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These datasets provide early estimates of 2024 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from April to late June. Typically, the EAG estimates are publicly released within 7-13 days of the latest satellite observation used for that version. Each weekly release contains five fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) Field Brome (Bromus arvensis); 4) medusahead (Taeniatherum caput-medusae); and 5) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory,...
The USGS Forecasting Scenarios of Land-use Change (FORE-SCE) model was used to produce an agricultural biofuel scenarios for the Northern Glaciated Plains, from 2012 to 2030. The modeling used parcel data from the USDA's Common Land Unit (CLU) data set to represent real, contiguous ownership and land management units. A Monte Carlo approach was used to create 50 unique replicates of potential landscape conditions in the future, based on a agricultural scenario from the U.S. Department of Energy's Billion Ton Update. The data are spatially explicit, covering the entire Northern Glaciated Plains ecoregions (an EPA Level III ecoregion), with a spatial resolution of 30-meters and 22 unique land-cover classes (including...
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: FORE-SCE,
Great Plains,
Land Cover,
Minnesota,
Model,
The study's goal was to downscale 2013 250-m expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) to 30 m (Gu, Y. and Wylie, B.K., 2015, Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations, Remote Sensing of Environment, v. 171, p. 291-298)using 2013 Landsat 8 data. The eMODIS NDVI was downscaled for four periods: mid spring, early summer, late summer and mid fall. The objective was to capture phenologies during periods that correspond to 1) annual grass growth, 2) annual grass senescence, 3) the optimal NDVI profile separation between sagebrush and other shrubs in the region, and...
This dataset is the third (circa 2013) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Gambia,
Land Cover,
Land Use,
biota,
land cover,
Landsat classification of surface water for multiple seasons to monitor inundation of playa wetlands
To improve understanding of the distribution of important, ephemeral wetland habitats across the Great Plains, we documented the occurrence and distribution of surface water in playa wetland complexes for four different years across the Great Plains Landscape Conservation Cooperative (GPLCC) region. Years of research on playas has yielded multiple mechanisms and projections for sub-regions of the LCC area, but a complete, region-wide inventory and assessment has not been completed. This information is important because it informs habitat and population managers about the timing and location of habitat availability. Data representing the presence of water, percent of the area inundated with water, and the spatial...
Categories: Data;
Tags: Great Plains,
Landsat,
Remote Sensing,
USGS Science Data Catalog (SDC),
imageryBaseMapsEarthCover,
This is a collection of data tables supporting the LCMAP CONUS Geographic Assessment v1.0. The data used to generate these tables come from the USGS LCMAP reference dataset and the map products released by LCMAP. Tables include annual land cover class composition and annual rate of land cover change metrics developed with a post-stratified estimator. Other tables including annual gross change of specific types of land covers, cumulative metrics of overall geographic footprint of change, frequency of overall geographic footprint of change, overall area estimates of specific class changes, and all unique changes in land cover classes. All tables cover the time period 1985-2016. All values in these tables are presented...
The surface psychrometric constant (spc) is a key model parameter in actual evapotranspiration modeling using the Operational Simplified Surface Energy Balance (SSEBop) model for establishing model boundary limits for the dry/bare and wet/vegetated surface conditions. The inverse of the constant (1/spc) represents the temperature difference (dT) between the bare/dry surface and the air temperature at the canopy level. The main output of the SSEBop model is an ET fraction (0-1) and, when combined with reference (“maximum”) ET, produces an actual ET estimate from satellite-observed land surface temperature. This dT is determined using net radiation inputs under gray-sky radiations from the ERA-5 datasets, i.e., Surface...
LANDFIRE's (LF) Annual Disturbance products provide temporal and spatial information related to landscape change. Annual Disturbance depicts areas of 4.5 hectares (11 acres) or larger that have experienced a natural or anthropogenic landscape change (or treatment) within a given year. For the creation of the Annual Disturbance product, information sources include national fire mapping programs such as Monitoring Trends in Burn Severity (MTBS), Burned Area Reflectance Classification (BARC) and Rapid Assessment of Vegetation Condition after Wildfire (RAVG), 18 types of agency-contributed "event" perimeters (see LF Public Events Geodatabase), and remotely sensed Landsat imagery. To create the LF Annual Disturbance...
LANDFIRE's (LF) 2022 Canopy Base Height (CBH) supplies information used in fire behavior models to determine the critical point at which a surface fire will transition to a crown fire in conjunction with other environmental factors, such as wind speed and moisture content. CBH data are continuous from 0 to 9.9 meters (to the nearest 0.1m) and describe the lowest point in a stand where there is enough available fuel (0.25in diameter) to propagate fire vertically through the canopy. Critical CBH is defined as the lowest point at which the Canopy Bulk Density (CBD) is .012kg m-3. Under different scenarios of disturbance and based on previous research incorporating plot-level CBH calculations, CBH for disturbed areas...
LANDFIRE (LF) 2022 Fuel Vegetation Height (FVH) represents the LF Existing Vegetation Height (EVH) product, modified to represent pre-disturbance EVH in areas where disturbances have occurred over the past 10 years. EVH is mapped as continuous estimates of canopy height for tree, shrub, and herbaceous lifeforms with a potential range of 0-100m. Continuous EVH values are binned to align with fuel model assignments when creating FVH. FVH 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 FVH is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. LF 2022 Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2013 to 2022. FDist is created from LF 2022 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Canopy Cover (CC), Canopy Height (CH), Canopy Bulk Density (CBD), Canopy Base Height (CBH),...
LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Height (EVH) represents the average height of the dominant vegetation for a 30-m cell. EVH is produced separately for tree, shrub, and herbaceous lifeforms using training data depicting the weighted average height by species cover and Existing Vegetation Type (EVT) lifeform. Decision tree models using field reference data, lidar, and Landsat are developed separately for each lifeform, then lifeform specific height class layers are merged along with land cover into a single EVH product based on the dominant lifeform of each pixel. EVH ranges are continuous for the herbaceous lifeform category ranging from 0.1 to 1 meter with decimeter increments, 0.1 to 3...
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
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....
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Rangelands have immense inherent spatial and temporal variability, yet assessments of land condition and trends are often assessed relative to the condition of a limited number of representative points. Ecological Potential (EP) data are spatially comprehensive, quantitative, and needed as a baseline for comparison of current rangeland vegetation conditions, trends, and management targets. We define EP as the potential fractional cover of vegetation components bare ground, herbaceous, litter, shrub, and sagebrush represented in the least disturbed and most productive portion of the western U.S. This dataset enables: 1) setting realistic expectations for restoration and management targets at 30-meter resolution,...
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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