Land use/Land cover Changes in Sangamner City by using Remote Sensing and GIS
Navale V.B.1, Mhaske S.Y.2 

1Navale V.B., Department of Civil & Env. Engineering, Research Scholar, V.J.T.I., Mumbai-400019, India.
2Mhaske S.Y., Department of Civil & Env. Engineering, Associate.

Manuscript received on 15 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 July 2019 | PP: 4614-4621 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3386078219©BEIESP | DOI: 10.35940/ijrte.B3386.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper examines that, with the help of Remotes Sensing (RS) and Geographical Information system (GIS) Land use/Land cover of the town area from period 1975 to 2017 are classified into different classes. The town information is extracted from Toposheet and Remote Sensing Landsat-7 ETM+ images of 1975 to 2017. There are five expansion types are considered during 42 years, including water body, built-up area, forest, Agriculture and exposed Rock. By analyzing the data from the year 1975 to 2017 we found that the natural feature area such as water body, the forest is decreasing continuously and the area of town that is built-up area increase partially etc. Shannon’s Entropy approach identifies the degree of special concentration and dispersion growth, its value is close to 1 which indicates that space distribution is evenly dispersed. According to get the value of statistical Kappa Coefficient which lies in between 0.75 to 0.89 we say that there is accuracy in the requirement of research. Also, in addition to that population for the next three-decade help to define the built-up area of the city, the method used to forecast the population are Arithmetic increase method, Geometric increase method, Incremental increase method, Decreasing rate of growth method and Simple graphical method, this method gives a forecast of urban expansion from the year 2021 to 2041. The Land use/ Land cover changes classification is useful for proper planning, utilization and management of resources. Land use/Land cover changes are contributed to creating community spirit and a properly balanced population structure.
Keywords: Landsat-7, GIS, Remote Sensing, Supervised Classification.

Scope of the Article: Classification