Satellite Data Applications for Fire Science
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The convergence of plentiful dry wildland fuels and weather favorable for fire ignition and spread signifies high potential for uncharacteristically large and dangerous fires. The ability to characterize the potential for hazardous fire activity requires measurements of fuel condition combined with information from weather forecasts. The availability of long fire histories adds a third dimension, fire probability, which can improve the ability to develop weekly forecasts of the location and number of large fires over a given region (Preisler et. al. 2008).
The USGS uses moderate resolution satellite data to assess live fuel condition for estimating fire danger. Using 23 years of vegetation condition measurements, we are able to determine the relative greenness of current live fuels. High relative greenness values indicate that the vegetation is healthy and vigorous. Low greenness values indicate that the vegetation is under stress, dry (possibly from drought), is behind in annual development, or dead. Forest, shrub, and grassland vegetation with low relative greenness is susceptible to fire ignition during the fire season.
The fire potential index (FPI) integrates weather information from the National Digital Forecast Database and satellite derived vegetation condition information and is used to identify the areas most susceptible to fire ignition (Burgan et.al. 1998). The combination of relative greenness and weather information provides an estimate of the moisture condition of the live and dead vegetation. The FPI is most similar to the Energy Release Component of the National Fire Danger Rating System in that both are moisture-related indexes and neither indicates the effect of wind on fire potential. The FPI indicates the estimated proportion (percentage) of the vegetation that is dry enough to burn, thus the FPI is highest when dead fuel moisture and vegetation greenness are low. The FPI provides local and regional fire planners a quantitative measure of fire ignition risk. Read a description of the current FPI processing flow.
Each day, the U.S. Geological Survey (USGS) in collaboration with the U.S. Forest Service produces 7 day forecasts for all lands. The forecasts are based on historical fire occurrence, current weather and fuels condition. The conditional probability map is an estimate of the likelihood that ignitions will become large fires, given existing levels of the fire danger variables. The large fire forecast map is a probability estimate of the number of fires within a Predictive Service Area exceeding 1000 acres in the forthcoming week. We also produce graphs of total number of expected fires >100 in federal lands per GACC versus day in year.
USGS Fire Danger Forecast Viewer
U.S. Forest Service Wildland Fire Assessment System
United States Geological Survey Fire Science—Fire Danger Monitoring and Forecasting
Preisler, H., R. Burgan, J. Eidenshink, J. Klaver, and B. Klaver (2009), Forecasting distributions of large federal-lands fires utilizing satellite and gridded weather information. International Journal of Wildland Fire 18, 508–516.
Burgan RE, Klaver RW, Klaver JM (1998), Fuel models and fire potential from satellite and surface observations. International Journal of Wildland Fire 8(3), 159–170. doi:10.1071/WF9980159
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