Paper
2 December 2014 Geospatial dynamic of seagrass in outer zone, Spermonde Archipelago, Indonesia using Landsat data from 1972-2013
Nurjannah Nurdin, Khairul Amri, Abd. Rasyid Djalil, Ilham Jaya, Agus Aris, Muhammad Akbar AS
Author Affiliations +
Proceedings Volume 9261, Ocean Remote Sensing and Monitoring from Space; 92610N (2014) https://doi.org/10.1117/12.2062898
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China
Abstract
Spermonde islands located in the Makassar Strait, South-West side of the peninsula of Sulawesi Island. Kondongbali island as one of eight small island in outer zone Spermonde Archipelago is study site of this research. Images of Landsat MSS, Landsat TM, Landsat ETM, Landsat ETM+, and Landsat 8 data were used to examine changes on seagrass on the small islands for forty one year from 1972 to 2013. The image fusion technique were done to combain relevant information for two images into single image to produce the high spatial resolution and fill gap processing was done on Landsat ETM+ SLC-off. Subsequently, a multi-component change detection procedure was applied to these indices to define changes. Seagrass cover classification devided into seagrass percent cover 0-24.9%, 25-59,9%, <60%), and sand. The percentage of seagrass change based on the image classification in outer zone islands from 1972 to 2013 has decrease. Eventhough, seagrass coverage as observed in Kondongbali Island is not so serious compared to other ecosystems (coral reef).. This research will be contributed to baseline information on spasial dynamic of coastal benthic communities in tropical area.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nurjannah Nurdin, Khairul Amri, Abd. Rasyid Djalil, Ilham Jaya, Agus Aris, and Muhammad Akbar AS "Geospatial dynamic of seagrass in outer zone, Spermonde Archipelago, Indonesia using Landsat data from 1972-2013", Proc. SPIE 9261, Ocean Remote Sensing and Monitoring from Space, 92610N (2 December 2014); https://doi.org/10.1117/12.2062898
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Cited by 2 scholarly publications.
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KEYWORDS
Earth observing sensors

Landsat

Spatial resolution

Image fusion

Image classification

Satellites

Remote sensing

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