Forest fire spot extraction algorithm based on FY-3D/MERSI-Ⅱ and Terra/MODIS data—Taking southwest China as an example
The southwest China has a high forest coverage,complex land use,and frequent human activities,resulting in a high risk of forest fires and a heavy burden on fire prevention tasks.Remote sensing technology,with its capability for extensive and periodic observations,is widely used in monitoring forest fires.Meteorolog-ical satellites equipped with infrared sensors sensitive to fires and high temporal resolution have become impor-tant remote sensing data sources for forest fire monitoring.The physical threshold method is a relatively mature algorithm for remote fire point extraction,but its accuracy is significantly influenced by the chosen threshold,leading to variations on fire point extraction accuracy in different regions.In this study,the FY-3D/MERSI-Ⅱand Terra/MODIS polar-orbiting satellites were used as data sources for forest fire point monitoring in Chongqing City of southwestern China.Through an analysis of historical data from the previous year's MOD14 monitoring product,regional background thresholds were determined.The context background threshold method was then applied for fire point extraction,with the removal of cloud,water,and solar glare interference.An analysis of Chongqing City forest fire in August 2022 using this method yielded an average fire point extraction accuracy ex-ceeding 90%.The research results indicate that adjusting the threshold according to regional characteristics can improve the accuracy of fire point monitoring in this area.
forest fire monitoringFY-3D/MERSI-ⅡTerra/MOD14fire point extractioncontextual back-ground threshould methodthreshold selection
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