Study of the 1997 Borneo fires: Quantitative analysis using global area coverage (GAC) satellite data

作者: M. J. Wooster , N. Strub

DOI: 10.1029/2000GB001357

关键词: MeteorologyPhysical geographyFar EastRainforestMonsoonAdvanced very-high-resolution radiometerPeat swamp forestVegetationEnvironmental scienceLand coverAgricultural land

摘要: [1] In 1997 a drought commenced in Southeast Asia, this being directly related to the then ongoing El Nino-Southern Oscillation (ENSO) event. Interaction between land clearance activities and led massive, uncontrolled vegetation fires that burned large areas of forest agricultural land, most severely on Indonesian island Borneo. A similar situation 1982–1983 largest fire ever documented, damaging around 50,000 km2 Borneo's forest. This paper investigates extent which nighttime advanced very high resolution radiometer (AVHRR) global area coverage (GAC) data can be used detail spatial temporal evolution these large-scale events, particularly activity. GAC are subsample full local (LAC) AVHRR data, but unlike LAC, they have been archived globally daily basis for almost 20 years. Despite extreme subsampling involved production, simulation modeling analysis real indicates surprisingly reliable statistics obtained Borneo event from imagery. For three dates October where coincident LAC available, once numerical adjustment procedure is included, counts extracted consistently agree within 0.15–13%. Time series began July south Kalimantan, principally at interface cleared, cultivated lowland rain Fire activity moved generally southward peaked September 1997. show equivalent 9733 pixels as containing one or more active 2 September. declined significantly November owing onset monsoon rains, with all ceasing by December Analysis cumulative map distinguishes peat swamp affected ecosystem Borneo, >20% cover category identified impacted fires. If performance shown extend other Nino years also less intense periods burning, archive offers tool analyzing long-term changes spatiotemporal pattern region. Any trend investigated its relation variations agriculture, Nino-related climate, phenomena relevant regional change Asia.

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