Affiliation:
1. Department of Aquacultural Engineering, College of Fisheries Engineering Tamil Nadu Dr. J. Jayalalithaa Fisheries University Nagapattinam India
2. Crustecean Culture Division ICAR‐Central Institute of Brackishwater Aquaculture Chennai India
3. ICAR‐Research Complex for Eastern Region, ICAR Parisar P.O. Bihar Veterinary College Patna India
Abstract
AbstractThe aim of the present study was to develop a multi‐criteria decision support system to find out possible aquaculture sites available in Nagapattinam district of Tamil Nadu, India. This study focuses on identifying possible aquaculture sites available in Nagapattinam district using remote sensing and GIS approaches. A geographical model has been developed to choose the probable aquaculture sites. The remote sensing and geographic information system techniques were applied to study the decisive parameters that play a vital role in the site suitability for aquaculture purposes. The chosen decisive parameters viz., normalized difference vegetation index, digital elevation model, soil type, normalized difference water index, land use land cover area and land surface temperature were subjected to the development of decision support system. Moreover, four different multi‐criteria decision support techniques viz., weighted overlay, analytical hierarchy process, fuzzy classified analytical hierarchy process and fuzzy classified weighted overlay were applied in the present study. The results obtained from the study rendered that the weighted overlay and the analytical hierarchy process outperforms the fuzzy classified models. The suitability ratio of analytical hierarchy process and weighted overlay methods were found to be 12.7 and 12.4 respectively. A total of 25 locations were selected and mapped in the Nagapattinam region and their accuracy was checked. The analytical hierarchy process results were obtained with an accuracy of 84%. Hence, the analytical hierarchy process provided better results than the weighted overlay technique. The study rendered that the area of 7.22% is highly suitable for aquaculture. These findings are essential for the development of sustainable aquaculture, assisting stakeholders in selecting suitable aquaculture sites that maximize productivity while minimizing environmental degradation.
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