摘要：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%.
其他摘要：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%.
