IDENTIFICATION OF SEABED COVER USING AIRBORNE LIDAR BATHYMETRY
The presence can well know characteristics of a coastal area of bathymetric information and the type of seabed coverage. Using the two pieces of information can make the utilization of the information more precise and maximal, such as for ship navigation, coastal development, and coastal conserva...
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/67589 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | The presence can well know characteristics of a coastal area of bathymetric
information and the type of seabed coverage. Using the two pieces of information
can make the utilization of the information more precise and maximal, such as for
ship navigation, coastal development, and coastal conservation. Currently, there is
little information on seabed cover type compared to bathymetric information.
Remote sensing methods can be an alternative acceleration. One method is using
Airborne LiDAR bathymetry (ALB). The LiDAR laser pulse will interact with the
environment in its paths, such as the atmosphere, air surface, air column, and
bottom of the water, until it returns to the receiver. The interaction can be seen by
extracting the full waveform from LiDAR. The different types of coverage of the
bottom of the water reflecting the laser pulse will affect the value and form of the
energy of the returned pulse. Therefore, this research approach will add a variable
from the waveform, namely width, and area. All these variables will be analyzed in
the formation of seabed classification using the Random Forest method.
Classification is divided into three classes: sand, rock, and coral. The research
location is on the coast of Bagus Beach, South Lampung Regency. The
classification results were tested using field survey data of seabed bottom type. The
accuracy test shows that adding the waveform variable can increase the
classification accuracy from 74 to 83, resulting kappa value of 74.5%. In addition,
the analysis results find important variables in making predictions, namely width,
depth, and area. With these promising results, LiDAR bathymetry can be a solution
in supporting the provision of complete seabed information.
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