Impacts of land use and fire on the loss and degradation of lowland forest in 1983–2000 in East Kutai District, East Kalimantan, Indonesia
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Dennis, R.A., Colfer, C.J.P. 2006. Impacts of land use and fire on the loss and degradation of lowland forest in 1983–2000 in East Kutai District, East Kalimantan, Indonesia . Singapore Journal of Tropical Geography 27 :30-48. ISSN: 0129-7619.
Permanent link to this item: http://hdl.handle.net/10568/19404
Deforestation and forest degradation are proceeding rapidly in the lowland forests of Indonesian Borneo. Time series analysis of satellite imagery provides an ideal means of quantifying landscape change and identifying the pathways which lead to the changes. This study investigates the forest and land cover changes by classifying Landsat MSS (Multispectral Scanner), TM (Thematic Mapper) and ETM + (Enhanced Thematic Mapper Plus) images over three time periods (1983–90, 1990–98, and 1998–2000), creating land cover maps for each year and change trajectories for each year-pair. The study area chosen covers an area of 2160 km 2 of undulating topography and alluvial plains in the East Kutai District of East Kalimantan Province, which in the 1980s was covered mostly with lowland dipterocarp forest; today the landscape is a patchwork dominated by oil palm and timber plantations and degraded forest. We relate land cover change data to land use allocation and to fire impacts based on fire hotspot distribution and fire damage information. The multidate land cover change trajectories provide an insight into the forest loss and degradation pathways over the 17-year period spanning the first entry of commercial logging concessionaires, followed by a governmentsponsored transmigration scheme, government-licensed timber and oil palm plantations and, finally, the devastating fires of 1998. The results show a mean deforestation rate of 42 km 2 or 6 per cent per year for 1983–2000, rising to 10 per cent per year for 1990–98; by 2000, 70 per cent of forest initially damaged by fire and drought during the 1982–83 El Niño event was classified as non-forest. Although our study area is perhaps a worst-case scenario in terms of land use planning outcomes, the lessons from this research are directly applicable to scenario prediction for informed forest and land use planning and monitoring.