PEMANFAATAN KANAL POLARISASI DAN KANAL TEKSTUR DATA PISAR-L2 UNTUK KLASIFIKASI PENUTUP LAHAN KAWASAN HUTAN DENGAN METODE KLASIFIKASI TERBIMBING

Abstract

Polarimetric and Interferometric Airborne SAR in L band (PiSAR-L2) is an upgraded PiSAR program, which has a purpose for experimental activities of PALSAR-2 sensor equiped by ALOS-2 in 2013. Japan Aerospace Exploration Agency (JAXA) and Ministry of Reseach and Technology Indonesia have collaborated to explore the utilization PiSAR-L2 data for some applications in Indonesia. The purpose of this research is to utilize full polarimetric band of PiSAR-L2 data to classify land cover of forest area in Riau province. Field data conducted by JAXA team was used as reference data to collect input and verification training samples. SAR data pre-processing was conducted by doing backscatter conversion (digital number to Sigma naught) and filtering process using Lee filter. Classification was carried out by Maximum Likelihood classifier using Maximum Likelihood Enhanced Neighbour method. The research used three treatments for input data, using three SAR polarization bands (HH, VV and HV), and using six bands (three SAR polarization bands and three texture bands (deviation HH, VV and HV), and using six bands (three polarization dan 3 texture bands) with training samples improvement based on confusion matrix result. Verification of classification results were done using confusion matrix for each treatment. The result shows that texture band can enhance the degree of separation between object classes of vegetation, especially between forest and acacia plantation. Classification using six bands (three polarization dan 3 texture bands) with training sample improvement increased the overall accuracy and kappa statistic of the classification result to be 80% and 0.612 respectively.