Using remote sensing and GIS for monitoring and predicting potential fishing zones of Sardinella aurita fisheries along the North Sinai coastal zone, Egypt

    Collection:
    Agricultural Communications Documentation Center (ACDC)
    Contributers:
    El-Gharbawy, Mohammad A. (author), Saber, Samy A. (author), El-Raey, Mohamed E. (author), and Zeina, Amr F. (author)
    Format:
    Journal article
    Publication Date:
    2024-09-01
    URL:
    https://ejabf.journals.ekb.eg/article_377623.html
    Published:
    Egypt: Egyptian Society for the Development of Fisheries and Human Health
    Location:
    Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 208 Document Number: D13321
    Journal Title:
    Egyptian Journal of Aquatic Biology and Fisheries
    Journal Title Details:
    28(5) : 59-74
    Subject Term:
    fish, pollution, predictions, production techniques, productivity, fishing, fishery, Egypt (Africa, Northern), monitoring, yield, remote sensing, environmental factors, GIS, Sardinella aurita, North Sinai, sea surface temperature, Chlorophyll-a, and potential fishing zone
    Notes:
    16 pages, The round sardinella, Sardinella aurita, is the most important species in the North Sinai fisheries; it represents about 85 % of the total catch in the North Sinai fisheries, yet the fishing activities are still based on traditional methods, like gathering information from fellow fishermen. The fishing grounds constantly change due to environmental factors; therefore, determining the potential fishing zones (PFZs) must depend on effective and advanced techniques to monitor the optimal (PFZs) for Sardinella aurita along the North Sinai coastal zone. This study integrated the daily Sentinel-3 satellite's remotely sensed data, advanced digital imagery processing techniques, and fish yield data obtained from the General Authority for Fish Resources Development (GAFRD) for Sardinella aurita in the North Sinai fisheries during 2021 to build a suitable model for determining, monitoring, and predicting the other optimal (PFZs) for Sardinella aurita along the North Sinai coastal zone. The results confirmed that, regarding the total catch of Sardinella aurita in 2021, the highest catch reached 73, 68, and 47 tons in April, December, and November, respectively, while the lowest catch reached 6 tons in January. The predicted PFZs resulting from the model are estimated to be 7 times more than the fishing grounds where fishermen currently fish. Moreover, the results confirmed the strong linkage between Sardinella aurita abundance and chlorophyll-a (Chl-a) concentration with sea surface temperature (SST). This study highlighted the importance of using remotely sensed data to help increase the national income from the fisheries sector by determining and predicting new fishing zones.

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