Land Change Prediction using Markov Change Multi-Layer Perceptron in Navi Mumbai, Maharashtra, India
Sandip P. Patil1, Manisha B. Jamgade2
1Sandip Pravin Patil, Department of Civil Engineering M. E Research Scholar, Pillai HOC College of Engineering and Technology, Pillai HOC College of Engineering and Technology, Rasayani, Raigad, Maharashtra, India.
2Manisha B. Jamgade, Department of Civil Engineering Assistant Professor, Pillai HOC College of Engineering and Technology, Pillai HOC College of Engineering and Technology, Rasayani, Raigad, Maharashtra, India.
Manuscript received on 03 July 2019 | Revised Manuscript received on 08 July 2019 | Manuscript published on 30 August 2019 | PP: 484-490 | Volume-8 Issue-10, August 2019 | Retrieval Number: I8532078919/2019©BEIESP | DOI: 10.35940/ijitee.I8532.0881019
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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: Long-term evaluation of land change and future prediction change is extremely important for planning and land use management. This research conducted for the analyze future prediction change in the study area Navi Mumbai. For this prediction analysis used satellite images year from 1998, 2008 and 2018 are taken. Thus, the change detection obtained from land use and land cover assist in most favourable solutions for the choice, planning, implementation, and observance of development schemes. To meet the increasing demands of human need, land management is required. In this work for upcoming predict year, Markov change model is used for simulating 2028 year. It will give vital and useful information on future development and planning. And also, is easy for continuing to monitor land change for the large area due to natural human activities and the effect of natural resources.
Keywords: Land use and Land cover change, Change detection, Spatial modelling, Markov Multi-Layer Perceptron
Scope of the Article: Regression and Prediction