20230228 14523400 1.0 TRUE TRUE 150000000 5000 ItemDescription EDW_RAVG_v2_01 <div style='text-align:Left;'><div><div><div style='font-size:12pt'><p><span>The USDA Forest Service Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program produces geospatial and related data representing post-fire vegetation condition by means of standardized change detection methods based on Landsat or similar multispectral satellite imagery. RAVG data products characterize the impact of disturbance (fire) on vegetation within a fire perimeter, and include estimates of percent change in live basal area (BA), percent change in canopy cover (CC), and the 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"). Annual national mosaics of each thematic product are prepared at the end of the fire season and updated, as needed, when additional fires from the given year are processed. The annual mosaics are available via the Raster Data Warehouse (RDW, see https://apps.fs.usda.gov/arcx/rest/services/RDW_Wildfire). A combined perimeter dataset, including the burn boundaries for all published Forest Service RAVG fires from 2012 to the present, is likewise updated as needed (at least annually).</span></p></div></div></div></div> Canopy Cover Burn Severity CBI CONUS Vegetation Condition Perimeter Burn Area Boundary Wildfire Biota Basal Area RAVG Composite Burn Index United States Wildland Fire 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 the cost-effective and efficient 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 produces 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. USDA Forest Service, Geospatial Technology and Applications Center (GTAC) <div style='text-align:Left;'><div><div><div style='font-size:12pt'><p><span>There are no restrictions on use, except for reasonable and proper acknowledgement of information sources. 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></div></div></div></div> 20230803 iVBORw0KGgoAAAANSUhEUgAAAMgAAACFCAYAAAAenrcsAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzcvVeTJNmVJva5CA8tMjJSq6os3VXdjRZoAQww0DbAjGFnjGu2 yycan7g0KuMrzch/QNs/wHkgbWhGjtnuzC5Hj2ExEN3TQHdXi9JVWVmpdYZWrmnnuHukZ6SHzMgC sBfIrswI9+v3Xr/nnnO+o+R3333Xhtts24YgCPwzaPPu9f9Nbdi+6EcUxa7XmKYJSZI6PsMbgzeO oPH1apZl8X00Fu8eWwBs+p8pYGwqCVM3US3WMfhMT4910LXy1smZG30AiCERC2+P4/LbOaTScXzx NxvIRsZxaWke8WwCGK9j7ck2Vj/fxfFWGXrDwthcAvFsGLVyE4WdGmRZhiSJaFSbsG0BAkzu3BZE CLb3Ts6un2ALsAWLFpvvs+hX0Pic6+l/9AnPs4/31+8atJ5/jn6C+qT+5FF03ok4LrK1b9qg8dNn rU19zjGdut/mPQBIOuZvplErqagUqxAgDt33MOvvnx/3I9iAaeP4eRXNog4lJCK/VcX07WlkphMQ p3TI8ybm00lotorj3SpsmKjka6jXmjA1C7ZuwTBMmIIF6s4hBMl5HhOJ7X4eMA+eAr0TC4lkFBOT 49ja3IWuGe79dIFDHC9jj5ynee9Dbv/QfyoN2pm/9eIA3jWd+unn+f2MtxOReNd3O4H8/bYTohyW kVtMYfHNHPZWi1h7IIAP2gHbeTfKyZidzUfdVQ9VVA5ViLYBCyLKtSqqQhHZBRm1Zg3lYgP1igbD 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