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Caption accompanying photograph: Photo taken on June 4, 1980, shows the flow of mud through the valley area. More of the side of the mountain is visible. Mount St. Helens, Skamania County, Washington. No index card.
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Caption accompanying photograph: Photo dramatically shows the new crater formed by the May 18, 1980 eruption through one of the infrequent breaks in the cloud cover. Over 5,000 feet of the north slope of the mountain was opened. Skamania County, Washington. No index card.
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This update to the Alaska National Land Cover Database (NLCD) 2016 replaces the files dated 20200213. In this update the landcover footprint was extended along the northern coast to include the islands that were missed in previous versions, and several duplicate roads (offset by 1 or 2 pixels) were removed on the Aleutian Islands. The Alaska National Land Cover Database 2016 was created using change detection between the nominal dates of 2011 and 2016 utilizing Google Earth engine composites of Landsat imagery. Traditionally, previous classifications of Alaska used path row data and spectral comparisons between path rows along with ancillary data to derive areas of change. Alaska has many challenges for land cover...
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Landsat Extended Acquisitions of the Poles (LEAP) imaging plan is a Landsat special request data collection program for Earth's polar regions that include Antarctica, Greenland, and Arctic sea ice geographies. The LEAP program includes Landsat 8 and Landsat 9 observatories that operationally acquire spaceborne images of all Earth's land surface and near-shore coastal environments. These images are acquired on a Worldwide Reference System-2, also called WRS-2. The WRS-2 is made up of paths and rows that define Landsat's imaged geography, and once acquired, are processed and discoverable in the U.S. Geological Survey's Landsat global data archive. The LEAP path-rows listed in the attached zipped data file represent...
The data presented here are in support of the evaluation efforts of the satellite-based actual Evapotranspiration (ETa) using the Operational Simplified Surface Energy Balance (SSEBop) model. The ETa data is currently used by the U.S. Geological Survey Famine Early Warning System Network (FEWS NET) to produce and post multitemporal ETa and ETa anomalies online on a regular basis for drought monitoring and early warning purposes and are freely available for download at https://earlywarning.usgs.gov/fews/.
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Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic annual grass cover and dynamics over large areas requires the use of remote sensing that can support early detection and rapid response initiatives. Here, we integrated in situ observations, weekly composites of harmonized Landsat and Sentinel-2 (HLS) data, maps of biophysical variables (e.g. soils and topography) and machine learning techniques to develop fractional estimates of exotic annual grass cover at a 30-m spatial resolution from 2016 to 2018....
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges....
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Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (Rigge et al. 2020). We integrated remotely sensed data (250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) (https://earthexplorer.usgs.gov/)) with land cover, biogeophysical (i.e., soils, topography) and climate data into regression-tree software (Cubist®). We...
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In recent years, rising sea levels have threatened critical infrastructure and cultural assets at Puʻuhonua o Hōnaunau National Historical Park thus motivating the park to make adaptive decisions in managing these key resources. To support the development of decision support tools for sea level rise preparedness, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for Puʻuhonua o Hōnaunau National Historical Park. This dataset was developed in collaboration with the University of Hawaii- Mānoa Sea Level Center, Department of Interior Pacific Island Climate Adaptation Science Center, and...
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These data products are preliminary burn severity assessments derived from post sensor data (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 Area Emergency...
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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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This product is published on a provisional basis to provide necessary information to individuals assessing burn severity impacts on a time sensitive basis. This product was produced using the methods of the Monitoring Trends in Burn Severity (MTBS) Program, however this fire may not meet the criteria for an MTBS initial assessment. 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. MTBS typically maps fires using an initial assessment (immediately after the fire) or an extended assessment (peak of green the season after...
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The U. S. Fish and Wildlife Service (FWS) 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. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a thematic raster...
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The U. S. Fish and Wildlife Service (FWS) 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. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a thematic raster...
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The U. S. Fish and Wildlife Service (FWS) 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. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a thematic raster...
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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 (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 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 includes...
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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...
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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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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...


map background search result map search result map Modeled conterminous United States Crop Cover datasets for 2000 - 2013 The Relative Impacts of Climate and Land-use Change on Conterminous United States Bird Species from 2001 to 2075 Showing the flow of mud through the valley area, Mount St. Helens. Skamania County, Washington. 1980. Fractional estimates of invasive annual grass cover in dryland ecosystems of western United States (2016 – 2018) Monitoring Trends in Burn Severity (ver. 8.0, April 2024) Using Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018 National Park Service (ver. 7.0, April 2024) Burned Area Reflectance Classification assessment Fire Occurrence Dataset Point Locations (ver. 7.0, April 2024) Burned Area Reflectance Classification Thematic Burn Severity Mosaic for 2019 (ver. 6.0, January 2024) National Park Service Thematic Burn Severity Mosaic in 2021 (ver. 6.0, January 2024) Provisional Initial Assessment Burned Areas Boundaries (ver. 7.0, April 2024) Topobathymetric Model of Puʻuhonua o Hōnaunau National Historical Park, 2011 to 2019 National Land Cover Database (NLCD) 2011 - Alaska LANDFIRE 2022 Forest Canopy Base Height (CBH) AK US Fish and Wildlife Service Fire Atlas- Burn Severity Mosaic for CONUS in 2002 (ver. 6.0, January 2024) US Fish and Wildlife Service Fire Atlas- Burn Severity Mosaic for CONUS in 2005 (ver. 6.0, January 2024) US Fish and Wildlife Service Fire Atlas- Burn Severity Mosaic for CONUS in 2007 (ver. 6.0, January 2024) Topobathymetric Model of Puʻuhonua o Hōnaunau National Historical Park, 2011 to 2019 Showing the flow of mud through the valley area, Mount St. Helens. Skamania County, Washington. 1980. Using Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018 US Fish and Wildlife Service Fire Atlas- Burn Severity Mosaic for CONUS in 2002 (ver. 6.0, January 2024) Fractional estimates of invasive annual grass cover in dryland ecosystems of western United States (2016 – 2018) US Fish and Wildlife Service Fire Atlas- Burn Severity Mosaic for CONUS in 2007 (ver. 6.0, January 2024) US Fish and Wildlife Service Fire Atlas- Burn Severity Mosaic for CONUS in 2005 (ver. 6.0, January 2024) LANDFIRE 2022 Forest Canopy Base Height (CBH) AK The Relative Impacts of Climate and Land-use Change on Conterminous United States Bird Species from 2001 to 2075 National Land Cover Database (NLCD) 2011 - Alaska Modeled conterminous United States Crop Cover datasets for 2000 - 2013 Monitoring Trends in Burn Severity (ver. 8.0, April 2024) National Park Service (ver. 7.0, April 2024) Burned Area Reflectance Classification assessment Fire Occurrence Dataset Point Locations (ver. 7.0, April 2024) Provisional Initial Assessment Burned Areas Boundaries (ver. 7.0, April 2024) National Park Service Thematic Burn Severity Mosaic in 2021 (ver. 6.0, January 2024) Burned Area Reflectance Classification Thematic Burn Severity Mosaic for 2019 (ver. 6.0, January 2024)