Abstract
In contemporary improvements remote sensing and GIS technologies offer great tool for mapping and detecting amend in land use/land cover (LULC). LULC is a vital aspect in perceptive the dealings of individual deeds with the environment and thus it is required to replicate alteration. The primary objective was mapping process with classification scheme and procedural steps for interpretation so as to maintain standard operational procedures. As of now satellite hyperspectral image provides information but this is not sufficient to classify the living areas. So, to get the sufficient information about land use data LANDSAT images has been taken. Here Tirupati area is selected to classify, because fast growing city in Andhra Pradesh which is a pilgrim center suited at Rayalaseema region with in Chittoor district. Tirupati is divided in rural and urban area. Here to classify the image Machine Learning Algorithms like support vector machine, K-NN algorithms are applied and to know which algorithm is best for classification is compared with accuracy.
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Nagalakshmi, G., Sarath, T., Jyothi, S. (2020). Land Site Image Classification Using Machine Learning Algorithms. In: Jyothi, S., Mamatha, D., Satapathy, S., Raju, K., Favorskaya, M. (eds) Advances in Computational and Bio-Engineering. CBE 2019. Learning and Analytics in Intelligent Systems, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-46939-9_19
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