Abstract
The remote sensing technology provides the means of classification of land cover with diversity of additional endless environmental variables over large spatial and moderate temporal extents. To investigate the land cover classification, remote sensing is useful as it provides a synoptic view with high level of information. Natural phenomenon and human intervention are major causes in land cover change can be easily seen with the help of satellite. Using land use land cover analysis methods, urban planner and policy maker can easily identify the change happened in some specific time period. In this study, unsupervised K-means clustering algorithm has been applied to investigate the land use land cover change in the time span of 2011–2016.
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Kulkarni, G., Muley, A., Deshmukh, N., Bhalchandra, P. (2020). Land Use Land Cover Change Detection Through GIS and Unsupervised Learning Technique. In: Tuba, M., Akashe, S., Joshi, A. (eds) Information and Communication Technology for Sustainable Development. Advances in Intelligent Systems and Computing, vol 933. Springer, Singapore. https://doi.org/10.1007/978-981-13-7166-0_23
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DOI: https://doi.org/10.1007/978-981-13-7166-0_23
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