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      The collection 6 MODIS active fire detection algorithm and fire products

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      , ,
      Remote sensing of environment
      Fire, Biomass burning, MODIS

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          Abstract

          The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, on-board NASA’s Terra and Aqua satellites, have provided more than a decade of global fire data. Here we describe improvements made to the fire detection algorithm and swath-level product that were implemented as part of the Collection 6 land-product reprocessing, which commenced in May 2015. The updated algorithm is intended to address limitations observed with the previous Collection 5 fire product, notably the occurrence of false alarms caused by small forest clearings, and the omission of large fires obscured by thick smoke. Processing was also expanded to oceans and other large water bodies to facilitate monitoring of offshore gas flaring. Additionally, fire radiative power (FRP) is now retrieved using a radiance-based approach, generally decreasing FRP for all but the comparatively small fraction of high intensity fire pixels. We performed a Stage-3 validation of the Collection 5 and Collection 6 Terra MODIS fire products using reference fire maps derived from more than 2500 high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. Our results indicated targeted improvements in the performance of the Collection 6 active fire detection algorithm compared to Collection 5, with reduced omission errors over large fires, and reduced false alarm rates in tropical ecosystems. Overall, the MOD14 Collection 6 daytime global commission error was 1.2%, compared to 2.4% in Collection 5. Regionally, the probability of detection for Collection 6 exhibited a ~3% absolute increase in Boreal North America and Boreal Asia compared to Collection 5, a ~1% absolute increase in Equatorial Asia and Central Asia, a ~1% absolute decrease in South America above the Equator, and little or no change in the remaining regions considered. Not unexpectedly, the observed variability in the probability of detection was strongly driven by regional differences in fire size. Overall, there was a net improvement in Collection 6 algorithm performance globally.

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          An overview of MODIS Land data processing and product status

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            The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment

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              Assessing variability and long-term trends in burned area by merging multiple satellite fire products

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                Author and article information

                Journal
                101572538
                39696
                Remote Sens Environ
                Remote Sens Environ
                Remote sensing of environment
                0034-4257
                1879-0704
                15 August 2018
                11 March 2016
                1 June 2016
                27 August 2018
                : 178
                : 31-41
                Affiliations
                Department of Geographical Sciences, University of Maryland, College Park, MD, USA
                Author notes
                [* ]Corresponding author at: Department of Geographical Sciences, University of Maryland, 2181 LeFrak Hall, College Park, MD 20742, USA
                Article
                NASAPA984364
                10.1016/j.rse.2016.02.054
                6110110
                30158718
                7323e8cd-c4f8-406b-97dd-21e601b17660

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

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                fire,biomass burning,modis
                fire, biomass burning, modis

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