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Detection of Land cover changes like forest DETECTION OF LAND COVER CHANGE USING FUZZY SEGMENTATION ALGORITHM Department fire, flood and cultivation is the important criterion for farmers. This paper proposes a Land cover detection model using Fuzzy Local C-Mean clustering model (FLC-C). Fuzzy Local C- Mean clustering model method is implemented to process subsequences of time series data and detects land cover change temperature measured as a function of time. Land surface temperature is measured and declared when consecutive subsequences that are extracted from one Moderate Resolution Imaging Spectroradiometer (MODIS) time series transitions from one cluster to another cluster and remains in the newly assigned cluster for the rest of the time series. The temporal sliding window designed to operate on a subsequence of the time series to extract information from two spectral bands from the MODIS product.

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M.Ramya, R.Ramya, K.Sangeetha, V.Prakash, Dr. N.S.Nithya, & Dr.E.Baby Anitha. (2021). Detection of land cover change using fuzzy segmentation algorithm . International Journal of Intellectual Advancements and Research in Engineering Computations, 7(2), 2236–2244. Retrieved from