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Satellite active fire data have been produced routinely for over two decades. Fire detection products are currently derived from both polar and geostationary systems with spatial resolutions normally ranging from 1-4km, and temporal resolution ranging from 15min to 12h. Due to the spectral characteristics of active fires, satellite fire detection algorithms using middle and thermal infrared data can discern fires from the background even when those occupy a relatively small fraction (0.01%) of the pixel footprint. However, comprehensive validation analyses implemented for the EOS Terra/MODIS fire product suggested that instantaneous omission errors can still be considerably large (as much as 80%). Those same validation studies indicated the vast majority of fires detected by 1km resolution MODIS data are sub-pixel in nature. Therefore the ability to spatially resolve these fires is significantly compromised when using coarse spatial resolution satellite data. The availability of high quality Landsat-class data is expected to increase significantly in the upcoming years with the launch of the Landsat Data Continuity Mission (LDCM) and the European Space Agency (ESA) Sentinal-2 A and B sensors. The spatial resolution of these data will range from 10-20m for the visible and short-wave infrared bands and their application for active fire mapping has already been extensively demonstrated by the proposing team. In addition to the Landsat-class data, other moderate spatial resolution fire data sets are expected to go online in the next 2-3 years. Those include an active fire mask to be derived from the NPOESS Preparatory Project Visible Infrared Imager Radiometer Suite 375m bands and a fully developed 356m fire detection and characterization product developed for the German Aerospace Center (DLR) FireBIRD constellation of small satellites, with the first sensor (TET-1) to be launched in 2012, and the second (BIROS) to be launched in 2013. Here we propose to take advantage of these new satellite sensors implementing a suite of active detection data at spatial resolutions ranging from 20-375m, with a frequency of 2-4 overpasses a day for any location in the CONUS region and Alaska. Complementing the use of satellite data this project will apply the Coupled Atmosphere Wildland Fire Environment (CAWFE) model, which combines a numerical weather prediction and fire behavior model. CAWFE will provide sophisticated fire diagnostic and predictive tools including the innovative option to assimilate the satellite-derived fire data. By partnering with the USDA Forest Service, we will seek user support and work to meet their requirements for successful transition of science products into operations. The project will serve the following main applications: (i)Improve routine fire monitoring and management; (ii)Provide value-added data for initialization of fire spread and behavior models; (iii)Improve fire tactical applications and decision making The application of a new suite of improved satellite active fire products in combination with a sophisticated and innovative fire modeling framework will address the two primary objectives of this solicitation by (i) enhancing the performance of existing decision-making through the use of integrated Earth observation data and (ii) by developing new capabilities for decision-making. The work being proposed is anticipated to directly affect two primary Societal Benefit Areas, namely Disasters and Health/Air Quality. Fire managers and practitioners will greatly benefit from the spatially refined near real-time satellite fire data, whereas improvements in fire modeling capabilities will provide enhanced predictive skills of smoke emissions and transport from individual wildfires occurring near populated areas and sensitive airsheds.