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We present a method for estimating monthly burned area globally at1° spatial resolution using Terra MODIS data andancillary vegetation coverinformation.  Using regression trees constructed for 14 different globalregions, MODIS active fire observations were calibrated to burned areaestimates derived from 500-m MODIS imagery based on the assumptionthat burned area is proportional to counts of fire pixels.  Unlike earliermethods, we allow the constant of proportionality to vary as a function of treeand herbaceous vegetation cover, and the mean size of monthly cumulativefire-pixel clusters.  In areas undergoing active deforestation, we implementeda subsequent correction based on tree cover information and a simple measure offire persistence.  Regions showing good agreement between predicted andobserved burned area included Boreal Asia, Central Asia, Europe, and TemperateNorth America, where the estimates produced by the regression trees wererelatively accurate and precise.  Poorest agreement was found forsouthern-hemisphere South America, where predicted values of burned area areboth inaccurate and imprecise; this is most likely a consequence of multiplefactors that include extremely persistent cloud cover, and lowerquality of the 500-m burned area maps used for calibration.  Application of ourapproach to the nine remaining  regions yielded comparatively accurate, butless precise, estimates of monthly burned area.  We applied the regionalregression trees to the entire archive of Terra MODIS fire data to produce amonthly global burned area data set spanning late 2000 through mid-2005.Annual totals derived from this approach showed good agreement with independentannual estimates available for nine Canadian provinces, the UnitedStates, and Russia.  With our data set we estimate the global annual burnedarea for the years 2001-2004 to vary between 2.97 million and3.74 million km<sup>2</sup>,with the maximum occurring in 2001.  These coarse-resolution burned areaestimates may serve as a useful interim product until long-term burned areadata sets from multiple sensors and retrieval approaches become available

Global estimation of burned area using MODIS active fire observations