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ExtractByMask Z:\TWRA\New_and_updated_rastersOrig\script_output\temp_hide\HUrisk_proj.tif Z:\TWRA\Integrated_measures\script_output\WHP_proj.tif Z:\TWRA\New_and_updated_rastersOrig\script_output\temp_hide\Extract_HUrisk_1.tif Inside "-12003310.5529859 2879427.43716212 -10271400.5529859 4490777.43716212 PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0]]"
BuildPyramids Z:\TWRA\New_and_updated_rastersOrig\script_output\temp_hide\HUrisk_proj_clip.tif -1 NONE Nearest LZ77 75 OVERWRITE
Copy Z:\TWRA\New_and_updated_rastersOrig\script_output\temp_hide\HUrisk_proj_clip.tif Z:\TWRA\New_and_updated_rastersOrig\script_output\HUrisk_proj_clip.tif "Raster Dataset" #
Rename Z:\TWRA\New_and_updated_rasters\script_output\HUrisk_proj_clip.tif Z:\TWRA\New_and_updated_rasters\script_output\HUrisk_proj.tif RasterDataset
file://Z:\TWRA\New_and_updated_rastersOrig\script_output\HUrisk_proj_clip.tif
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HUrisk_proj_clip.tif
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WGS_1984_Web_Mercator_Auxiliary_Sphere
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The purpose of the Texas Wildfire Hazard Assessment (TxWRAP) is to provide foundational information about wildfire hazard across all land ownership in the state of Texas. Such information supports fuel management planning decisions, as well as revisions to land and resource management plans. A wildfire hazard assessment is a quantitative analysis of potential impacts by wildfire.
<div style='text-align:Left;'><div><div><p><span>This spatial dataset was produced with the Wildfire Exposure Simulation Tool (WildEST), a cloud-based geospatial fire behavior characteristic simulation system. WildEST performs multiple deterministic simulations under a range of weather types (wind speed, wind direction, fuel moisture content) and weights those results based on weather type probabilities (WTP).</span></p><p><span style='font-weight:bold;'>HURisk ntegrates all four primary elements of wildfire risk - likelihood, intensity, susceptibility, and exposure - on pixels where housing unit density is greater than zero. It is an index with similarities to Risk to Potential Structures (RPS), but it also incorporates housing unit count. </span></p><p><span style='font-weight:bold;'>To obtain HUrisk, we used the housing unit count as derived from HUDen (representing exposure) and the cRPS raster (representing intensity and susceptibility). We multiplied those two datasets by the annual burn probability (BP) raster (representing wildfire likelihood). HURisk is analogous to the expected Net Value Change (eNVC) metric presented by Scott et al. (2013), if the only highly-valued resource or asset is housing units. The equation for HURisk is: </span></p><p><span style='font-weight:bold;'>HURisk = (HUDen * 0.0001) * cRPS * BP </span></p><p><span style='font-weight:bold;'>To produce the final integer version of the HURisk raster, we multiplied by 1,000,000 and rounded to the nearest intege. Pixels where the HUDen raster is zero are NoData in the HURisk raster.</span></p></div></div></div>
Primary data contact: Texas A&M Forest Service, Forest Resource Protection Division, Applied Technology Department. Send an email to TxWRAP-Support@tfs.tamu.edu for inquires. Visit www.TexasWildfireRisk.com for additional information.This dataset was developed for the Texas Wildfire Risk Assessment by Pyrologix LLC (www.pyrologix.com), a subsidiary of Vibrant Planet (www.vibrantplanet.net).
housing_unit_risk_img
2024-09-30T00:00:00
WildEST
Wildfire Exposure Simulation Tool
TWRA
Texas Wildfire Risk Assessment
TxWRAP
Texas Wildfire Risk Assessment Portal
TFS
TAMFS
Texas A&M Forest Service
<div style='text-align:Left;'><div><div><p><span>The user must be aware of data conditions and must ultimately bear responsibility for the appropriate use of the information with respect to possible errors, possible omissions, map scale, data collection methodology, data currency, and other conditions specific to certain data.</span></p></div></div></div>
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