Application of Machine Learning in Land Use Land Cover in Ranchi District, Jharkhand State of India

Abstract

The increasing population coupled with the modernization is affecting the urban areas. These lead to the depletion in the natural water bodies. The present paper is based on the study of application of machine learning technique to detect the differences in the extent of the land use land cover the past two years from the Sentinel 2A satellite data. The supervised method of machine learning the maximum likelihood classification is used to categorize various features in the images on the basis of colour bands. Finally, the principal component analysis provides the result for the classification process of a reference raster images to the trained image.  The covariance matrix of the bands represent the variation of the data of obtained from different processes of classification.