NASA - National Aeronautics and Space Administration

Biomass burning patterns over the Maritime Continent of Southeast Asia are examined using a new active fire detection product based on application of the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to data from the imagers on the MTSAT geostationary satellites operated by the Japanese space agency JAXA. Data from MTSAT-1R and MTSAT-2 covering 34 months from September 2008 to July 2011 are examined for a study region consisting of Indonesia, Malaysia, and nearby environs. The spatial and temporal distributions of fires detected in the MTSAT WF_ABBA product are described and compared with active fire observations from MODIS MOD14 data. Land cover distributions for the two instruments are examined using a new 250 m land cover product from the National University of Singapore. The two products show broadly similar patterns of fire activity, land cover distribution of fires, and pixel fire radiative power (FRP). However, the MTSAT WF_ABBA data differ from MOD14 in important ways. Relative to MODIS, the MTSAT WF_ABBA product has lower overall detection efficiency, but more fires detected due to more frequent looks, a greater relative fraction of fires in forest and a lower relative fraction of fires in open areas, and significantly higher single-pixel retrieved FRP. The differences in land cover distribution and FRP between the MTSAT and MODIS products are shown to be qualitatively consistent with expectations based on pixel size and diurnal sampling. The MTSAT WF_ABBA data are used to calculate coverage-corrected diurnal cycles of fire for different regions within the study area. These diurnal cycles are preliminary but demonstrate that the fraction of diurnal fire activity sampled by the two MODIS sensors varies significantly by region and vegetation type. Based on the results from comparison of the two fire products, a series of steps is outlined to account for some of the systematic biases in each of these satellite products in order to produce a successful merged fire detection product.