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"Dillon, Gregory K.; Scott, Joe H.; Jaffe, Melissa R.; Olszewski, Julia H.; Vogler, Kevin C.; Finney, Mark A.; Short, Karen C.; Riley, Karin L.; Grenfell, Isaac C.; Jolly, W. Matthew; Brittain, Stuart. 2023. Spatial datasets of probabilistic wildfire risk components for the United States (270m). 3rd Edition. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2016-0034-3".
USFS IIPP Support
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USFS IIPP Support
<div style='text-align:Left;'><div><div><p><span>National data on burn probability (BP) were generated for the conterminous United States (CONUS), Alaska, and Hawaii using a geospatial Fire Simulation (FSim) system developed by the USDA Forest Service Missoula Fire Sciences Laboratory. The FSim system includes modules for weather generation, wildfire occurrence, fire growth, and fire suppression. FSim is designed to simulate the occurrence and growth of wildfires under tens of thousands of hypothetical contemporary fire seasons in order to estimate the probability of a given area (i.e., pixel) burning under current (end of 2020) landscape conditions and fire management practices. The data presented here represent modeled BP and FLPs for the United States (US) at a 270-meter grid spatial resolution. Flame-length probability is estimated for six standard Fire Intensity Levels. The six FILs correspond to flame-length classes as follows: FLP1 = &lt; 2 feet (ft); FLP2 = 2 &lt; 4 ft.; FLP3 = 4 &lt; 6 ft.; FLP4 = 6 &lt; 8 ft.; FLP5 = 8 &lt; 12 ft.; FLP6 = 12+ ft. Because they indicate conditional probabilities (i.e., representing the likelihood of burning at a certain intensity level, given that a fire occurs), the FLP data must be used in conjunction with the BP data for risk assessment.These data are a newer edition of the Short et al. (2016, 2020) data publications. This third edition is based on circa 2020 landscape data, which were the most current LANDFIRE products available at the time of production. The methods used to generate these data generally followed the same process used in previous editions, with improvements made at specific steps. The process steps outlined in the Data Quality, Lineage section of this metadata document are expanded from previous editions to more fully explain each step and provide additional details on methods for this edition. Beyond the newer input landscape data from LANDFIRE, we also used updated datasets for other inputs such as fire occurrence, observed gridded daily weather, and wind data from weather stations. To better capture recent climate conditions, we also shortened the time period of historical weather records used to inform the generation of simulated weather streams for simulation runs, using the most recent 15 years this time (2006-2020) rather than full record from 1972-2012 in the second edition. See the process steps described in the Data Quality, Lineage section for more details.</span></p></div></div></div>
National-scale assessment of wildfire risk offers a consistent means of evaluating threats to valued resources and assets, thereby facilitating investments in management activities that can mitigate those risks. We used a simulation system to estimate the probabilistic components of wildfire risk across the nation. We generated the data in three volumes: (I) the conterminous U.S. (CONUS), (II) Alaska, and (III) Hawaii. These outputs have been generated to support a number of national planning and risk assessment efforts.
USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory.
5775 US Hwy 10 W
Missoula
MT
59808
Ph. 406-329-4800
USFS IIPP Support
USFS
Support
sm.fs.IIPP_Support@usda.gov
USFS IIPP Support
USFS
Support
sm.fs.IIPP_Support@usda.gov
USFS IIPP Support
USFS
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USFS IIPP Support
CONUS; Hawaii; Alaska;
2023;
ISO 19115 Topic Category; geoscientificInformation; National Research & Development Taxonomy; RMRS; Probabilistic Wildfire Risk; Burn Probability; flame length; fire intensity;
ISO 19115 Topic Categories
geoscientificInformation; imageryBaseMapsEarthCover;
ISO 19115 Topic Category
geoscientificInformation
National Research & Development Taxonomy
flame length
fire intensity
geoscientificInformation
imageryBaseMapsEarthCover
RMRS
Probabilistic Wildfire Risk
Burn Probability
CONUS
Hawaii
Alaska
2023
<div style='text-align:Left;'><div><div><p><span>These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:"Dillon, Gregory K.; Scott, Joe H.; Jaffe, Melissa R.; Olszewski, Julia H.; Vogler, Kevin C.; Finney, Mark A.; Short, Karen C.; Riley, Karin L.; Grenfell, Isaac C.; Jolly, W. Matthew; Brittain, Stuart. 2023. Spatial datasets of probabilistic wildfire risk components for the United States (270m). 3rd Edition. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2016-0034-3".</span></p><p><span /></p><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/). 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. 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. USDA is an equal opportunity provider, employer, and lender.</span></p></div></div></div>
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USFS IIPP Support
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