1. Center for Study of Science, Technology and Policy, Bangalore Abhik Kumar Das* & Sujaya Rathi An Empirical Geometric Model for City Expansion International Conference on Intelligent Infrastructure Date : December 1-2,2012 | Science City, Kolkata

2. Defining City : Computational Approach

3. Past - Present – Future ?? Year19732000 Area (SqKm)Area(%)Area (SqKm)Area(%)CHANGE (%) Built up104.94.8306.213.9192 Open spaces1474.567.2417.419-28.3 water38.21.746.62.1-78

4. Assumption of the Geometric Model The center of an area can be considered at (x i, y i ) where i = 1,2,...,n. Here i -represents the i-th area and n is the total number of areas under consideration The area has radial-outward expansion, for simplicity let assume the expansion rate in x and y direction as e x(i) and e y(i), respectively. The area contains a ‘growth-time-factor’ (g i )

5. Mono-Centric Structure of An Area Any area can be represented as [x i, y i,g i, e x(i), e y(i) ] The growth of the area at any time step can be represented as, G i (x i, y i,g i, e x(i), e y(i) )

6. What is G ? : Spatial Organization of Economic Activity !!!

7. Expansion Rate ?? Depends on Absorption Capacity of an Area Migration Pattern Accessibility of Infrastructure (Energy, Housing, Transport, ……) M. Fujita and J. F. Thisse, “Economics of Agglomeration”, Journal of the Japanese and International Economics, 10, pp.339-378, 1996. P. Krugman, “Increasing returns and Economic Geography”, Journal of Political Economy, 99-3 ; 484- 499. 1991.

8. (a) shows the two dimensional representation and (b) shows the three dimensional representation of expansion of two areas. Area 1 has equal expansion rate in both direction where as Area 2 has non equal expansion rate. The different growth time factor of two areas are shown in (b) (a) (b)

9. Mono-Centric  Poly-Centric Structure the original mono-centric structure of large metropolises with time tends to dissolve progressively into a poly-centric structure. Historical business center with low level of amenities, increasing car ownership, cheap land, flat topography, and street design may accentuate the tendency toward poly-centricity forces that might inhibit poly-centricity could be commercial center with high level of amenities; rail based public transport, radial primary road network, and difficult topography preventing communication between suburbs. L. S. Mayer, “The Gaming of Policy and the Politics of Gaming: A Review”, Simulation and Gaming, 40, pp. 825-862, 2009.

10. Poly-Centricity : Convolution of G i and G j

11. Control Variables : Expansion rate (An Economic Variable) !! Generate Different Plausible Scenarios Scenario Planning : Policy Planning

12. Scenario I: depicts the high absorption capacity of Bangalore and also Mysore. Bangalore engulfs its surrounding cities, and Mandya (20 km away), a relatively disadvantaged city in terms of absorption capacity becomes a part of Mysore urban agglomeration. Similarly, the interaction of the absorption capacities of Ramanagaram and Kanakpura, help form the Ramanagaram- Kanakpura-Channapatna urban agglomeration.

13. Scenario II : Mandya and Tumkar have some absorption capacity and prevent itself from being a part of Mysore or Bangalore, respectively. However, Magadi town, approximately same distance from Bangalore to Tumkur at 20 km, becomes a part of the Bangalore urban region (spreading 80 km east-west) as it fails to grow by itself.

14. Scenario III highlights the primacy of Bangalore in the region and shows the plausibility of the formation of a mega urban agglomeration.

15. Scenario Planning Scenario Planning is now an Essential Tool for Policy Makers Model based approach is computationally feasible to ‘Generate Plausible Scenarios’ The concept of alternative scenarios is already introduced in the draft of twelfth Five-Year Planning for shaping India’s future (“Scenarios: Shaping India’s Future”, Planning Commission, Government of India, June 2012)

16. Thank You