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I Wayan Matsya Deva Nagendra
Program Studi Ilmu Kelautan, Fakultas Kelautan dan Perikanan, Universitas Udayana, Kampus UNUD Bukit Jimbaran, Bali 80361, Indonesia
Earth & Planetary Sciences

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Perbandingan Kemampuan Satelit SAR, Optik dan Kombinasi SAR & Optik Untuk Mendeteksi Area Mangrove di Teluk Benoa I Wayan Matsya Deva Nagendra; I Wayan Gede Astawa Karang; Ni Luh Putu Ria Puspitha
Journal of Marine and Aquatic Sciences Vol 5 No 2 (2019)
Publisher : Fakultas Kelautan dan Perikanan Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (821.249 KB) | DOI: 10.24843/jmas.2019.v05.i02.p14

Abstract

Mangrove in Benoa Bay plays important roles in the southern Bali island. Mangrove habitat in Benoa Bay has undergone in area changes due to various anthropogenic activities and natural factors, it is important to monitor the distribution of the mangrove forests. Mangrove area changes can be detected using remote sensing technology. This research is to aims the capabilities of radar and optical satellites in mangroves detection using supervised classification Maximum likelihood & Minimum distance. The results showed that radar images failed to detect mangroves as a separate class and produced three classes of land cover (urban, vegetation and waters), optical images and a combination of radar & optic images capable of detecting mangroves as a separate class and produce five land cover class (vegetation other, urban, mangroves, waters and agriculture). The evaluation of the Maximum likelihood classification shows that the combination of radar & optical images scenario has the highest overall accuracy and kappa accuracy with value of 91.35% and 87.01% respectively. Minimum distance classification shows that the optical image scenario has the highest accuracy and highest kappa accuracy with value of 80.83% and 72.51%. The results of the accuracy evaluation shown that the maximum likelihood has higher accuracy than the minimum distance classification method.
Co-Authors I Wayan Gede Astawa Karang Ni Luh Putu Ria Puspitha