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These digital images were taken at select locations over the Potomac River using 3DR Solo unmanned aircraft systems (UAS) in October 2019. These images were collected for the purpose of evaluating UAS assessment of river habitat data such as water depth, substrate type, and water clarity. Each UAS was equipped with a Ricoh GRII digital camera for natural color photos, used to produce digital elevation models and ortho images, a MicaSense RedEdge multi-spectral camera that captures five specific bands of the visible spectrum (blue, green, red, rededge, and near-infrared), which can be used to classify vegetation, or FLIR Vue Pro R 640 13mm radiometric thermal camera that provides temperature data embedded in every...
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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
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LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
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These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
Tags: Arizona, Botany, Cloud Optimized GeoTIFF data, Colorado River, Ecology, All tags...
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LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
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LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
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This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
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These BioLake raster data provide global estimates (~10.0 x 12.4 km resolution) of twelve bioclimatic variables based on estimated lake temperature. Eleven of these twelve variables (BioLake01 - BioLake11) are estimated for each of three lake strata: lake mix (surface) layer, lake bottom, and total lake water column. These eleven variables correspond to CHELSA (Climatologies at high resolution for the earth's land surface areas) bioclimatic variables BIO1 - BIO11, except that these BioLake variables are based on lake water temperature and CHELSA BIO1 - BIO11 variables are based on air temperature. CHELSA BIO is also calculated a finer spatial resolution (~1 x 1 km). The twelfth variable (BioLake20; months with non-zero...
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Globally, groundwater dependent ecosystems (GDEs) are increasingly vulnerable to groundwater extraction and land use practices. Groundwater supports these ecosystems by providing inflow, which can maintain water levels, water temperature, and chemistry necessary to sustain the biodiversity that they support. Many aquatic systems receive groundwater as a portion of base flow, and in some systems (e.g., springs, seeps, fens) the connection with groundwater is significant and important to the system’s integrity and persistence. Groundwater management decisions for human use may not consider ecological effects of those actions on GDEs, which rely on groundwater to maintain ecological function. This disconnect between...
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In May 2021, the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey’s (USGS), Southwest Biological Science Center (SBSC) acquired airborne multispectral high resolution data for the Colorado River in Grand Canyon in Arizona, USA. The imagery data consist of four bands (Band 1 – red, Band 2 – green, Band 3 – blue, and Band 4 – near infrared) with a ground resolution of 20 centimeters (cm). These image data are available to the public as 16-bit GeoTIFF files, which can be read and used by most geographic information system (GIS) and image-processing software. The spatial reference of the image data are in the State Plane (SP) map projection using the central Arizona zone (FIPS 0202)...
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Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. The blue water evapotranspiration (BWET) raster dataset at 30-meter resolution is created to estimate agricultural irrigation water consumption. The dataset contains seasonal total (1 May to 30 September) BWET time series (1986 – 2020) for the croplands across the U.S. High Plains aquifer region. The BWET estimates are generated by integrating an energy-balance ET model (Operational Simplified Surface Energy Balance model) and a water-balance ET model (Vegetation ET model). BWET in croplands reflects crop consumptive use of irrigation water extracted from surface water and groundwater...
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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 Freshwater Introduction South of Highway 82 (ME-16) 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...
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This data set consists of digital data describing wetlands and uplands habitats for the Mississippi Coastal Improvements Program (MsCIP) area, consisting of Cat, Ship, Horn and Petit Bois Islands for the year 2020. Wetlands were classified using the Cowardin, et al., wetlands classification scheme to the level of freshwater and tidal, salinity modifiers. Uplands were classified using a customized classification scheme which can be cross-referenced to Anderson, et. al. For this dataset, upland dunes were delineated as areas at or above 1.524 meters (5 feet) as determined in the Lidar data that was referenced without modification for this classification. With this elevation criteria some delineated upland dune features...
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This data release includes 2022 data for the Louisiana Outer Coast Restoration Project for Whiskey Island. Specifically, this data release includes a detailed habitat map, general habitat map, and georeferenced imagery. These habitat maps are developed using the methods and classification scheme from Louisiana Coastal Protection and Restoration Authority’s (CPRA) Barrier Island Comprehensive Monitoring (BICM) program. For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (that is, dataset and recommended symbology). For more information about BICM...
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Wetland restoration efforts conducted by the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in Louisiana rely on monitoring efforts to determine the efficacy of these efforts. The Coastwide Reference Monitoring System (CRMS) was developed to assist in a multiple-reference approach that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling for monitoring. The CRMS program includes a suite of approximately 390 sites that encompass the range of hydrological and ecological conditions for each stratum. As part of CRMS, land and water classifications are created from Digital Orthophoto Quarter Quadrangles (DOQQs) approximately every three years at all CRMS sites. A DOQQ...
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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 persuant 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 Channel Armor Gap Crevasse (MR-06) project for 2016. This data set 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 Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic...
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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 Highway 384 Hydrologic Restoration (CS-21) project for 2015. 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 Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic...


map background search result map search result map Coastwide Reference Monitoring System (CRMS) 2015 land-water classifications Channel Armor Gap Crevasse (MR-06): 2016 Land-Water Classification Highway 384 Hydrologic Restoration (CS-21): 2015 land-water classification Louisiana Barrier Island Comprehensive Monitoring Program – 2015 habitat map, West Chenier Region (ver. 1.1, May 2020) Louisiana Barrier Island Comprehensive Monitoring Program – 2008 habitat map, East Chenier Region (ver. 1.1, May 2020) Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification February 2020 National Wetlands Inventory, Mississippi Barrier Islands Habitat Classification: (Cat Island, Ship Island, Petit Bois Island and Horn Island) Distribution Models Predicting Groundwater Influenced Ecosystems in the Northeastern United States Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Louisiana Outer Coast Restoration Project – 2022 habitat map, Whiskey Island Aerial imagery data of the Colorado River Corridor, Arizona - 2021 Seasonal Blue Water Evapotranspiration 1986 – 2020 for the Croplands in the High Plains Aquifer Region Channel Armor Gap Crevasse (MR-06): 2016 Land-Water Classification Louisiana Outer Coast Restoration Project – 2022 habitat map, Whiskey Island Highway 384 Hydrologic Restoration (CS-21): 2015 land-water classification Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Coastwide Reference Monitoring System (CRMS) 2015 land-water classifications Aerial imagery data of the Colorado River Corridor, Arizona - 2021 LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Seasonal Blue Water Evapotranspiration 1986 – 2020 for the Croplands in the High Plains Aquifer Region Distribution Models Predicting Groundwater Influenced Ecosystems in the Northeastern United States Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS