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Keyword: Landfire

A case study comparison of landfire fuel loading and emissions generation on a mixed conifer forest in northern Idaho, USA

Publications Posted on: January 21, 2016
The use of fire as a land management tool is well recognized for its ecological benefits in many natural systems. To continue to use fire while complying with air quality regulations, land managers are often tasked with modeling emissions from fire during the planning process.

Automated integration of lidar into the LANDFIRE product suite

Publications Posted on: October 07, 2015
Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure.

Utilizing random forests imputation of forest plot data for landscape-level wildfire analyses

Publications Posted on: October 05, 2015
Maps of the number, size, and species of trees in forests across the United States are desirable for a number of applications. For landscape-level fire and forest simulations that use the Forest Vegetation Simulator (FVS), a spatial tree-level dataset, or “tree list”, is a necessity.

Assessing the expected effects of wildfire on vegetation condition on the Bridger-Teton National Forest, Wyoming, USA

Publications Posted on: November 17, 2014
Characterizing wildfire risk to a fire-adapted ecosystem presents particular challenges due to its broad spatial extent, inherent complexity, and the difficulty in defining wildfire-induced losses and benefits. Our approach couples stochastic wildfire simulation with a vegetation condition assessment framework to estimate the conditional and expected response of vegetation condition to wildfire.

LANDFIRE - A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning

Publications Posted on: July 30, 2013
LANDFIRE is the working name given to the Landscape Fire and Resource Management Planning Tools Project (

Extent of coterminous US rangelands: Quantifying implications of differing agency perspectives

Publications Posted on: October 01, 2012
Rangeland extent is an important factor for evaluating critical indicators of rangeland sustainability.

Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

Publications Posted on: July 18, 2012
Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure.

A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the southeastern United States

Publications Posted on: May 01, 2012
Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation System.

Tools, courses, and learning pathways offered by the National Interagency Fuels, Fire, and Vegetation Technology Transfer

Publications Posted on: October 07, 2011
Technological advances in the area of fuel and wildland fire management have created a need for effective decision support tools and technology training.

Monitoring landscape change for LANDFIRE using multi-temporal satellite imagery and ancillary data

Publications Posted on: October 07, 2011
LANDFIRE is a large interagency project designed to provide nationwide spatial data for fire management applications. As part of the effort, many 2000 vintage Landsat Thematic Mapper and Enhanced Thematic Mapper plus data sets were used in conjunction with a large volume of field information to generate detailed vegetation type and structure data sets for the entire United States.