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Layer: Potential Total Smoke Production Index (ID: 0)

Name: Potential Total Smoke Production Index

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Type: Raster Layer

Geometry Type: null

Description: - Metric Name: Potential Total Smoke Production Index - Tier: 1 - Data Vintage: 2022 - Unit Of Measure: 0 - 1, strong, a unitless number serving as an index; on a per 30-m pixel basis - Metric Definition and Relevance: This metric is an index of the potential smoke production (represented by particulate matter that is 2.5 microns or less in diameter, or PM, sub, ) that could be emitted for a given 30-meter pixel under fire weather conditions that produce high severity fire effects. By showing spatial variation in potential smoke emissions under standardized fuel moisture conditions, this index is intended to help identify potential emissions hotpots within a region if a high severity wildfire occurs in the future. It may be useful for regional scale planning and/or prioritization., p, p, - Creation Method: Potential TOTAL smoke production index is the smoke production expected for a given pixel under severe fire weather conditions. It is based on model outputs from the First Order Fire Effects Model (FOFEM) developed by the U.S. Forest Service (Spatial FOFEM: https://www.firelab.org/project/fofem-fire-effects-model). Key drivers (and model inputs) for this mapped variation are (1) fuel loads spatially extracted from the Landfire FCCS modeled fuelbeds map (LANDFIRE 2022 Update (LF 2.3.0),, a, ), and (2) fuel moistures, which are assigned to approximate the extremely dry conditions under which high severity fire generally occurs. The data are dimensionless and linearly normalized from 0 to 1 based on the statewide maximum value, with 1 being the maximum PM, sub, emissions per 30-m pixel for the given region. Fuels are taken from LANDFIRE LF2022_FCCS_220. Spatial FOFEM was run as implemented in FlamMap 6.2 (https://www.firelab.org/project/flammap)., p, p, p, p, p, p, p, p, p, p, p, p, p

Service Item Id: 2ecc06cca0d24288ace18f29c1c4f2d6

Copyright Text: LANDFIRE FCCS ([LANDFIRE Program: Data Products – Fuel – Fuel Characteristic Classification System Fuelbeds](https://www.landfire.gov/fccs.php)) 2022 Rocky Mountain Research Station https://www.firelab.org/project/fofem-fire- effects-model

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Supported Query Formats: JSON, geoJSON, PBF

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