Simulation of short-term post-fire vegetation recovery by integration of LANDFIRE data products, DNBR data and LANDIS modeling

Abstract

This study developed an approach to simulate short-term post-fire vegetation recovery by integration of LANDFIRE data products, the differenced normalized burn ratio (DNBR) data, and LANDISv4.0a modeling. Combination of DNBR and LANDFIRE data products provided information on burn severity, pre-fire existing vegetation types, vegetation composition and structure, and the biophysical gradients that affect the distribution of ecosystem components. Such critical information established the initial states for LANDIS parameterization and simulation modeling. We tested the simulation at the Sanford Fire site, which is within the Dixie National Forest in Utah state and has 31,579 hectares of burned forested land by a 2002 wildfire. The simulation was at 30-meter cell size, at one-year time interval, and at 10-year duration. The results indicated that integration of LANDFIRE data products, DNBR data, and LANDISv4.0a modeling provided the necessary data sets and modeling mechanism for updating vegetation maps affected by wildfires. © 2009 Taylor & Francis Group, LLC.