A Survey on Wetland, Land Degradation and Agriculture using Data Mining Techniques



Data related to wetland, soil degradation and agriculture is now becoming essential research in field of data mining. Wetlands perform the ecological function of nutrient cycling, carbon storage, flood reduction and provisioning of habitat for wildlife. Wetlands make 6% of the world's total land surface, but it contributes nearly 40% of the yearly global ecosystem services. Now-a-days wetlands are under high pressure because of the land is altered and used for different purposes, while it is essential for achieving food security and rural livelihoods. It is found from the recent study that more than 50% of the world's wetlands have disappeared due to agriculture and urbanization. This survey aims to suggest how the agricultural sector can be enhanced in Ethiopia by using data mining techniques in assuring food security, economical growth of the smallholder farmers and the country. The study also aims to analyze about the possibility of expanding the agriculture, to meet the future demand of the country’s fast growing population without disturbing the environmental ecosystem. The data processing techniques in agriculture require evaluating, storing, monitoring and retrieving of the resources used. The data mining techniques used for this survey include K-means, Support Vector Machines (SVM).

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ISSN : 2251-1563