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. Mapping spatial distributions of tropical peatlands is important for properly estimating carbon emissions and for providing information that aids in the sustainable management of tropical peatlands, particularly in Indonesia. This study evaluated the performance of phased array type L-band synthetic aperture radar (SAR) (PALSAR) dual-polarization and fully polarimetric data for tropical peatlands classification. The study area was in Siak River Transect, Riau Province, Indonesia, a rapidly developing region, where the peatland has been intensively converted mostly into oil palm plantations over the last two decades. Thus, polarimetric features derived after polarimetric decompositions, backscatter coefficients measurements, and the radar vegetation index were evaluated to classify tropical peatlands using the decision tree classifier. Overall, polarimetric features generated by the combination of dual-polarization and fully polarimetric data yielded an overall accuracy (OA) of 69% and a kappa coefficient (K) of 0.57. The integration of an additional feature, “distance to river,” to the algorithm increased the OA to 76% and K to 0.66. These results indicated that the methodology in this study might serve as an efficient tool in tropical peatlands classification, especially when involving the use of L-band SAR dual-polarization and fully polarimetric data.

Polarimetric synthetic aperture radar application for tropical peatlands classification: a case study in Siak River Transect, Riau Province, Indonesia