20260115 18222300 1.0 TRUE 150000000 5000 FGDC USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 data@fs.fed.us 20260123 ArcGIS Metadata 1.0 withheld USFS_EDW_RAVG_CompositeBurnIndex 2022-02-01T00:00:00 U.S. Forest Service raster dataset <div style='text-align:Left;'><div><div><p><span>The USDA Forest Service Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program produces geospatial data and maps of post-fire vegetation condition using standardized change detection methods based on Landsat or similar multispectral satellite imagery. RAVG data products characterize vegetation condition within a fire perimeter, and include estimates of percent change in basal area (BA), percent change in canopy cover (CC), and a standardized composite burn index (CBI). Standard thematic products include 7-class percent change in basal area (BA-7), 5-class percent change in canopy cover (CC-5), and 4-class CBI (CBI-4). Contingent upon the availability of suitable imagery, RAVG products are prepared for all wildland fires reported within the conterminous United States (CONUS) that include at least 1000 acres of forested National Forest System (NFS) land (500 acres for Regions 8 and 9 as of 2016). Data for individual fires are typically made available within 45 days after fire containment ("initial assessments"). Late-season fires, however, may be deferred until the following spring or summer ("extended assessments"). National mosaics of each thematic product are prepared annually. The associated burned area perimeters are available via the Enterprise Data Warehouse (EDW, see https://data.fs.usda.gov/geodata/edw/datasets.php). Assessment type (initial or extended assessment) for each fire is included as an attribute in the perimeter dataset.</span></p></div></div></div> RAVG data are produced to assist in post-fire vegetation management planning. They are intended to enhance decision-making capabilities and reduce planning and implementation costs associated with post-fire vegetation management. The primary benefit is cost-effective, efficient, and precise identification of potential areas of resource concern following wildfire. RAVG complements the Burned Area Emergency Response (BAER) Imagery Support program--which provides information integral to determining fire effects on soils--by providing information about fire effects on existing vegetation. RAVG analysis provides a first approximation of areas that may require reforestation treatments after a fire in order to re-establish forest cover and restore associated ecosystem services. This initial approximation may be followed by site-specific diagnosis and development of a silvicultural prescription to more precisely identify reforestation needs. U.S. Forest Service (801) 975-3800 Washington DC 20250 SM.FS.PostFireRAVG@usda.gov Questions or comments may be submitted by phone, by email or via the RAVG website: <https://fsapps.nwcg.gov/ravg/contact> United States CONUS ISO 19115 Topic Category Biota RAVG Burn Severity Vegetation Condition Wildland Fire Wildfire Landsat Normalized Burn Ratio Differenced Normalized Burn Ratio Relative Differenced Normalized Burn Ratio NBR dNBR RNBR Basal Area Canopy Cover Composite Burn Index CBI Biota RAVG Burn Severity Vegetation Condition Wildland Fire Wildfire Landsat Normalized Burn Ratio Differenced Normalized Burn Ratio Relative Differenced Normalized Burn Ratio NBR dNBR RNBR Basal Area Canopy Cover Composite Burn Index CBI United States CONUS <div style='text-align:Left;'><div><div><p><span>The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. </span></p><p><span /></p><p><span>Additionally, the U.S. Forest Service waives copyright and related rights in the work worldwide through the CC0 (which can be found at https://creativecommons.org/public-domain/cc0/). </span></p><p><span /></p><p><span>In accordance with Federal civil rights law and U.S. Department of Agriculture (USDA) civil rights regulations and policies, the USDA, its Agencies, offices, and employees, and institutions participating in or administering USDA programs are prohibited from discriminating based on race, color, national origin, religion, sex, disability, age, marital status, family/parental status, income derived from a public assistance program, political beliefs, or reprisal or retaliation for prior civil rights activity, in any program or activity conducted or funded by USDA (not all bases apply to all programs). Remedies and complaint filing deadlines vary by program or incident. </span></p><p><span /></p><p><span>Persons with disabilities who require alternative means of communication for program information (e.g., Braille, large print, audiotape, American Sign Language, etc.) should contact the State or local Agency that administers the program or contact USDA through the Telecommunications Relay Service at 711 (voice and TTY). Additionally, program information may be made available in languages other than English. </span></p><p><span /></p><p><span>To file a program discrimination complaint, complete the USDA Program Discrimination Complaint Form, AD-3027, found online at How to File a Program Discrimination Complaint and at any USDA office or write a letter addressed to USDA and provide in the letter all of the information requested in the form. To request a copy of the complaint form, call (866) 632-9992. Submit your completed form or letter to USDA by: (1) mail: U.S. Department of Agriculture, Office of the Assistant Secretary for Civil Rights, 1400 Independence Avenue, SW, Mail Stop 9410, Washington, D.C. 20250-9410; (2) fax: (202) 690-7442; or (3) email: program.intake@usda.gov. </span></p><p><span /></p><p><span>USDA is an equal opportunity provider, employer, and lender. </span></p></div></div></div> The U.S. Forest Service makes no warranty, express or implied, nor assumes any liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data or for the improper or incorrect use of those data. The data are dynamic and may change over time. The user is responsible for verifying the limitations of the geospatial data and for using the data accordingly. None None ERDAS Imagine 14.00.0100, Build 745; Esri ArcCatalog 10.2.2.3552 true -126.882 -72.763 50.019 29.174 Ground condition 2012 2021 1 -126.894429 -72.569441 51.278904 27.578756 Geospatial Technology and Applications Center - Disturbance Assessment and Services 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2012-2023 No tests for logical consistency have been performed on these data. Each layer is a mosaic of numerous individual raster datasets, which were produced using a standardized process; however, some variability is expected due to the many factors that affect the underlying imagery as a function of time, location, and natural environment. This dataset is intended to include burn severity data for all fires that meet standard RAVG criteria for the given years; namely, wildfires reported within CONUS that include at least 1000 acres of forested National Forest System land (at least 500 acres for Regions 8 and 9 as of 2016). Exceptions (omissions) may include fires for which suitable imagery was not available in a timely manner (i.e., within 45 days after fire containment for initial assessments). The target scale of this dataset is 1:24,000. The horizontal accuracy of this dataset is determined by that of the moderate-resolution multi-spectral imagery from which it is derived. RAVG burn severity data are derived from multi-spectral imagery. A Relative Differenced Normalized Burn Ratio (RdNBR) image, which portrays the variation of burn severity within a burn area, is derived from a pair of multi-spectral images: a post-fire scene and a corresponding pre-fire scene. Whenever possible, the RAVG project uses Landsat images that have been geometrically rectified, terrain corrected, and converted to top-of-atmosphere (at-satellite) reflectance. The following process was developed for Landsat imagery but applies to other multi-spectral satellite imagery that includes a near-infrared (NIR) band and a short-wave infrared (SWIR) band (approximately 2.2 micrometers). The Normalized Burn Ratio (NBR) is computed for each image using the NIR and SWIR bands: NBR = (NIR - SWIR) / (NIR + SWIR) The Differenced NBR (dNBR) is computed as the change in NBR, scaled by 1000 (for representation as integer values): dNBR = (PreNBR - PostNBR)*1000 The Relative dNBR (RdNBR) includes an additional scale factor designed to reduce the correlation with pre-fire vegetation density. It also includes an offset calculated from the dNBR in an unburned area in the vicinity of the fire having vegetation cover similar to that of the burned area. The offset is intended to account for seasonal or interannual differences between the two images. RdNBR = (dNBR - offset)/sqrt(abs(PreNBR/1000)) RdNBR is the index used for vegetation burn severity assessments in the RAVG program. Higher RdNBR values are correlated with more severe burns. Three burn severity indices form the complement of RAVG products: Composite Burn Index (CBI), percent change in basal area (BA), and percent change in canopy cover (CC). Values are estimated from RdNBR via regression models, which were developed from field data and Landsat imagery, both acquired approximately one year post-fire. The field data were collected from a number of fires that burned in the Sierra Nevada and Klamath Mountains in California between 1999 and 2006. RdNBR values were derived from post-fire imagery acquired at approximately the same time, and seasonally matching imagery from before each fire. The CBI is a composite linear combination of fire effects experienced at a site and encompasses all vegetation strata from the forest floor to the upper canopy. The composite value ranges from 0 to 3. Thematic CBI-based severity classes were "calibrated" from field data collected about one year post-fire, meaning that field data collected on a given fire or fires that occurred in similar vegetation types were used to classify burn severity as unchanged, low, moderate or high severity. CBI values of 0.1, 1.25, and 2.25 were selected as the breakpoints between the successive classes, which are defined as follows: Unchanged: Areas indistinguishable from pre-fire conditions. This does not necessarily indicate that the area was unburned. Low: Areas of surface fire with little change in cover and little mortality of the structurally dominant vegetation. Moderate: Areas between low and high severity, with a mixture of effects on the structurally dominant vegetation. High: Areas where the dominant vegetation has high to complete mortality. Percent change in basal area was calibrated through regression analysis of the RdNBR index to basal area change as measured in the same field plots where the CBI data were collected. For this measure, a tree with no green foliage one year post-fire was defined as being dead. Percent change in canopy cover was likewise calibrated through regression analysis of the RdNBR index to measured or calculated tree canopy cover change. Pre-fire canopy cover was determined through photo interpretation of pre-fire digital orthophotos or by way of the Forest Vegetation Simulator (FVS) (https://www.fs.fed.us/fmsc/fvs/). The following models were used for extended assessments; that is, assessments based on post-fire imagery acquired during the growing season one year after the fire: CBI = (1/0.6124)*LN((RdNBR + 123.3)/196.8) [2016 and earlier] CBI = (1/0.3890)*LN((RdNBR + 369.0)/421.7) [2017 and later] BA Percent Change = 100*(SIN((RdNBR-166.5)/389))^2 CC Percent Change = 100*(SIN((RdNBR-161.0)/392.6))^2 Calibrated thresholds for initial assessments were derived through regression modeling of satellite reflectance values from imagery collected one year post-fire to imagery acquired immediately post-fire. Application of the calculated correction factor yields the following initial assessment models: CBI = (1/0.6124)*LN((RdNBR/1.1438 + 123.3)/196.8) [2016 and earlier] CBI = (1/0.3890)*LN((RdNBR/1.1438 + 369.0)/421.7) [2017 and later] BA Percent Change = 100*(SIN((RdNBR/1.1438-166.5)/389))^2 CC Percent Change = 100*(SIN((RdNBR/1.1438-161.0)/392.6))^2 A thematic version of each continuous burn severity raster was created based on the following class breaks: Four-category severity classification based on CBI: 0 = outside perimeter 1 = unchanged (0 <= CBI < 0.1) 2 = low severity (0.1 <= CBI < 1.25) 3 = moderate severity (1.25 <= CBI < 2.25) 4 = high severity (2.25 <= CBI <= 3.0) 9 = unmappable Seven-category percent change in basal area (BA): 0 = outside perimeter 1 = 0% BA loss 2 = 0% < BA loss < 10% 3 = 10% <= BA loss < 25% 4 = 25% <= BA loss < 50% 5 = 50% <= BA loss < 75% 6 = 75% <= BA loss < 90% 7 = BA loss >= 90% 9 = unmappable Five-category percent change in canopy cover (CC): 0 = outside perimeter 1 = 0% CC loss 2 = 0% < CC loss < 25% 3 = 25% <= CC loss < 50% 4 = 50% <= CC loss < 75% 5 = CC loss >= 75% 9 = unmappable When a perimeter for a given fire was available from the incident management team or local unit, it was used as the initial approximation for the RAVG burned area perimeter. In many cases, supplied perimeters were edited to account for obvious discrepancies with the visible burned area (based on the post-fire imagery). If no perimeter was provided, the burned area boundary was delineated from the dNBR and post-fire reflectance imagery. Open water and areas obscured by clouds, shadows, active fire, smoke, or snow were masked and identified as "unmappable". Note that derived burn severity products represent a snapshot in time and that the models are applied to the entire extent of each burned area without regard to vegetation type. Factors such as delayed mortality, resprouting, the presence of non-tree vegetation, and the occurrence of non-fire disturbances can contribute to errors in the burn severity estimates. 2021 All thematic burn severity images of a given severity type (percent change in basal area, percent change in canopy cover, or composite burn index) for a given year have been mosaicked into a national burn severity raster dataset. If needed, constituent raster datasets were resampled to a common resolution (30 m) and snapped to a common grid (the 2011 National Land Cover Database (NLCD)). Note that initial and extended assessments, if any, are combined in the mosaics. Assessment type for each fire is included as an attribute in the associated burned area perimeter dataset, available via the Enterprise Data Warehouse (EDW, see https://data.fs.usda.gov/geodata/edw/datasets.php). 2021 0 1 0 -14125823.192200 3195967.621400 -14125823.192200 6670777.621400 -8078393.192200 6670777.621400 -8078393.192200 3195967.621400 -11102108.192200 4933372.621400 201581 30.000000 115827 30.000000 EPSG 6.18.3(9.3.1.2) Band_1 8 9.000000 1.000000 CBI4 RAVG 4-class Composite Burn Index (CBI) class U.S. Forest Service Value 4-class Composite Burn Index (CBI) Category U.S. Forest Service 0 Outside of fire perimeter Internal 1 Unchanged (0 <= CBI < 0.1) Internal 2 Low Severity (0.1 <= CBI < 1.25) Internal 3 Moderate Severity (1.25 <= CBI < 2.25) Internal 4 High Severity (2.25 <= CBI <= 3.0) Internal 9 Unmappable Internal Red Red Color Value (0-255 scale) U.S. Forest Service 0 255 Green Green Color Value (0-255 scale) U.S. Forest Service 0 255 Blue Blue Color Value (0-255 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