Issue |
BIO Web Conf.
Volume 106, 2024
The 5th International Conference on Marine Science (ICMS 2023)
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Article Number | 04009 | |
Number of page(s) | 12 | |
Section | Marine Remote Sensing & GIS | |
DOI | https://doi.org/10.1051/bioconf/202410604009 | |
Published online | 03 May 2024 |
Geospatial analysis for prediction of potential fishing zones in the Banggai Waters using hydroacoustic data and satellite remote sensing
1 Geography Information Science Study Program, Faculty of Social Studies Education, Universitas Pendidikan Indonesia, 40154 Bandung, West Java, Indonesia
2 Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University, 16680 Bogor, West Java, Indonesia
3 Marine Fisheries Research Center, 16680 Bogor, West Java, Indonesia
* Corresponding author: henrymanik@apps.ipb.ac.id
Banggai waters are a strategic area rich in fish resources and a source of livelihood for most of the local population. Mapping fish stocks is important to ensure the sustainability of fishing in the area. One of them uses hydroacoustic data and satellite imagery to provide more comprehensive results on fish stocks and more accurate predictions of potential fishing zones. This study will spatially estimate fish density in Banggai waters using hydroacoustic data and investigate the distribution of chlorophyll-a and sea surface temperature using Himawari-8 imagery. Hydroacoustic data processing will produce target strength (TS) and volume backscatter strength (Sv) values to determine the value and distribution of fish density. Meanwhile, ZPPI results are obtained from the overlay of chlorophyll-a and sea surface temperature. From the results of mapping the potential fishing zone, the high category has the highest percentage of 43%, low 28% and medium 29%. The ZPPI point distribution map then shows the concentration of ZPPI points in the southern Banggai waters. The fish density distribution map shows that the spatial distribution tends to be around the coast of Banggai Peninsula, dominated by small and very small fish categories. Correlation of fish density point distribution with ZPPI results and oceanographic parameters has a positive influence on fish density from GAM modelling.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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