Evaluation of Pan-sharpening Method: Applied to Artisanal Gold Mining Monitoring in Gunung Pani Forest Area

AbstractThe vast Indonesia's forests area and remote mining locations make it difficult for the implementation of terrestrial monitoring. The objective of the research was to develop relatively high accuracy and low cost remote sensing method for gold mining area monitoring in forest area. Landsat satellite images were chosen since Landsat is a continuous program and currently provide free source of images. A pan-sharpening method for enhancing satellite imagery is proposed as an important step for developing a relatively high accuracy and low cost approach for image-based analysis of mining areas. Eight different pan-sharpening methods were evaluated including: PCA, IHS, PCA, Multiplicative, Wavelet, Brovey, Ehlers, Gram-Schmidt and ESRI. The visual evaluations followed by a quantitative examination were performed. Visual evaluation shows two algorithms outperform all the others which were Modified IHS and Principal Component