Sustainable Urban Growth using Geoinformatics and CA based Modelling

Electronic governance (e-governance) can be used as a vehicle for better decision making, resources monitoring, budget allocation, planning and development of cities as per the aspirations of people. Urban growth simulation and modelling in association with information technologies like Geographical Information Systems (GIS) can be used to ascertain possible impacts of urbanization on climate, ecology and environment. Such techniques can assist in effective governance of cities in making optimum decisions of urban development by developing different alternatives urbanization scenarios corresponding to different policies to achieve sustainable and environment friendly smart cities. Present study is aimed to demonstrate the application of geo-spatial techniques and urban growth modelling in determining different urban growth scenarios corresponding to different land use policies and sustainable developmental goals. A cellular automata (CA) based SLEUTH urban growth model and GIS has been used to simulate the urban growth of Pushkar fringe. Pushkar has experienced scattered and rapid urban development in recent past owing to increased tourism and industrial activities causing significant ecological and environmental problems. The SLEUTH model was conceptualized and calibrated using historical urban growth obtained from classification of multi-spectral satellite data. Further, calibrated model has been used to simulate urban growth of the Puskar fringe for year 2040 corresponding to six land use policy scenarios formulated to achieve sustainable developmental objectives and smart Pushkar town. (The study demonstrated the ability of GIS and CA based urban growth modelling to improvise the existing urban growth practices and in developing growth scenarios corresponding to different sustainable and smart city goals.

[1]  A. Dewan,et al.  Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization , 2009 .

[2]  E. Silvaa,et al.  Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal , 2002 .

[3]  Xiaojun Yang,et al.  Modelling urban growth and landscape changes in the Atlanta metropolitan area , 2003, Int. J. Geogr. Inf. Sci..

[4]  K. Clarke,et al.  The SLEUTH Land Use Change Model: A Review , 2013 .

[5]  M. K. Jat,et al.  Application of geo-spatial techniques and cellular automata for modelling urban growth of a heterogeneous urban fringe , 2017 .

[6]  Qihao Weng.  Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. , 2002, Journal of environmental management.

[7]  B. Bhatta,et al.  Urban sprawl measurement from remote sensing data , 2010 .

[8]  J. W. Bruce,et al.  The causes of land-use and land-cover change: moving beyond the myths , 2001 .

[9]  Keith C. Clarke,et al.  Toward Optimal Calibration of the SLEUTH Land Use Change Model , 2007, Trans. GIS.

[10]  M. Batty,et al.  Modeling urban dynamics through GIS-based cellular automata , 1999 .

[11]  Keith C. Clarke,et al.  Loose-Coupling a Cellular Automaton Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore , 1998, Int. J. Geogr. Inf. Sci..

[12]  S. Goetz,et al.  Using the Sleuth Urban Growth Model to Simulate the Impacts of Future Policy Scenarios on Urban Land Use in the Baltimore-Washington Metropolitan Area , 2004 .

[13]  Deepak Khare,et al.  Monitoring and modelling of urban sprawl using remote sensing and GIS techniques , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[14]  Elisabete A. Silva,et al.  Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal , 2002 .