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Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach

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@article{IJASEIT16107,
   author = {Masita Dwi Mandini Manessa and Dadang Handoko and Fajar Dwi Pamungkas and Riza Putera Syamsuddin and Dwi Sutarko and Agus Sukma Yogiswara and Mutia Kamalia Mukhtar and Supriatna Supriatna},
   title = {Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {12},
   number = {4},
   year = {2022},
   pages = {1512--1516},
   keywords = {UAV; multispectral; bathymetry; coral reef; random forest.},
   abstract = {UAV-derived multispectral bathymetry is an alternative to creating a shallow water bathymetry map without a massive field survey. Multispectral UAV technology can be used for detailed scale identification scopes because it has better spatial resolution and relatively affordable cost. The UAV used in this study record the coastal area using four multispectral sensors, blue, green, red, and near-infrared bands. The UAV images are processed into point cloud information under the use of the Structure from Motion (SfM)-based algorithm with a spatial resolution of 0.075 m. Then the point cloud information is used to predict the water depth using the random forest algorithm. This research was conducted at Pemuteran Beach, Bali, Indonesia. We compared the performance of only spectral, cloud point, and the combination of cloud point – spectral information to predict the water depth. As a result, the cloud point – spectral based shows significant accuracy improvement compared with the spectral only approach that reaches ~1.5, ~2.5 m, and ~0.3m for R2, RMSE, and MAPE, respectively. So, the use of the SfM UAV technique can improve the common spectral-based SDB method.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=16107},
   doi = {10.18517/ijaseit.12.4.16107}
}

EndNote

%A Manessa, Masita Dwi Mandini
%A Handoko, Dadang
%A Pamungkas, Fajar Dwi
%A Syamsuddin, Riza Putera
%A Sutarko, Dwi
%A Yogiswara, Agus Sukma
%A Mukhtar, Mutia Kamalia
%A Supriatna, Supriatna
%D 2022
%T Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach
%B 2022
%9 UAV; multispectral; bathymetry; coral reef; random forest.
%! Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach
%K UAV; multispectral; bathymetry; coral reef; random forest.
%X UAV-derived multispectral bathymetry is an alternative to creating a shallow water bathymetry map without a massive field survey. Multispectral UAV technology can be used for detailed scale identification scopes because it has better spatial resolution and relatively affordable cost. The UAV used in this study record the coastal area using four multispectral sensors, blue, green, red, and near-infrared bands. The UAV images are processed into point cloud information under the use of the Structure from Motion (SfM)-based algorithm with a spatial resolution of 0.075 m. Then the point cloud information is used to predict the water depth using the random forest algorithm. This research was conducted at Pemuteran Beach, Bali, Indonesia. We compared the performance of only spectral, cloud point, and the combination of cloud point – spectral information to predict the water depth. As a result, the cloud point – spectral based shows significant accuracy improvement compared with the spectral only approach that reaches ~1.5, ~2.5 m, and ~0.3m for R2, RMSE, and MAPE, respectively. So, the use of the SfM UAV technique can improve the common spectral-based SDB method.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=16107
%R doi:10.18517/ijaseit.12.4.16107
%J International Journal on Advanced Science, Engineering and Information Technology
%V 12
%N 4
%@ 2088-5334

IEEE

Masita Dwi Mandini Manessa,Dadang Handoko,Fajar Dwi Pamungkas,Riza Putera Syamsuddin,Dwi Sutarko,Agus Sukma Yogiswara,Mutia Kamalia Mukhtar and Supriatna Supriatna,"Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach," International Journal on Advanced Science, Engineering and Information Technology, vol. 12, no. 4, pp. 1512-1516, 2022. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.12.4.16107.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Manessa, Masita Dwi Mandini
AU  - Handoko, Dadang
AU  - Pamungkas, Fajar Dwi
AU  - Syamsuddin, Riza Putera
AU  - Sutarko, Dwi
AU  - Yogiswara, Agus Sukma
AU  - Mukhtar, Mutia Kamalia
AU  - Supriatna, Supriatna
PY  - 2022
TI  - Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 12 (2022) No. 4
Y2  - 2022
SP  - 1512
EP  - 1516
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - UAV; multispectral; bathymetry; coral reef; random forest.
N2  - UAV-derived multispectral bathymetry is an alternative to creating a shallow water bathymetry map without a massive field survey. Multispectral UAV technology can be used for detailed scale identification scopes because it has better spatial resolution and relatively affordable cost. The UAV used in this study record the coastal area using four multispectral sensors, blue, green, red, and near-infrared bands. The UAV images are processed into point cloud information under the use of the Structure from Motion (SfM)-based algorithm with a spatial resolution of 0.075 m. Then the point cloud information is used to predict the water depth using the random forest algorithm. This research was conducted at Pemuteran Beach, Bali, Indonesia. We compared the performance of only spectral, cloud point, and the combination of cloud point – spectral information to predict the water depth. As a result, the cloud point – spectral based shows significant accuracy improvement compared with the spectral only approach that reaches ~1.5, ~2.5 m, and ~0.3m for R2, RMSE, and MAPE, respectively. So, the use of the SfM UAV technique can improve the common spectral-based SDB method.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=16107
DO  - 10.18517/ijaseit.12.4.16107

RefWorks

RT Journal Article
ID 16107
A1 Manessa, Masita Dwi Mandini
A1 Handoko, Dadang
A1 Pamungkas, Fajar Dwi
A1 Syamsuddin, Riza Putera
A1 Sutarko, Dwi
A1 Yogiswara, Agus Sukma
A1 Mukhtar, Mutia Kamalia
A1 Supriatna, Supriatna
T1 Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem: A Case Study of Pemuteran Beach
JF International Journal on Advanced Science, Engineering and Information Technology
VO 12
IS 4
YR 2022
SP 1512
OP 1516
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 UAV; multispectral; bathymetry; coral reef; random forest.
AB UAV-derived multispectral bathymetry is an alternative to creating a shallow water bathymetry map without a massive field survey. Multispectral UAV technology can be used for detailed scale identification scopes because it has better spatial resolution and relatively affordable cost. The UAV used in this study record the coastal area using four multispectral sensors, blue, green, red, and near-infrared bands. The UAV images are processed into point cloud information under the use of the Structure from Motion (SfM)-based algorithm with a spatial resolution of 0.075 m. Then the point cloud information is used to predict the water depth using the random forest algorithm. This research was conducted at Pemuteran Beach, Bali, Indonesia. We compared the performance of only spectral, cloud point, and the combination of cloud point – spectral information to predict the water depth. As a result, the cloud point – spectral based shows significant accuracy improvement compared with the spectral only approach that reaches ~1.5, ~2.5 m, and ~0.3m for R2, RMSE, and MAPE, respectively. So, the use of the SfM UAV technique can improve the common spectral-based SDB method.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=16107
DO  - 10.18517/ijaseit.12.4.16107