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This product ("Prairie fires") presents burned area boundaries for The Flint Hills Ecoregion (KS and OK), one of the most fire prone ecosystems in the United States where hundreds of thousands of acres burn annually as prescribed fire and wildfire. The prairie fire products provide the extent of larger prairie fires in the Flint Hills to record the occurrence of fire and can be used to identify individual burned areas within the perimeters. This product is published to provide fire information of the most fire prone ecosystems to individuals and land management communities for assessing burn extent and impacts on a time sensitive basis. The methods used to produce the prairie fire products from 2019 to present are...
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...
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...
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...
CONUS-wide annual water-year actual ET (ETa) data using Landsat resolution satellite imagery from the Operational Simplified Surface Energy Balance (SSEBop) model (version 2.6) with the Forcing and Normalizing Operation (FANO) parameterization. Raster data products were generated for five (5) water-years (Oct-Sep; 2009, 2011, 2013, 2016, 2018). Data and metadata is provided for individual GeoTIFF tiles distributed in the UTM Zone in which it lies, available for each water-year.
Categories: Data;
Types: GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Conterminous United States (CONUS),
Evapotranspiration,
Landsat,
Water use
Data set includes a mosaic of multiple Landsat 8 OLI sensor path/row combinations for May 14, 17, and 19, 2014 covering the South Atlantic Landscape Conservation Cooperative (SALCC) geography between extreme northeastern North Carolina (including Back Bay, VA-NC) south through Sapelo I., GA. The imagery was acquired as georeferenced, calibrated digital data. Water and upland masking used NIR thresholds, CCAP land cover, and LiDAR DEMs. The image composite includes three normalized difference indces useful for marsh classification and monitoring, including: 1) Normalized Difference Vegetation Index (NDVI), 2) Normalized Difference Water Index (NDSI), and 3) Normalied Difference Soil Index (NDSI). The NDX bands were...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service;
Tags: Georgia,
Landsat,
Normalized Difference Indices,
North Carolina,
South Carolina Coastal,
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the zip folder there are 5 raster tiffs. i. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit ii. XXX_pre_refl.tif The at-sensor-reflectance of the prefire landsat scene, named with the PolyID unique identifier for the...
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the zip folder there are 5 raster tiffs. i. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit ii. XXX_pre_refl.tif The at-sensor-reflectance of the prefire landsat scene, named with the PolyID unique identifier for the...
This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the folder there are 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of...
A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.3 annual land cover products (1985–2021) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2021) to a reference sample of 26,971 Landsat resolution (30m x 30m) pixels. These pixels were selected from a sample frame of all pixels in the ARD grid system which fell within the map area (Dwyer et al., 2018). Interpretation used the TimeSync reference data collection tool which visualizes Landsat images and Landsat data values for all usable images in the time series (1984–2021)...
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...
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...
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...
This data release contains a single vector shapefile and two text documents with code used to generate the data product. This vector shapefile contains the locations of 365 “plugged and abandoned” well sites from across the Colorado Plateau with their respective relative fractional vegetation cover (RFVC) values. Oil and gas pads are often developed for production, and then capped, reclaimed, and left to recover when no longer productive (collectively termed “plugged and abandoned”). Understanding the rates, controls, and degree of recovery of these reclaimed well sites (well pads) to a state similar to pre-development conditions is critical for energy development and land management decision processes. We used...
Regional, high-resolution mapping of vegetation cover and biomass is central to understanding changes to the terrestrial carbon (C) cycle, especially in the context of C management. The third most extensive vegetation type in the United States is pinyon?juniper (P?J) woodland, yet the spatial patterns of tree cover and aboveground biomass (AGB) of P?J systems are poorly quantified. We developed a synoptic remote-sensing approach to scale up pinyon and juniper projected cover (hereafter ?cover?) and AGB field observations from plot to regional levels using fractional photosynthetic vegetation (PV) cover derived from airborne imaging spectroscopy and Landsat satellite data. Our results demonstrated strong correlations...
Categories: Publication;
Types: Citation,
Journal Citation;
Tags: AVIRIS,
ETM+,
Ecological Applications,
Ecological Society of America,
Juniperus osteosperma,
This data was used in the analysis for the article “Burn Severity Controls on Post-fire Araucaria-Nothofagus Regeneration in the Andean Cordillera” by T. Assal, M. Gonzalez and J. Sibold. The aim of the study was to investigate post-fire regeneration patterns of forests on the west slope of the Andes; to evaluate the relationship between remotely sensed burn severity and forest mortality; and to assess controls of burn severity on forest response at local spatio-temporal scales. This dataset reflects the burn severity calculated from Landsat data as part of the analysis.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Chile,
Landsat,
Tolhuaca National Park,
Tolhuaca National Park,
biota,
Three ET datasets were generated to evaluate the potential integration of Landsat and Sentinel-2 data for improved ET mapping. The first ET dataset was generated by linear interpolation (Lint) of Landsat-based ET fraction (ETf) images of before and after the selected image dates. The second ET dataset was generated using the regular SSEBop approach using the Landsat image only (Lonly). The third ET dataset was generated from the proposed Landsat-Sentinel data fusion (L-S) approach by applying ETf images from Landsat and Sentinel. The scripts (two) used to generate these three ET datasets are included – one script for processing SSEBop model to generate ET maps from Lonly and another script for generating ET maps...
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