Abstract
Dynamic Wildfire Risk Mapping: Challenges and Solutions Track: EMS/Fire Author(s): Noah Goldstein, Max Moritz, Faith Kearns Mapping wildfire risk is crucial for planning, government and civilian groups as more homes and communities are being threatened by wildfire. A common approach to understanding the risk of wildfires is to do a simple map overlay and determine which regions are in danger. This static deterministic method, while quick to produce, cannot account for new and novel data sources and modeling approaches. This work presents two complementary approaches to mapping dynamic wildfire risk. The first is a stochastic coupled wildfire risk/urban growth model called Vesta, which can be used to forecast risk under different development and management scenarios. The second is the Fire Information Engine, a product of the University of California Berkeley Center for Fire Research and Outreach, which produces user-defined Web maps of localized wildfire risk to structures. The Fire Information Engine incorporates newly collected field data and can be used to compare different risk assessment strategies. Noah Goldstein Lawrence Livermore National Laboratory Systems & Decision Sciences 7000 East Ave., L-644 Livermore , CA 94551 US Phone: (925) 423-3916 E-mail: goldstein8@llnl.gov Max Moritz College of Natural Resources Center for Fire Research and Outreach 137 Mulford Hall ##3114 UC Berkeley Berkeley , CA 94720 US Phone: 510-642-7329 E-mail: mmoritz@nature.berkeley.edu Faith Kearns College of Natural Resources Center for Fire Research and Outreach 137 Mulford Hall ##3114 UC Berkeley Berkeley , CA 94720 US Phone: (510) 643-0409 E-mail: fkearns@nature.berkeley.edu |
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