Abstract
Live Fuel Moisture: Implications for Fire Prediction and Severity Models Track: EMS/Fire Author(s): Laura LaVoy, Jennifer Rechel Uncontained fires threaten wildlands and human habitations every year. Seasonal Live Fuel Moisture (LFM) is one indicator of the existence and severity of fire. LFM, when combined with other factors, can create a correlation model that can be displayed using a GIS, providing seasonal fire severity and predictions for wildland fire managers. Analysis of data through geodatabases housing the LFM and other data will reveal correlation models between the determinants. Difference maps can be produced to show the seasonal difference in fire risk and severity. This can be used to provide regional fire managers with seasonal difference maps in LFM for an ultimate goal of better preparedness for uncontrolled, uncontained wildland fire. To that end, production of repeatable, standard processes for the analysis of seasonal LFM data is necessary for achieving such a goal. Furthermore, all tools and geodatabases can be distributed through ArcIMS Web services. Laura LaVoy University of Redlands 1111 E Central Ave ##4 Redlands , CA 92374 US Phone: 678-860-0253 E-mail: laura_lavoy@institute.redlands.edu Jennifer Rechel USDA Forest Service 4955 Canyon Crest Drive Riverside , CA 92507-6071 US Phone: 951-680-1541 E-mail: jrechel@fs.fed.us |
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