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

Bambang Trisakti and Ahmad Sutanto and Heru Noviar and Kustiyo (2015) Utilization of Pisar L-2 Data for Land Cover Classification in Forest Area using Pixel-Based and Object-Based Methods. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL (7). pp. 525-529.

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Polarimetric and Interferometric Airborne SAR in L-band 2 (PiSAR-L2) program is an experimental program of PALSAR-2 sensor in 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 disaster applications in Indonesia. The research explored the utilization of PiSAR-L2 data for land cover classification in forest area using the pixel-based and object-based methods. The PiSAR-L2 data in the 2.1 level with full polarization bands were selected over part of forest area in Riau Province. Field data collected by JAXA team was used for both training samples and verification data. Preprocessing data 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 classification processes. These processes were conducted for 2.5 meter and 10 meter spatial resolution data applying two methods of the maximum likelihood 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 images could improve the accuracy of land cover classification, particularly to differentiate between forest and acacia plantation. The pixelbased method showed a more detail information of the objects, but has “salt and pepper”. In the other hand, the object-based method showed a good accuracy and clearer border line among objects, but has often some misinterpretations in object identification.

Item Type: Article
Uncontrolled Keywords: PiSAR-L2 data, Pixel-based method, Object-based method, Full polarization, Texture band, Forest
Subjects: Teknologi Penginderaan Jauh > Pengelolaan dan Pengembangan > Citra Satelit
Divisions: Deputi Penginderaan Jauh > Pusat Teknologi dan Data Penginderaan Jauh
Depositing User: Dinar Indrasasi
Date Deposited: 09 Feb 2021 09:17
Last Modified: 09 Sep 2021 00:21
URI: http://repositori.lapan.go.id/id/eprint/140

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