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Located in the northern tropical Pacific Ocean, Majuro is the capital of the Republic of the Marshall Islands. Majuro Atoll consists of a large, narrow landmass and a set of smaller perimeter islands surrounding a lagoon that is over 100 square miles in size. The waters surrounding the Majuro Atoll land areas are relatively shallow with poorly mapped bathymetry. However, the Pacific Ocean on the exterior of the coral atoll and the lagoon within its interior consist of deep bathymetry with steep slopes. The highest elevation of the Majuro Atoll is estimated at only 3-meters above sea level, which is the island community of Laura located on the western part of the atoll. At the eastern edge of the atoll lies the capital...
Categories: Data; Tags: 3D Elevation Program, 3DEP, American Society of Photogrammetry and Remote Sensing, Base Maps, Bathymetric, All tags...
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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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The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This dataset focuses on ecological change observation over ten years of field observation at 134 plots within two sites that are located in Southwestern of Wyoming, USA from 2008-2018. At sites 1 and 3, 134 long-term field observation plots were measured annually from 2008 to 2018. General plot locations were selected in 2006 using segments and spectral clusters on QuickBird imagery to identify the best locations for representing the variability of the entire site (one QuickBird image). Ground measurements were conducted using ocular measurements with cover was estimated from...
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A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.1 annual land cover products (1985–2019) for the Conterminous United States was conducted with an independently collected reference data set. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2018) to a reference sample of 24,971 randomly-selected Landsat resolution (30m x 30m) pixels. The interpreted land cover attributes were crosswalked to the LCMAP annual land cover classes: Developed, Cropland, Grass/Shrub, Tree Cover, Wetland, Water, Snow/Ice and Barren. Validation analysis directly compared reference labels with annual LCMAP land cover map attributes by...
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The LCMAP Hawaii Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products for Hawaii. The LCMAP Hawaii Reference Data Product includes the collection of an independent dataset of 600 30-meter by 30-meter plots across Hawaii. This dataset was collected via manual image interpretation to aid in validation of the land cover and land cover change products as well as area estimates. The LCMAP Reference Data Product collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across Hawaii from 2000–2019.
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The LCMAP Intensification Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Intensification Reference Data Product includes the collection of an independent dataset of 2,000 30-meter by 30-meter plots selected via stratified random sampling across the conterminous United States (CONUS). This dataset was collected via manual image interpretation to aid in validation of the land cover and land cover change products as well as area estimates. The LCMAP Intensification Reference Data Product collected variables related to primary and secondary land use, primary and secondary land cover(s),...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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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...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
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The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
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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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U.S. Geological Survey (USGS) scientists completed a multidisciplinary data collection effort during the week of October 21-25, 2019, using new technologies to map and validate bathymetry over a large stretch of the non-tidal Potomac River. The work was initiated as an effort to validate commercially-acquired topobathymetric light detection and ranging (lidar) data funded through a partnership between the USGS and the Interstate Commission on the Potomac River Basin (ICPRB). The goal was to compare airborne lidar data to bathymetric data collected through more traditional means (boat-based sonar, wading Real Time Kinematic Global Navigational Satellite System (RTK-GNSS) surveys) and through unmanned aerial systems...
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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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The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic...
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The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic...
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The National Park Service (NPS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic...


map background search result map search result map One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016 Switchgrass waterway buffers in the eastern Great Plains Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 Potomac River Topobathymetric Lidar Validation Survey Data Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 LCMAP Hawaii Reference Data Product land cover, land use and change process attributes National Park Service Thematic Burn Severity Mosaic in 2006 (ver. 6.0, January 2024) National Park Service Thematic Burn Severity Mosaic in 1996 (ver. 6.0, January 2024) National Park Service Thematic Burn Severity Mosaic in 1995 (ver. 6.0, January 2024) Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021 Monitoring Trends in Burn Severity Thematic Burn Severity Mosaic for 2021 (ver. 5.0, August 2023) 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 Potomac River Topobathymetric Lidar Validation Survey Data One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016 Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI LCMAP Hawaii Reference Data Product land cover, land use and change process attributes Switchgrass waterway buffers in the eastern Great Plains Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Non Sagebrush Shrub Fractional Component Time-Series Across the Western U.S. 1985-2021 Monitoring Trends in Burn Severity Thematic Burn Severity Mosaic for 2021 (ver. 5.0, August 2023) LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS National Park Service Thematic Burn Severity Mosaic in 1995 (ver. 6.0, January 2024) National Park Service Thematic Burn Severity Mosaic in 1996 (ver. 6.0, January 2024) National Park Service Thematic Burn Severity Mosaic in 2006 (ver. 6.0, January 2024)