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Estimation of Forest Fire Emission in Thailand by Using Remote Sensing Information

<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/4402" mdate="2011-10-28 00:00:00"> <author>A. Junpen and S. Garivait and S. Bonnet and A. Pongpullponsak</author> <title>Estimation of Forest Fire Emission in Thailand by Using Remote Sensing Information</title> <pages>604 - 612</pages> <year>2011</year> <volume>5</volume> <number>10</number> <journal>International Journal of Geological and Environmental Engineering</journal> <ee>https://publications.waset.org/pdf/4402</ee> <url>https://publications.waset.org/vol/58</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 20052009 using MODerateresolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80 of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country. </abstract> <index>Open Science Index 58, 2011</index> </article>