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Layer: Annual burn probability 300m normalized (ID: 42)

Parent Layer: Functional

Name: Annual burn probability 300m normalized

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Type: Raster Layer

Geometry Type: null

Description: Annual Burn Probability represents the likelihood of a wildfire of any intensity occurring at a given location (pixel) in a single fire season. In a complete assessment of wildfire hazard, wildfire occurrence and spread are simulated in order to characterize how temporal variability in weather and spatial variability in fuel, topography, and ignition density influence wildfire likelihood across a landscape. In such cases, the hazard assessment includes modeling of burn probability, which quantifies the likelihood that a wildfire will burn a given point (a single grid cell or pixel) during a specified period of time. Burn probability for fire management planning applications in this case is reported on an annual basis - the probability of burning during a single fire season.----------------This raster has been modified from the base 30m version in the following ways:-------- - It has been aggregated from a 30m to a 300m scale by averaging across the 30m values-------- - The normalized values are rescaled based on the full range of actual values, with -1 representing high values, and 1 representing low values. This interpretation reflects concerns for the occurrence of unplanned fire, so lower probabilities are considered more favorable.----------------- Unit Of Measure: Probability, 0 to 1

Copyright Text: Pyrologix, LLC: Primary data contact: James Newman (California State BLM Office) jnewman@blm.gov. This 2022 dataset is an update produced by Pyrologix (pyrologix.com) for the Bureau of Land Management (BLM) California State Office. The original 2020 dataset was developed by Pyrologix for the USFS Pacific Southwest Region. Scott, Joe H.; Thompson, Matthew P.; Calkin, David E. 2013. A wildfire risk assessment framework for land and resource management. Gen. Tech. Rep. RMRS-GTR-315. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 83 p

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