Determine Potential Fishing Zones in the Persian Gulf Using Remote Sensing and GIS

Author(s):
Abstract:
Marine environment, including the ocean and coastal areas provide enormous opportunities for the growth in fisheries and the exploitation of natural resources. Fishing is an important source for the food production industry and in Iran. Due to the high demand to find fish resources, data from satellites play an important role in fisheries applications. Remote sensing of ocean color can be used in many applications, such as commercial fishing, marine transport, ocean mining, oil and gas exploration, hydrography, etc. Since the satellite images can provide a wide area coverage and good temporal resolution, they can be of great help in detecting potential fishing zones. The MODIS sensor that has the capability of high spectral resolution and multiple thermal bands make it a superior sensor compared to other types. In this research, the correlation coefficient value between MODIS satellite images and in-site water samples were at 0.84, which indicates a high accuracy of SST MODIS Images. This research aims to determine potential fishing zones in the Persian Gulf by using layers of sea surface temperature, sea surface height, chlorophyll - a and sea surface temperature gradient of water surface. Fuzzy methods provide a good decision making algorithm to determine the location of important areas, including uncertain and unclear ones. In this decision was given weighting layer through FAHP procedure was performed and the highest weight in the sea surface temperature as a parameter. After overlaying layers, the results indicate that 82% of the selected areas coincide with that of commercial fishing zones. The application of targeted fishing can be used to increase fishing efficiency at lower time compared to the current longer time that is possible by integrating remote sensing and Global geographic information system (GIS).
Language:
Persian
Published:
Iranian Journal of Remote Sencing & GIS, Volume:9 Issue: 1, 2017
Pages:
37 to 48
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