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Environmental Engineering - Inženjerstvo okoliša, Vol. 8 No. 1-2, 2021.

Professional paper

https://doi.org/10.37023/ee.8.1-2.10

URBAN SPACE CHANGE AND FUTURE PREDICTION OF KANPUR NAGAR, UTTAR PRADESH USING EO DATA

Shubham Sharma orcid id orcid.org/0000-0002-9420-2804 ; Centre for Climate Change and Water Research, Suresh Gyan Vihar University, Jaipur 302017, India
Suraj Kumar Singh orcid id orcid.org/0000-0002-9420-2804 ; Centre for Sustainable Development, Suresh Gyan Vihar University, Jaipur 302017, India
Shruti Kanga ; Centre for Climate Change and Water Research, Suresh Gyan Vihar University, Jaipur 302017, India
Nikola Kranjčić orcid id orcid.org/0000-0001-7219-9440 ; University of Zagreb, Faculty of Geotechnical Engineering, Hallerova aleja 7, HR42000, Varaždin, Croatia
Bojan Đurin orcid id orcid.org/0000-0002-2361-8036 ; Department of Civil Engineering, University North, 42000 Varaždin, Croatia

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Abstract

Urban Land use changes, measurements, and the analysis of rate trends of growth would help in resources management and planning, etc. In this study, we analyze the urban change dynamics using a support vector machine model. This method derives the urban and rural land-use change and various components, such as population growth, built-up areas, and other utilities. Urban growth increases rapidly due to exponential growth of population, industrial growth, etc. The population growth also affects the availability of various purposes in its spatial distribution. In this present study, we carried out using multi-temporal satellite remote sensing data Landsat MSS (Multispectral scanner), ETM+ (Enhanced thematic mapper), OLI (Operational land imager) for the analysis of urban change dynamics between years 1980-1990, 1990-2003, 2012-2020 in Kanpur Nagar city in the state of Uttar Pradesh in India. In our study, we used SVM (Support Vector Machine) Model to analyze the urban change dynamics. A support vector machine classification technique was applied to generate the LULC maps using Landsat images of the years 1980, 1990, 2003, and 2020. Envi and ArcGIS software had used to identify the land cover changes and the applying urban simulation model (CA- Markov model) in Idrisi selva edition 17.0 software. The LULC maps of 2003 and 2020 were used to simulate the LULC projected map for 2050 using (Cellular automata) CA- Markov based simulation model.

Keywords

Urban growth, Support vector machine, Change detection, Urban simulation model, and CA- Markov model.

Hrčak ID:

266063

URI

https://hrcak.srce.hr/266063

Publication date:

20.12.2021.

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