Watershed Research fund. This dataset contains geomorphometry for streams and floodplains in the Chesapeake and Delaware River watersheds. Geomorphometry is a quantitative representation of landscape surface form (e.g., channel width and depth) obtained from digital elevation models (DEMs). The dataset contains geomorphometry derived from running 3-m DEMs through the Floodplain and Channel Evaluation Tool (FACET) version 0.1.0. FACET generates...
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Polygon locations of fire perimeters in the Sky Island mountain ranges in the Madrean Archipelago Ecoregion of the southwestern United States and northern Mexico. These fires occurred from 1985 to 2011 and were mapped using Landsat satellite imagery.
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Corescan© Hyperspectral Core Imager Mark III (HCI-III) system data were acquired for hand samples, and subsequent billets made from the hand samples, collected during the U.S. Geological Survey (USGS) 2014, 2015, and 2016 field seasons in the Nabesna area of the eastern Alaska Range. This area contains exposed porphyry deposits and hand samples were collected throughout the region in support of the HyMap imaging spectrometer survey (https://doi.org/10.5066/F7DN435W) (Kokaly and others, 2017a). The HCI-III system consists of three different components. The first is an imaging spectrometer which collects reflectance data with a spatial resolution of approximately 500 nanometers (nm) for 514 spectral channels covering...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (Light Detection and Ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (light detection and ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (Light Detection and Ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (Light Detection and Ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (light detection and ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (light detection and ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired LiDAR (Light Detection and Ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. LiDAR data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
Snow covered area (SCA) observations from the Landsat Enhanced Thematic Mapper (ETM+) were used in combination with a distributed snowmelt model to estimate snow water equivalent (SWE) in the headwaters of the Rio Grande basin (3,419 km2) - a spatial scale that is an order of magnitude greater than previous reconstruction model applications. In this reconstruction approach, modeled snowmelt over each pixel is integrated over the time of ETM+ observed snow cover to estimate SWE. Considerable differences in the magnitude of SWE were simulated during the study. Basin-wide mean SWE was 2�6 times greater in April 2001 versus 2002. Despite these climatological differences, the model adequately recovered SWE at intensive...
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Switchgrass (Panicum virgatum L.), a highly productive perennial grass, has been recommended as one potential source for cellulosic biofuel feedstocks. Previous studies indicate that planting perennial grasses (e.g., switchgrass) in high topographic relief cropland waterway buffers can improve local environmental conditions and sustainability. The main advantages of this land management practice include (1) reducing soil erosion and improving water quality because switchgrass requires less tillage, fertilizers, and pesticides; and (2) improving regional ecosystem services (e.g., improving water infiltration, minimizing drought and flood impacts on production, and serving as carbon sinks). In this study, we mapped...
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These data show the spatial distribution of individual coastal ocean observing systems in the United States.
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The evapotranspiration (ET) datasets were created under contract for this study by the University of Idaho. A high-resolution remote sensing technique known as Mapping Evapotranspiration at High Resolution and Internalized Calibration (METRIC) was used to create estimates of the spatial distribution of ET. The METRIC technique uses thermal infrared Landsat imagery to quantify actual evapotranspiration at a 30-meter resolution that can be related to individual irrigated fields. Because evaporation uses heat energy, ground surfaces with large ET rates are left cooler as a result of ET than ground surfaces that have less ET. As a consequence, irrigated fields appear in the Landsat images as cooler than nonirrigated...
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In advance of design, permitting, and construction of a pipeline to deliver North Slope natural gas to out-of-state customers and Alaska communities, the Division of Geological & Geophysical Surveys (DGGS) has acquired lidar (light detection and ranging) data along proposed pipeline routes, nearby areas of infrastructure, and regions where significant geologic hazards have been identified. Lidar data will serve multiple purposes, but have primarily been collected to (1) evaluate active faulting, slope instability, thaw settlement, erosion, and other engineering constraints along proposed pipeline routes, and (2) provide a base layer for the state-federal GIS database that will be used to evaluate permit applications...
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Geomorphometry for Streams and Floodplains in the Chesapeake and Delaware Watersheds was generated as part of the project Quantifying Floodplain Ecological Processes and Ecosystem Services in the Delaware River Watershed funded through the William Penn Foundation' Delaware Watershed Research fund. This dataset contains geomorphometry for streams and floodplains in the Chesapeake and Delaware River watersheds. Geomorphometry is a quantitative representation of landscape surface form (e.g., channel width and depth) obtained from digital elevation models (DEMs). The dataset contains geomorphometry derived from running 3-m DEMs through the Floodplain and Channel Evaluation Tool (FACET) version 0.1.0. FACET generates...
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Geomorphometry for Streams and Floodplains in the Chesapeake and Delaware Watersheds was generated as part of the project Quantifying Floodplain Ecological Processes and Ecosystem Services in the Delaware River Watershed funded through the William Penn Foundation' Delaware Watershed Research fund. This dataset contains geomorphometry for streams and floodplains in the Chesapeake and Delaware River watersheds. Geomorphometry is a quantitative representation of landscape surface form (e.g., channel width and depth) obtained from digital elevation models (DEMs). The dataset contains geomorphometry derived from running 3-m DEMs through the Floodplain and Channel Evaluation Tool (FACET) version 0.1.0. FACET generates...
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Geomorphometry for Streams and Floodplains in the Chesapeake and Delaware Watersheds was generated as part of the project Quantifying Floodplain Ecological Processes and Ecosystem Services in the Delaware River Watershed funded through the William Penn Foundation' Delaware Watershed Research fund. This dataset contains geomorphometry for streams and floodplains in the Chesapeake and Delaware River watersheds. Geomorphometry is a quantitative representation of landscape surface form (e.g., channel width and depth) obtained from digital elevation models (DEMs). The dataset contains geomorphometry derived from running 3-m DEMs through the Floodplain and Channel Evaluation Tool (FACET) version 0.1.0. FACET generates...


map background search result map search result map Great Lakes, USA: water level observation network Evapotranspiration in the Upper Klamath Basin for October 2013 LaserProfiler Switchgrass waterway buffers in the eastern Great Plains High-resolution lidar data for infrastructure corridors, Nabesna Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Big Delta Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Tyonek Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Tyonek Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Talkeetna Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Talkeetna Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Wiseman Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Valdez Quadrangle, Alaska Mapped fire perimeters from the Sky Island Mountains of US and Mexico: 1985-2011 Geomorphometry for Hydrologic Unit 0205020506 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 02040103 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 02040201 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 0206000312 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 0206000203 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 0206000403 (FACET version 0.1.0) LaserProfiler High-resolution lidar data for infrastructure corridors, Nabesna Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Big Delta Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Tyonek Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Tyonek Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Talkeetna Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Talkeetna Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Wiseman Quadrangle, Alaska High-resolution lidar data for infrastructure corridors, Valdez Quadrangle, Alaska Evapotranspiration in the Upper Klamath Basin for October 2013 Mapped fire perimeters from the Sky Island Mountains of US and Mexico: 1985-2011 Geomorphometry for Hydrologic Unit 0205020506 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 02040103 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 02040201 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 0206000312 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 0206000203 (FACET version 0.1.0) Geomorphometry for Hydrologic Unit 0206000403 (FACET version 0.1.0) Great Lakes, USA: water level observation network Switchgrass waterway buffers in the eastern Great Plains