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One of the largest hydraulic mines (1.6 km2) is located in California’s Sierra Nevada within the Humbug Creek watershed and Malakoff Diggins State Historic Park (MDSHP). MDSHP’s denuded and dissected landscape is composed of weathered Eocene auriferous sediments susceptible to chronic rill and gully erosion whereas block failures and debris flows occur in more cohesive terrain. This data release includes a 2014 digital elevation model (DEM), a study area boundary, and a geomorphic map. The 2014 DEM was derived from an available aerial LiDAR dataset collected in 2014 by the California Department of Conservation. The geomorphic map was derived for the study area from using a multi-scale spatial analysis. A topographic...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
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The Louisiana State Legislature created Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Grand Liard Marsh and Ridge Restoration (BA-68) project for 2016. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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The Louisiana Coastal Protection and Restoration Authority and the Natural Resource Damage Assessment (NRDA) develop restoration plans in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Lake Hermitage Marsh Creation– NRDA Early Restoration project 2020. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Cameron-Creole Maintenance (CS-04a) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project boundary....
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Pecan Island Terracing (ME-14) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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Reflectance data from HyMap™ were processed using the Material Identification and Characterization Algorithm (MICA), a module of the USGS PRISM (Processing Routines in IDL for Spectroscopic Measurements) software (Kokaly, 2011), programmed in Interactive Data Language (IDL; Harris Geospatial Solutions, Broomfield, Colorado). The HyMap reflectance data are provided and described in this data release. MICA identifies the spectrally predominant mineral(s) in each pixel of imaging spectrometer data by comparing continuum-removed spectral features in the pixel’s reflectance spectrum to continuum-removed absorption features in reference spectra of minerals, vegetation, water, and other materials. Linear continuum removal...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for wetlands throughout Collier county using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (15,223 points), NAIP-derived Normalized Difference Vegetation Index (2010), a 10 m lidar DEM from 2007, and a 10 m canopy surface model were used to generate a model of predicted bias across marsh, mangrove, and cypress habitats. The predicted bias was then subtracted from...
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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...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Fritchie Marsh Restoration (PO-06) project for 2016. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project...
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The Louisiana Coastal Protection and Restoration Authority and the Natural Resource Damage Assessment (NRDA) develop restoration plans in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Lake Hermitage Marsh Creation– NRDA Early Restoration project for 2018 and 2020. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Hopedale Hydrologic Restoration (PO-24) project for 2021. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...


map background search result map search result map Geomorphic Map Malakoff Diggins State Historic Park, California Mineral predominance map for Nabesna, Alaska, derived from imaging spectrometer reflectance data LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 Grand Liard Marsh and Ridge Restoration (BA-68): 2016 land-water classification Fritchie Marsh Restoration (PO-06): 2016 land-water classification LEAN-Corrected Collier County DEM for wetlands Lake Hermitage Marsh Creation– NRDA Early Restoration Project: 2018 land-water classification Lake Hermitage Marsh Creation– NRDA Early Restoration Project: 2020 land-water classification Final surface model (SRF) for basin A1 Digital elevation model (DEM) for basin A2 Digital terrain model (DTM) for basin B2 Vegetation classification model (Veg) for basin B2 Cameron-Creole Maintenance (CS-04a) 2018 land-water classification Pecan Island Terracing (ME-14): 2018 land-water classification 3. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 4.0, June 3rd, 2022) 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 Hopedale Hydrologic Restoration (PO-24): 2021 land-water classification Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 1.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 2.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 4.0, May 2023) Lake Hermitage Marsh Creation– NRDA Early Restoration Project: 2018 land-water classification Lake Hermitage Marsh Creation– NRDA Early Restoration Project: 2020 land-water classification Geomorphic Map Malakoff Diggins State Historic Park, California Final surface model (SRF) for basin A1 Vegetation classification model (Veg) for basin B2 Digital terrain model (DTM) for basin B2 Digital elevation model (DEM) for basin A2 Grand Liard Marsh and Ridge Restoration (BA-68): 2016 land-water classification Pecan Island Terracing (ME-14): 2018 land-water classification Hopedale Hydrologic Restoration (PO-24): 2021 land-water classification Fritchie Marsh Restoration (PO-06): 2016 land-water classification Cameron-Creole Maintenance (CS-04a) 2018 land-water classification LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 Mineral predominance map for Nabesna, Alaska, derived from imaging spectrometer reflectance data LEAN-Corrected Collier County DEM for wetlands 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 3. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 4.0, June 3rd, 2022) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 1.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 2.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 4.0, May 2023)