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A Cluster-Based Method for Improving Water Depth Estimation from Satellite Derived Bathymetry
Meliala L.a, Juliansah T.a, Adytia D.b, Sidiq T.P.a, Windupranata W.a, Poerbandonoa
a Institut Teknologi Bandung, Geodesy and Geomatics Engineering Study Program, Bandung, Indonesia
b Telkom University, School of Computing, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 IEEE.In this presented paper, an effort to improve the accuracy of the bathymetric model derived from optical satellite imagery is discussed. According to the previous study, the accuracy approximately measures in 2 m for depth up to 10 m by means of the Global Bathymetric Inversion Methods. Therefore, the improvement is done based on the so-called Cluster-Based Method applied to the analytical and log-ratio methods. The Cluster-Based Method partitions the working area on the by classifying the errors between the known depths and the predicted ones. The data for the known and predicted depths are acquired from the in-situ survey and the Sentinel-2 imagery. Improvement by one-third to the accuracy of the resulting bathymetry is obtained.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Cluster-based methods,Inversion methods,Log-ratio method,Optical satellite imagery,Water depth,Working areas[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]analytical-method,bathymetry,Cluster-Based Method,log-ratio method,satellite[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The authors would like to thank Telkom University for holding the international conference on data science. This research is funded by the DG Higher Education, Ministry of Education and Culture under World Class Research 2020.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICoDSA50139.2020.9212988[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]