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Keyword: burn probability

Wildfire Hazard Potential (WHP) for the conterminous United States (270-m GRID), version 2018 continuous (2nd Edition)

Datasets Posted on: December 30, 2020
Federal wildfire managers often want to know, over large landscapes, where wildfires are likely to occur and how intense they may be. To meet this need we developed a map that we call wildfire hazard potential (WHP) – a raster geospatial product that can help to inform evaluations of wildfire risk or prioritization of fuels management needs across very large spatial scales (millions of acres).

Wildfire Hazard Potential (WHP) for the conterminous United States (270-m GRID), version 2018 classified (2nd Edition)

Datasets Posted on: December 30, 2020
Federal wildfire managers often want to know, over large landscapes, where wildfires are likely to occur and how intense they may be. To meet this need we developed a map that we call wildfire hazard potential (WHP) – a raster geospatial product that can help to inform evaluations of wildfire risk or prioritization of fuels management needs across very large spatial scales (millions of acres).

Spatial datasets of probabilistic wildfire risk components for the United States (270m) (2nd Edition)

Datasets Posted on: December 30, 2020
National data on burn probability (BP) and conditional flame-length probability (FLP) 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 (Finney et al. 2011). The FSim system includes modules for weather generation, wildfire occurrence, fire growth, and fire suppression.

Wildfire Hazard Potential for the United States (270-m), version 2020 (3rd Edition)

Datasets Posted on: December 30, 2020
This dataset is the 2020 version of wildfire hazard potential (WHP) for the United States. The files included in this data publication represent an update to any previous versions of WHP or wildland fire potential (WFP) published by the USDA Forest Service. WHP is an index that quantifies the relative potential for wildfire that may be difficult to control, used as a measure to help prioritize where fuel treatments may be needed.

Wildfire Risk to Communities: Spatial datasets of landscape-wide wildfire risk components for the United States

Datasets Posted on: December 30, 2020
The data included in this publication depict components of wildfire risk for all lands in the United States that: 1) are landscape-wide (i.e., measurable at every pixel across the landscape); and 2) represent in situ risk – risk at the location where the adverse effects take place on the landscape.

Wildfire Risk to Communities: Spatial datasets of wildfire risk for populated areas in the United States

Datasets Posted on: December 30, 2020
The data included in this publication depict components of wildfire risk specifically for populated areas in the United States. These datasets represent where people live in the United States and the in situ risk from wildfire, i.e., the risk at the location where the adverse effects take place. Related datasets representing components of risk across the entire landscape are available in a separate data publication (Scott et al.

Commentary on the article “Burn probability simulation and subsequent wildland fire activity in Alberta, Canada - Implications for risk assessment and strategic planning” by J.L. Beverly and N. McLoughlin

Publications Posted on: August 16, 2020
Monte Carlo simulations using wildland fire spread models have been conducted to produce numerical estimates of fire likelihood, project potential fire effects, and produce event sets of realistic wildfires (Parisien et al., 2019). The application of these methods has greatly expanded over the last few decades as a result of increased computation capabilities, available data, and our fundamental understanding of landscape fire dynamics.

A wildfire risk assessment framework for land and resource management

Publications Posted on: June 07, 2018
Wildfires can result in significant, long-lasting impacts to ecological, social, and economic systems. It is necessary, therefore, to identify and understand the risks posed by wildland fire, and to develop cost-effective mitigation strategies accordingly. This report presents a general framework with which to assess wildfire risk and explore mitigation options, and illustrates a process for implementing the framework.

Spatial dataset of probabilistic wildfire risk components for the conterminous United States (1st Edition)

Datasets Posted on: March 15, 2018
National burn probability (BP) and conditional fire intensity level (FIL) data were generated for the conterminous United States (US) using a geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. [2011]). The FSim system includes modules for weather generation, wildfire occurrence, fire growth, and fire suppression.

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