TY - JOUR
T1 - Preliminary Result of Drone UAV Derived Multispectral Bathymetry in Coral Reef Ecosystem
T2 - A Case Study of Pemuteran Beach
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
N1 - Funding Information:
ACKNOWLEDGMENT This study was supported by RISPRO LPDP grant number PRJ-41/LPDP/2020.
Publisher Copyright:
© IJASEIT is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.
PY - 2022
Y1 - 2022
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.
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.
KW - Bathymetry
KW - Coral reef
KW - Multispectral
KW - Random forest
KW - Uav
UR - http://www.scopus.com/inward/record.url?scp=85136085242&partnerID=8YFLogxK
U2 - 10.18517/ijaseit.12.4.16107
DO - 10.18517/ijaseit.12.4.16107
M3 - Article
AN - SCOPUS:85136085242
SN - 2088-5334
VL - 12
SP - 1512
EP - 1516
JO - International Journal on Advanced Science, Engineering and Information Technology
JF - International Journal on Advanced Science, Engineering and Information Technology
IS - 4
ER -