Land-Use/Land-Cover Change Detection Analysis using Machine Learning Algorithms: Pune as a use Case


Authors : Sanjay Srivas, Dr. P. G. Khot

Volume/Issue : Volume 4 - 2019, Issue 12 - December

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/2NCgazi

Urbanization leads to the dynamic use of land and it has significant impact on the urban ecosystem. In the present scenario, remote sensing plays a significant role in monitoring, planning and controlling the natural resources. Improvements in the remote sensing satellite technology coupled with better remote sensors providing high resolution data, have given scientists an opportunity to perform extensive space time data analysis. This paper primarily deals with changes in the urban sprawl of Pune city. Landsat images of 1991 and 2011 covered by path 147 and rows 47 were acquired, LULC classification was used to stratify the images, while the LULC map was analyzed using SAGA version 7.3.0 software. The result indicates that severe land changes have occurred in urban (79%), Green Zone (forest + shrubland + grassland) (- 9%), openland (-15%) and water bodies (5%) areas over the period of two decades. The result highlights an immense increase in the urbanization. This type of an outcome can be used for making better policies and regulations to sustain rapid urbanization.

Keywords : Geographic Information System (GIS), Urbanization, Classification, Land Cover Land Use (LULC), Change Analysis.

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