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Satellite-based identification of Aquaculture Farming using Neural Network Method over Coastal Areas around Bhitarkanika, Odisha
* 1 , 2
1  4th year student of Integrated in Geo-informatics
2  Assistant Professor at Central University of Jharkhand


Aquaculture is the farming of fish, crustaceans, molluscus, aquatic plants, algae, and other aquatic organisms. Aquaculture farming in coastal areas of India plays key role in economy which contributes 1.07 % of GDP. It is the second largest in aquaculture production, which gives employment to 14.5 million people and foreign exchange earnings of US$ 3.51 billion from fishes and fisheries products. In Odisha, aquaculture system exports 26% of its products to foreign countries. Artificial neural networks have a feature of pattern recognition which uses training dataset to identify pattern of any feature from images. The term pattern recognition considers a wide range of information processing problems of great practical significance. After identifying the patterns it can be used to identify similar patterns from other images.  This study have been carried over two districts namely, Bhadrak and Kendrapada in Odisha. Here, Landsat-8 satellite data (OLI sensor) has been used and training sites have been collected. In this study, pattern recognition feature of neural network have been used to extract aquaculture features from satellite image. Further, we have analyzed the area that have been converted from agriculture to aquaculture from 2002 to 2017 using neural network classification. The details and results will be presented at the conference.  

Keywords: Artificial neural network, Pattern recognition, Aquaculture