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Shifting cultivation and its practice are said to be pernicious and eco-hostile from the standpoint of dependence of tribal people on forest-clad hill slopes. In this farming, the soil bone diseases are also reduced significantly. This is an example of subsistence, extensive, and arable farming. In the rainforest, it is one of the traditional forms of agriculture. The Amazonian Indians mostly do this farming in South America. They use the land for 2 to 3 years before moving to another area. There is a huge part of land which is used for Shifting cultivation for several years. Because of its spread, growing loss of potential green cover and related imbalance in eco-habitat, the Forest Policy, 1952 and the National Commission on Agriculture, 1976 suggested that shifting cultivation be banned, providing the tribal practitioner alternative systems of livelihood support. In this paper we are going to look at different methods and algorithms used to build AI models to predict Land used for Shifting Cultivation. Keywords: Shifting Cultivation, Remote Sensing, LULC, Image Processing, Neural Networks. |
