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Forecasting distribution of numbers of large fires

Systems to estimate forest fire potential commonly utilize one or more indexes that relate to expected fire behavior; however they indicate neither the chance that a large fire will occur, nor the expected number of large fires. That is, they do not quantify the probabilistic nature of fire danger. In this work we use large fire occurrence information from the Monitoring Trends in Burn Severity pr
Jeffery C. Eidenshink, Haiganoush K. Preisler, Stephen Howard, Robert E. Burgan

United States Geological Survey fire science: Fire danger monitoring and forecasting

Each day, the U.S. Geological Survey produces 7-day forecasts for all Federal lands of the distributions of number of ignitions, number of fires above a given size, and conditional probabilities of fires growing larger than a specified size. The large fire probability map is an estimate of the likelihood that ignitions will become large fires. The large fire forecast map is a probability estimate
Jeff C. Eidenshink, Stephen M. Howard

Forecasting distributions of large federal-lands fires utilizing satellite and gridded weather information

The current study presents a statistical model for assessing the skill of fire danger indices and for forecasting the distribution of the expected numbers of large fires over a given region and for the upcoming week. The procedure permits development of daily maps that forecast, for the forthcoming week and within federal lands, percentiles of the distributions of (i) number of ignitions; (ii) num
H.K. Preisler, R.E. Burgan, J.C. Eidenshink, Jacqueline M. Klaver, R. W. Klaver

USGS Fire Science: Fire Danger Monitoring and Forecasting

The U.S. Geological Survey (USGS) has advanced the use of moderate-resolution satellite data in a decision support system for assessing national fire potential. Weekly updated digital images of the Normalized Difference Vegetation Index (NDVI), based on data acquired at 1-kilometer (km) resolution (about 0.6 mi), have been used for the past 19 years as a means to assess live vegetation conditions
Jeff Eidenshink

Introduction to fire danger rating and remote sensing - Will remote sensing enhance wildland fire danger prediction?

While ‘Fire Danger’ per se cannot be measured, the physical properties of the biotic and abiotic world that relate to fire occurrence and fire behavior can. Today, increasingly sophisticated Remote Sensing methods are being developed to more accurately detect fuel properties such as species composition (fuel types), vegetation structure or plant water content - to name a few. Based on meteorologic
Britta Allgöwer, J.D. Carlson, Jan W. Van Wagtendonk