Bogor Agricultural University, Indonesia
BibTex Citation Data :
@article{IK.IJMS10042, author = {Agnestesya Manuputty and Jonson Lumban Gaol and Syamsul Agus}, title = {Seagrass Mapping Based on Satellite Image Worldview-2 by Using Depth Invariant Index Method}, journal = {ILMU KELAUTAN: Indonesian Journal of Marine Sciences}, volume = {21}, number = {1}, year = {2015}, keywords = {}, 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. }, issn = {2406-7598}, pages = {37--44} doi = {10.14710/ik.ijms.21.1.37-44}, url = {https://ejournal.undip.ac.id/index.php/ijms/article/view/10042} }
Refworks Citation Data :
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.
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