Utilizing Multi-Temporal ALOS/PALSAR Backscatter Data to Detect Deforestation in the Indonesian Tropical Forest

Abstract

Deforestation detection mapping has been analyzed using Synthetic Aperture Radar (SAR) data from the ALOS PALSAR satellite. SAR is a promising tool for deforestation mapping in tropical forest regions because microwave energy can penetrate clouds. This study examined the effect of SAR polarization on the accuracy of deforestation mapping and the seasonal variation of radar backscattering values in Riau Province, Indonesia. Image differencing was used to determine the threshold value for distinguishing between forest and non-forest areas. The difference between HV (horizontal transmit-vertical receive) and HH (horizontal transmit-horizontal receive) polarization was used as the discriminant variable. The correlation between radar backscattering value and accumulated rainfall was also analyzed to assess the effect of seasonal change. The findings demonstrated that the accuracy of deforestation detection mapping using HV polarization outperforms that achieved with HH polarization. Moreover, seasonal variations in rainfall were observed to influence radar backscatter signatures in bare soil, acacia, and oil palm, though no such influence was detected in forested areas. The accuracy of deforestation detection mapping, employing the thresholding method, reached a rate of 92.21%. During the period from November 2007 to July 2009, forested areas in Riau experienced a reduction, decreasing to 6.77%, and further decreasing to 6.08% by October 2010.