Filters: partyWithName: Earth Resources Observation and Science (EROS) Center (X) > partyWithName: U.S. Geological Survey (X) > Types: Map Service (X)
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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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Exotic annual grasses [EAG] are one of the most damaging biological stressors in western North America. Despite numerous environmental and societal impacts associated with EAG there remains a need to enhance regional monitoring capabilities to better guide management and conservation efforts. Here we provide estimates of historic and potential future trends in EAG abundance that were developed using linear trend analysis and machine learning techniques at a 30-m spatial resolution. Specifically, these data represent historic (1985 to 2019) and potential future (2025-2040) rates of exotic annual grass change as estimated using Theil-Sen regression and a process-constrained, random forest model assuming only changes...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Ecology,
Exotic annual grasses, cheatgrass, remote sensing,
Exotic annual grasses, cheatgrass, remote sensing,
Land Use Change,
Remote Sensing,
Exotic annual grasses are one of the most damaging biological stressors in western North America and increase the susceptibility of landscapes to wildfire occurrence. Here we couple estimates of long-term rangeland component fractions (e.g. exotic annual grasses) with remote sensing, climate data, and machine learning techniques to estimate the long-term (1985 to 2019) probability of wildfire occurrence (30-m spatial resolution) in sagebrush-dominated landscapes of the western United States.
Disclaimer: this is an historic version of NLCD provided for research and citation purposes. Different release dates of NLCD cannot be used with other release dates for correct analysis. Each release of NLCD generates a complete set of directly comparable products. These products must be used together for correct analysis. You can find the latest suite of synced products at www.mrlc.gov. The National Land Cover Database 2001 land cover layer for mapping zones 01-66 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Base Maps,
Coastal Zone,
Earth Cover,
GIS,
Land Cover,
Caption accompanying photograph: Photo shows the May 18, 1980 eruption, the largest to date, with the upper third of the mountain centered in the photo. Mount Adams in background. Skamania County, Washington. No index card.
Caption accompanying photograph: Photo shows a closer view of the crater and eruption of May 18, 1980. Mount St. Helens, Skamania County, Washington. No index card.
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.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: LCMAP,
Land Change Monitoring, Assessment, and Projection,
Land Use Change,
Remote Sensing,
USGS Science Data Catalog (SDC),
These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
As part of the next generation NLCD 2016 mapping process, the NLCD research team developed a suite of intermediate products that were used to generate the final NLCD Land Cover products. Some of those products also have value as independent products and are provided here. Please read the product descriptions to understand what the product represents. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: GIS,
Image processing,
Land Use Land Cover Theme,
Land cover,
N.L.C.D.,
Caption accompanying photograph: Photo shows the undisturbed snow cover of Mount St. Helens on April 10, 1980, with a plume of steam visible at the summit. Skamania County, Washington. No index card.
Categories: Image;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Mount St. Helens Collection,
Mount St. Helens EROS Data Center Collection,
Skamania County, Washington,
Volcanoes,
aerial,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
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...
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,
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,
The USGS’s FORE-SCE model was used to produce land-use and land-cover (LULC) projections for the conterminous United States. The projections were originally created as part of the "LandCarbon" project, an effort to understand biological carbon sequestration potential in the United States. However, the projections are being used for a wide variety of purposes, including analyses of the effects of landscape change on biodiversity, water quality, and regional weather and climate. The year 1992 served as the baseline for the landscape modeling. The 1992 to 2005 period was considered the historical baseline, with datasets such as the National Land Cover Database (NLCD), USGS Land Cover Trends, and US Department of Agriculture's...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: CONUS,
CONUS,
Conterminous,
Conterminous United States,
FORE-SCE,
The data are a long-term (1980-present), daily reanalysis of reference evapotranspiration, covering the globe at a spatial resolution of 0.625° Longitude x 0.5° Latitude. Reference evapotranspiration is a measure of evaporative demand, or the "thirst of the atmosphere", basically how much moisture from the surface could evaporate into overpassing air, assuming (i) that enough water is available to evaporate and (ii) the surface is covered with a specific reference crop that completely shades the ground (some other conditions also apply). For this dataset, reference evapotranspiration is derived from the daily implementation of the Penman-Monteith reference evapotranspiration equation (Monteith, 1965) as codified...
Categories: Data,
Data Release - Revised;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Raster;
Tags: Climatology,
Remote Sensing,
USGS Science Data Catalog (SDC),
Water Resources,
climatologyMeteorologyAtmosphere,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
The dataset provides a near real time estimation of 2020 herbaceous mostly annual fractional cover predicted on July 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P96PVZIF., Boyte et al. 2018 https://doi.org/10.5066/P9RIV03D.), but starting this year we are mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Idaho,
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. 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 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year...
Categories: Data Release - Revised;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: GIS,
Image processing,
Land Use Land Cover Theme,
Land cover,
NGDA,
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