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Polarimetric and Interferometric Airborne SAR in L-band 2 (PiSAR-L2) program is an experimental program of PALSAR-2 sensorin ALOS-2 satellite. Japan Aerospace Exploration Agency (JAXA) and Indonesian National Institute of Aeronautics and Space(LAPAN) have a research collaboration to explore the utilization of PiSAR-L2 data for forestry, agriculture, and disasterapplications in Indonesia. The research explored the utilization of PiSAR-L2 data for land cover classification in forest area usingthe pixel-based and object-based methods. The PiSAR-L2 data in the 2.1 level with full polarization bands were selected over part offorest area in Riau Province. Field data collected by JAXA team was used for both training samples and verification data. Preprocessingdata was carried out by backscatter (Sigma naught) conversion and Lee filtering. Beside full polarization images (HH,HV, VV), texture imagess (HH deviation, HV deviation, and VV deviation) were also added as the input bands for the classificationprocesses. These processes were conducted for 2.5 meter and 10 meter spatial resolution data applying two methods of the maximumlikelihood classifier for pixel-based classification and the support vector machine classifier for the object-based classification.Moreover, the average overall accuracy was calculated for each classification result. The results show that the use of texture imagescould improve the accuracy of land cover classification, particularly to differentiate between forest and acacia plantation. The pixelbasedmethod showed a more detail information of the objects, but has “salt and pepper”. In the other hand, the object-based methodshowed a good accuracy and clearer border line among objects, but has often some misinterpretations in object identification

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Utilization of Pisar L-2 Data for Land Cover Classification in Forest Area Using Pixel-Based and Object-Based Methods