LibraryData/library_env_or_wildfire_average_flame_length

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WildEST – Wildfire Exposure Simulation Tool

WildEST is a scripted geospatial process used for simulating potential fire behavior characteristics that addresses two shortcomings of current methods. WildEST performs multiple deterministic simulations under a range of weather types (wind speed, wind direction, fuel moisture content). Rather than weighting results solely according to the temporal relative frequencies of the weather scenarios, the WildEST process integrates results by weighting them according to their weather type probabilities (WTP), which appropriately weights high-spread conditions into the calculations.

Most WildEST results apply to the head of the fire. For fire-effects calculations, WildEST also generates flame-length probability rasters that incorporate non-heading spread directions, for which fire intensity is considerably lower than at the head of the fire. These “NVC” FLPs are analogous to FLP rasters produced by FSim.

These WildEST results were completed on the 2022 current-condition fuelscape (derived from LANDFIRE), which reflects fuelscape conditions for the year 2022 and includes all historical fuel disturbances through 2021. WildEST results were modified for risk calculations in the QWRA using an irrigated agriculture mask to assign FLPs to pixels which are likely to be irrigated during fire season. An irrigated agriculture mask was created from LANDFIRE 2.2.0 Fire Behavior Fuel Models (where the model = “NB3”), and data collected from IrrMapper (Ketchum et al., 2020). All NB3 pixels as well as pixels that were classified as irrigated in three of the most recent five years in IrrMapper were included in the irrigated agriculture mask. Pixels in the irrigated agriculture mask were assigned an FLP of 0.75 for flame lengths between 0 – 2 feet, 0.25 for flame lengths 2 – 4 feet, and an FLP of 0 for all intensity values greater than 4 feet.

This dataset represents the mean conditional flame length. For each pixel, it was calculated as the sum product of all FIL rasters and the midpoint flame length of each FIL class. For FIL6 we used a midpoint flame length of 100 feet to represent torching trees.

Fire-effects flame-length probability rasters are used for effects analysis in a landscape wildfire risk assessment, as described in USFS GTR-315.

Probability is calculated using non-heading fire behavior and is weighted according to WTP, incorporating both temporal frequencies and the influence of high-spread conditions. Raster resolution is 30m. Data finalized 11/17/2022.

Ketchum, D., Jencso, K., Maneta, M.P., Melton, F., Jones, M.O., Huntington, J., 2020. IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S. Remote Sensing 12, 2328. https://doi.org/10.3390/rs12142328

Map Name: library_env_or_wildfire_average_flame_length_2023

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Average Flame Length (0)

Description: WildEST – Wildfire Exposure Simulation ToolWildEST is a scripted geospatial process used for simulating potential fire behavior characteristics that addresses two shortcomings of current methods. WildEST performs multiple deterministic simulations under a range of weather types (wind speed, wind direction, fuel moisture content). Rather than weighting results solely according to the temporal relative frequencies of the weather scenarios, the WildEST process integrates results by weighting them according to their weather type probabilities (WTP), which appropriately weights high-spread conditions into the calculations.Most WildEST results apply to the head of the fire. For fire-effects calculations, WildEST also generates flame-length probability rasters that incorporate non-heading spread directions, for which fire intensity is considerably lower than at the head of the fire. These “NVC” FLPs are analogous to FLP rasters produced by FSim. These WildEST results were completed on the 2022 current-condition fuelscape (derived from LANDFIRE), which reflects fuelscape conditions for the year 2022 and includes all historical fuel disturbances through 2021. WildEST results were modified for risk calculations in the QWRA using an irrigated agriculture mask to assign FLPs to pixels which are likely to be irrigated during fire season. An irrigated agriculture mask was created from LANDFIRE 2.2.0 Fire Behavior Fuel Models (where the model = “NB3”), and data collected from IrrMapper (Ketchum et al., 2020). All NB3 pixels as well as pixels that were classified as irrigated in three of the most recent five years in IrrMapper were included in the irrigated agriculture mask. Pixels in the irrigated agriculture mask were assigned an FLP of 0.75 for flame lengths between 0 – 2 feet, 0.25 for flame lengths 2 – 4 feet, and an FLP of 0 for all intensity values greater than 4 feet. This dataset represents the mean conditional flame length. For each pixel, it was calculated as the sum product of all FIL rasters and the midpoint flame length of each FIL class. For FIL6 we used a midpoint flame length of 100 feet to represent torching trees.Fire-effects flame-length probability rasters are used for effects analysis in a landscape wildfire risk assessment, as described in USFS GTR-315. Probability is calculated using non-heading fire behavior and is weighted according to WTP, incorporating both temporal frequencies and the influence of high-spread conditions. Raster resolution is 30m. Data finalized 11/17/2022.Ketchum, D., Jencso, K., Maneta, M.P., Melton, F., Jones, M.O., Huntington, J., 2020. IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S. Remote Sensing 12, 2328. https://doi.org/10.3390/rs12142328

Service Item Id: 1f24ba69b7d242a3934cec3b7408bd44

Copyright Text: Primary data contact: Ian Rickert (Regional Fire Management Planning Specialist) ian.rickert@usda.govThis dataset was developed for The USFS Pacific Northwest Region (R6) by Pyrologix LLC (www.pyrologix.com), and modified for use in the QWRA by Oregon State University, College of Forestry (andy.mcevoy@oregonstate.edu).

Spatial Reference: 102100 (3857)

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LibraryData/library_env_or_wildfire_average_flame_length_2023 (MapServer)