Abstract
Shallow water seabed profile has considerable potential resources so the availability of information which very important for coastal resources. The use of remote sensing techniques is considered to provide coastal information effective and efficient. This research aimed to determine the shallow water seabed profile based on Landsat 8 Imagery and its accuracy related to the in situ data. Methods of this research are satellite mage pre-processing, image classification, field survey, image classification, and accuracy assesment . Therefore, 6 classification of shallow water seabed profile, there are rubble (R), seagrass mixed sand (MIX -SG/SD), coral reefs mixed rubble (MIX-C/RB), rubble mixed dead coral (MIX-RB/DC), sand mixed rubble (MIX-SD/RB), and sand mixed seagrass (MIX-SD/SG), respectevely. The result of this classification has an accuracy value 80%.
Highlights
The shallow water seabed profiles potentially coastal resources, so it must be managed well in order to be optimally and sustainably utilized
The use of remote sensing is done because the conventional method is considered less efficient in providing a profile of shallow seabed profile in addition to require a long time is a relatively expensive cost considering that the region is generally located in remote areas and access difficult
The amount of rubble found in Gili Matra is caused by environmental conditions that are experiencing global warming and human activities are less conservative such as placing anchors at random when the ship is docked, and tourists who are less used to doing snorkeling so that many seabed objects are damaged by the activity on while swimming
Summary
The shallow water seabed profiles potentially coastal resources, so it must be managed well in order to be optimally and sustainably utilized. Through this technology, information of an object can be obtained using satellite sensors and analyzed and presented in spatial and thematic form in accordance with the purpose of the activity [5]
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