<![CDATA[Spatial information on small scale gold mining activities and its impact to the forest are still scarce. The research objective was to develop practical remote sensing method for mining activities monitoring in forest area especially in identifying gold mining location and asses forest cover changes (deforestation, forest degradation, regrowth) due to gold mining in Gunung Pani forest area, Gorontalo Province, Celebes. Landsat imagery were chosen since Landsat is a continuous and free remote sensing program which enable a sustainable and practical monitoring. Using Landsat imagery facing some obstacles such as inadequate spatial resolution and SLC-off of the Landsat 7 imagery. A multi-temporal Landsat imageries recorded in 2000, 2003and 2013 were used. The 30 meter Landsat imageries were pan-sharpened in order to increase its spatial resolution. Some pan-sharpening methode were explored and evaluated. Supervised classifications were applied to the best pan sarphened images. Spatial analysis by means of GIS was conducted in order to identify mining location and to assess forest cover change. High spatial resolution imagery of QuickBird was used as a reference to improve derived information quality and to reduce volume of the ground check activities. The results showed that Landsat 7 continued by Landsat 8 system provide continuous and valuable data for mining monitoring in the forest area. The developed methods proved that it is practically possible to assess forest cover changes due to mining activities. Small-scale mining areas were possible to be identified by combining remote sensing methods and GIS analysis. Key word: deforestation, degradation, gold mining, Gunung Pani, Landsat imager.]]>
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