Seagrass Mapping Based on Satellite Image Worldview-2 by Using Depth Invariant Index Method

*Agnestesya Manuputty  -  Bogor Agricultural University, Indonesia
Jonson Lumban Gaol  -  Bogor Agricultural University, Indonesia
Syamsul Bahri Agus  -  Bogor Agricultural University, Indonesia
Published: 1 Mar 2015.
Open Access

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Abstract

Seagrass has an important role in coastal areas, so it’s sustainability need to be maintained. One effort to preserve it is sustainable manner management of segrass based on the spatial data using remote sensing techniques. The aim of this study was to map seagrass ecosystems and to determining the accuracy level from classification results that obtained by the WorldView-2 images. This study was conducted in Karang Bongkok and Kotok Islands in August 2014 and March 2015. The satellite images data used on this study was WorldView-2 satellite images at the acquisition date of October 5, 2013. The method used to conduct image processing data is Depth Invariant Index (DII) using Support Vector Machine (SVM) classification. The result shows that seagrass mapping in Karang Bongkok and Kotok Islands using DII transformation has 19.5112 ha areas with 72% accuracy on Karang Bongkok Island and 2.5704 ha areas with of 83% accuracy on Kotok Island.

Key words: Seagrass mapping, DII, SVM, Karang Bongkok, Kotok Island.

Funding: Syamsul Bahri Agus, Bogor Agricultural University,Departemen of Marine Science and Technology

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Last update: 2021-05-06 15:02:51

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