Sudhira, 2008, Colloquium


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Presentation made during my Thesis Colloquium on 29-Apr-2008 at IISc.

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  • Sudhira, 2008, Colloquium

    1. 1. H S Sudhira SR No. 4-04-04-1-03766-0 Centre for Sustainable Technologies and Department of Management Studies, Indian Institute of Science, Bangalore Thesis Advisors: Dr. T V Ramachandra and Prof. M H Bala Subrahmanya
    2. 2. <ul><li>The Concept of Urban Sprawl </li></ul><ul><li>Dynamics of Urban Sprawl: A Theoretical Framework </li></ul><ul><li>Study Area: Bangalore, India </li></ul><ul><li>Patterns </li></ul><ul><li>Processes and Causes </li></ul><ul><li>Consequence and Evolution of Spatial Planning Support System (SPSS) </li></ul><ul><li>Conclusions and Future Challenges </li></ul>
    3. 4. <ul><li>Urban Scenario in India </li></ul><ul><ul><li>High rates of Urbanisation: 3-4 % </li></ul></ul><ul><ul><li>Current Urban Population around 30 % </li></ul></ul><ul><ul><li>Contribution to GDP from urban areas is around 50 - 60 % </li></ul></ul><ul><ul><li>Estimated Urban Population in 2020: 50 % </li></ul></ul><ul><li>Urbanizing Landscapes and Sprawling Cities </li></ul>GDP: Gross Domestic Product
    4. 5. <ul><li>Urbanisation </li></ul><ul><li>Urban Growth </li></ul><ul><li>Urban Sprawl </li></ul>
    5. 6. <ul><li>Dispersed development along highways, or surrounding the city and in rural countryside </li></ul><ul><li>Some type of development with implications such as loss of agricultural land, open space, and ecologically sensitive habitats </li></ul><ul><li>Unplanned and uncoordinated outgrowth </li></ul>
    6. 7. <ul><li>Spatially Explicit with </li></ul><ul><ul><li>Implications on </li></ul></ul><ul><ul><ul><li>Land-use </li></ul></ul></ul><ul><ul><ul><li>Social, Economical & Ecological </li></ul></ul></ul><ul><ul><li>Consequence of </li></ul></ul><ul><ul><ul><li>Mobility ~ Transportation Structure </li></ul></ul></ul><ul><li>Yet, Sprawling literature Lost in Semantic Wilderness (Galster et al. , 2001) </li></ul><ul><ul><li>Aesthetic Appearance </li></ul></ul><ul><ul><li>Pattern » Process » Cause » Consequence </li></ul></ul>
    7. 8. <ul><li>Initially in the USA and northwestern Europe </li></ul><ul><ul><li>Transportation Research Bureau (TRB) on Costs of Sprawl </li></ul></ul><ul><ul><li>Sprawling Cities And TransporT: from Evaluation to Recommendations (SCATTER) </li></ul></ul><ul><li>Batty et al. , (1999, 2002 and 2003), Torrens and Alberti (2000) </li></ul><ul><li>Sierra Club (USA) and Smart Growth </li></ul><ul><li>Inadequate studies in India </li></ul>
    8. 9. <ul><li>Mostly using spatial metrics ( Barnes et al. , 2001; Hurd et al. , 2001; Epstein et al. , 2002) </li></ul><ul><li>Using landscape metrics (Yeh and Li, 2001; Torrens and Alberti 2000) </li></ul><ul><li>Carrying Capacity based indicators </li></ul><ul><li>City-system based indicators </li></ul><ul><li>Sprawl Indicators </li></ul><ul><li>Sprawl Indicators for India ? </li></ul>
    9. 10. <ul><li>Comprehensive Development Plans / Master Plans </li></ul><ul><ul><li>Static Maps </li></ul></ul><ul><ul><li>Focussed on Land-use Zoning </li></ul></ul><ul><li>Nevertheless, inadequate to capture processes and other city functions, esp. mobility, resource usage, etc. </li></ul><ul><li>Urbanisation has posed great challenges for Urban Planning and Management of million-plus cities to accommodate this growth </li></ul>
    10. 11. <ul><li>GIS: Limited in scope </li></ul><ul><li>New trends: Planning Support Systems (PSS) </li></ul><ul><li>Existing PSS </li></ul><ul><ul><li>What If? </li></ul></ul><ul><ul><li>RAMCO </li></ul></ul><ul><ul><li>WADBOS </li></ul></ul><ul><li>Other frameworks for PSS </li></ul><ul><ul><li>UrbanSim </li></ul></ul><ul><ul><li>Object-Based Environment for Urban Systems (OBEUS) </li></ul></ul><ul><ul><li>Geographic Automata Systems (GAS) </li></ul></ul>
    11. 12. <ul><li>Land-use Change Models » Urban Growth Models » Urban Simulation </li></ul><ul><li>Modelling and Simulation in geospatial domain </li></ul><ul><ul><li>Cellular Automata </li></ul></ul><ul><ul><li>Agent-based models </li></ul></ul><ul><ul><li>Geographic Automata Systems (GAS) </li></ul></ul><ul><ul><li>Dynamic GeoSpatial Simulation Framework </li></ul></ul>
    12. 13. <ul><li>To evolve appropriate metrics to characterise the urban sprawl. </li></ul><ul><li>To determine the different drivers and causal factors responsible for sprawl and establish the linkages (model) for Bangalore city. </li></ul><ul><li>To design an SPSS (Spatial Planning Support System) to evaluate and review policy options in order to recommend appropriate policy and management solutions. </li></ul>
    13. 16. <ul><li>Acknowledging Scale: Three time scales have to be considered for describing the main processes of evolution of urban systems (Pumain, 2003): </li></ul><ul><ul><li>Short time process of innovation and competition, at the actor level; </li></ul></ul><ul><ul><li>Mean time – usually a few decades – process of specialisation as related to economic cycles at the level of each town and city, and </li></ul></ul><ul><ul><li>Long time process of the emergence and slow transformation of the urban hierarchy – in general, several centuries – at the level of the whole system of cities. </li></ul></ul>
    14. 17. <ul><li>The natural increase in the proportion of urban population to that of the total population, chiefly induced by migration complimented by unplanned development of outgrowth of urban areas </li></ul><ul><li>As the organic growth of cities and its outgrowth lacking any planned delivery of urban services along with requisite infrastructure and amenities </li></ul><ul><li>Distinction from developed economies and developing economies </li></ul>
    15. 18. <ul><li>The proposition is that towns and cities have evolved due to organic urbanisation than planned urbanisation </li></ul><ul><li>In the organic urbanisation cities engulf neighbouring villages and small towns, resulting in the formation of larger urban agglomerations organically </li></ul><ul><li>Sivaramakrishnan et al. (2006) detail the pattern of urbanisation in the country </li></ul>
    16. 19. <ul><li>3 variables </li></ul><ul><ul><li>Planning and Governance </li></ul></ul><ul><ul><li>Extent of Outgrowth </li></ul></ul><ul><ul><li>Level of Services & Infrastructure Provision </li></ul></ul><ul><li>Key Interactions … </li></ul><ul><ul><li>Planning and Governance are Critical </li></ul></ul><ul><ul><li>Extent of outgrowth and Level of services Interact </li></ul></ul>
    17. 20. Planning and Governance Dispersed Compact Extent of Outgrowth Sprawl City with Poor Level of Services III Compact City with Good Level of Services I Compact City with Poor Level of Services II Sprawl City with Good Level of Services IV Level of Service Poor Good Poor Good C A B
    18. 22. <ul><li>History and Culture </li></ul><ul><li>Geography and Environment </li></ul><ul><li>Demography and Economy </li></ul><ul><li>Urban Agenda: Planning and Governance </li></ul><ul><ul><li>Organizations and Stakeholders </li></ul></ul><ul><ul><li>Challenges in Managing Urban Infrastructure </li></ul></ul><ul><ul><li>Issues in Planning and Development </li></ul></ul>
    19. 24. Year Area (sq. km) 1949 69 1963-64 112 1969 134 1979 161 1995 226 2007 741
    20. 25. Characteristics Development Zones Zone 1 Zone 2 Zone 3 Authority Greater Bangalore City Corporation (formerly Bangalore City Corporation) Greater Bangalore City Corporation (formerly 8 municipal councils ) and 111 Villages) Development Authorities and other Town and Village Municipal Councils Urban Status Core city Outgrowth Potential areas for future outgrowth Infrastructure Services Present, but nearly choked, needs augmenting of existing infrastructure Not fully present, with new growth, requires planning and augmentation of infrastructure Farmlands and scattered settlements with minimal no infrastructure Impact of growth No scope for new growth but calls for urban renewal to ease congestion, etc High potential for growth since already peri-urban area and emergence of new residential layouts and other developments Mostly rural, with minimal growth currently, but potential for future growth Planning, Development and Regulation Controls Corporation operates building controls. Planning vested with BDA. Corporation operates minimal building controls. Planning vested with BDA. Planning vested with parastatal agencies: BDA and BMRDA and not other local bodies. No regulation on building/construction
    21. 27. Comprehensive Development Plan 2015 <ul><li>The Bangalore Development Authority (BDA)’s Master Plan for 2015 </li></ul>
    22. 28. <ul><li>Multiple Agencies and Plans </li></ul><ul><ul><li>Comprehensive Development Plan – BDA </li></ul></ul><ul><ul><li>City Development Plan – BBMP </li></ul></ul><ul><ul><li>Infrastructure Development and Investment Plan – KUIDFC </li></ul></ul><ul><ul><li>Comprehensive Traffic and Transportation Plan – Rites </li></ul></ul><ul><li>Rationalisation of Jurisdictions </li></ul><ul><li>Ensuring Integration and Coordination :: BMLTA </li></ul><ul><li>Disconnect with Near-to-short term Planning and Operational Planning :: MPC ? </li></ul><ul><li>Planning for Life with Philosophy, Culture Tradition and Resources </li></ul>
    23. 29. <ul><li>If we could first know where we are, and whither we are tending, </li></ul><ul><li>we could better judge what to do, and how to do it. </li></ul><ul><li>- Abraham Lincoln </li></ul>
    24. 30. <ul><li>Need for Indicators </li></ul><ul><li>Types of Indicators </li></ul><ul><ul><li>Policy-driven, </li></ul></ul><ul><ul><li>Theme-or-index driven, </li></ul></ul><ul><ul><li>Systems, </li></ul></ul><ul><ul><li>Performance, </li></ul></ul><ul><ul><li>Needs-based allocation and </li></ul></ul><ul><ul><li>Benchmarking </li></ul></ul><ul><li>Spatial Information Systems </li></ul><ul><ul><li>National Urban Information System (NUIS) of TCPO, MoUD, Govt. of India </li></ul></ul>
    25. 31. <ul><li>Systems Approach </li></ul><ul><ul><li>Pressure –State-Response (PSR) Framework </li></ul></ul><ul><ul><li>Driving forces-P-S-Implications-R (DPSIR) </li></ul></ul><ul><ul><li>Extended Urban Metabolism Model </li></ul></ul><ul><ul><li>Indicators and Information Systems (Meadows et al. , 1998) </li></ul></ul>
    26. 32. <ul><li>Carrying Capacity based Regional Planning (National Institute of Urban Affairs) </li></ul><ul><ul><li>Supportive and Assimilative Capacities </li></ul></ul><ul><ul><li>5 Modules ~ 58 Indicators </li></ul></ul><ul><li>Boston Indicators </li></ul><ul><ul><li>2005: Thinking globally/acting locally: A regional wake-up call </li></ul></ul><ul><ul><li>2007: A time like no other: Charting the course for next revolution </li></ul></ul>
    27. 33. <ul><li>Urban Indicators for Managing Cities (ADB’s Cities Data Book Project) </li></ul><ul><ul><li>Key Indices </li></ul></ul><ul><ul><ul><li>City Development Index (CDI) </li></ul></ul></ul><ul><ul><ul><li>Congestion Index </li></ul></ul></ul><ul><ul><ul><li>Connectivity Index </li></ul></ul></ul><ul><ul><li>13 themes </li></ul></ul><ul><ul><li>Parallels CDI with HDI! </li></ul></ul>
    28. 34. <ul><li>Costs of Sprawl – 2000: TRB </li></ul><ul><ul><li>Impact of Sprawl on Resources </li></ul></ul><ul><ul><ul><li>Land Conversion </li></ul></ul></ul><ul><ul><ul><li>Water and Sewer Infrastructure </li></ul></ul></ul><ul><ul><ul><li>Local Road Infrastructure </li></ul></ul></ul><ul><ul><ul><li>Local Public Service Costs </li></ul></ul></ul><ul><ul><ul><li>Real Estate Development Costs </li></ul></ul></ul><ul><ul><li>Personal Costs of Sprawl </li></ul></ul><ul><ul><ul><li>Travel Miles and Costs </li></ul></ul></ul><ul><ul><ul><li>Quality of Life </li></ul></ul></ul>
    29. 35. <ul><li>Sprawling Cities And TransporT: from Evaluation to Recommendations (SCATTER) </li></ul><ul><ul><li>Land-use </li></ul></ul><ul><ul><li>Mobility </li></ul></ul><ul><ul><li>Public Transport </li></ul></ul><ul><ul><li>Road Traffic </li></ul></ul><ul><ul><li>Accessibilities </li></ul></ul>
    30. 36. <ul><li>Demography and Economy </li></ul><ul><li>Environment and Resources </li></ul><ul><li>Mobility </li></ul><ul><li>Planning and Governance </li></ul>
    31. 37. <ul><li>Data Sources </li></ul><ul><ul><li>Questionnaire-based Household Survey </li></ul></ul><ul><ul><li>Satellite-based Remote Sensing Data </li></ul></ul><ul><ul><ul><li>National Remote Sensing Agency (Dept of Space) for IRS LISS-III 2006 </li></ul></ul></ul><ul><ul><ul><li>Global Land Cover Facility (GLCF), University of Maryland and NASA, USA for Landsat TM 1992 and Landsat ETM+ 2000 </li></ul></ul></ul><ul><ul><li>Secondary Sources </li></ul></ul><ul><ul><ul><li>From concerned Government Agencies </li></ul></ul></ul>
    32. 38. <ul><li>For a sample size of 70,00,000, with an Error rate of 5%, Precision range of 3% at 95% Confidence Level, the requisite sample size is 202.735 ~ 203 </li></ul><ul><li>Yet, distinguishing earlier BMP (3 zones) of 226 sq km and 5 new zones as two separate clusters, the total sample size for the survey is 421 (greater than 203 x 2) </li></ul><ul><li>8 Zones of Bruhat Bangalore </li></ul><ul><ul><li>3 Zones of erstwhile BMP (45 lakhs) </li></ul></ul><ul><ul><li>5 New Zones from CMCs and TMC (25 lakhs) </li></ul></ul>
    33. 39. <ul><li>Bangalore East, Bangalore West and Bangalore South Zones have a sample size of 75 each with about 7 starting points and 11 samples per starting point </li></ul><ul><li>In the five new zones, the sample size is about 42 each with about 7 starting points and 6 samples per starting point </li></ul>
    34. 40. BBMP Zones
    35. 41. <ul><li>Analysis of Survey Data </li></ul><ul><ul><li>Multi Dimensional Scaling </li></ul></ul><ul><li>Remote Sensing Data Analysis </li></ul><ul><ul><li>Band Extraction; Geo-registration; FCC Generation and Image Classification </li></ul></ul>
    36. 49. <ul><li>Built-up area has increased by 30.8 % between 1992 and 2000 </li></ul><ul><li>And further by 61.6 % between 2000 and 2006 </li></ul><ul><li>That is, about 20 sq km of built-up / paved surface annually in the last 6 years </li></ul>Land-use 1992 (sq. km) 2000 (sq. km) 2006 (sq. km) Percentage Change (2000 to 2006) Built-up 142.54 186.42 301.27 61.61 % Non Built-up 1449.35 1405.42 1291.58 -8.10 %
    37. 55. Percentage Built-up areas across zones 1992 2000 2006 Bangalore East 35.79 37.30 50.93 Bangalore West 58.09 54.23 69.38 Bangalore South 49.54 54.48 72.47 Bommanahalli 5.05 11.08 27.90 RRNagara 4.70 8.24 18.87 Dasarahalli 10.04 16.56 30.32 Byatarayanapura 6.01 11.15 24.01 Mahadevapura 8.03 13.28 26.89
    38. 60. Effectiveness of solid waste collection in all the zones when compared with the per capita expenditure is positively correlated (r = 0.79, p = 0.018)
    39. 63. Zones Population # Nature of Local Governance (until formation of BBMP) Public Participation in Preparation of Master Plan Preparation and Publication Master Plan Per Capita Expenditure (Rs.) * Bangalore East 1414831 City Corporation No Yes (BDA) 1653 Bangalore West 1292771 City Corporation No Yes (BDA) 1653 Bangalore South 1584621 City Corporation No Yes (BDA) 1653 Bommanahalli 201652 City Municipal Council No Yes (BDA) 546 Raja Rajeshwari Nagara 138840 City &Z Town Municipal Council No Yes (BDA) 583.5 Dasarahalli 264940 City Municipal Council No Yes (BDA) 187 Byatarayanapura 272571 City and Town Municipal Council No Yes (BDA) 602.5 Mahadevapura 322013 City Municipal Council No Yes (BDA) 168.65
    40. 64. No significant differences between services and healthcare (p=0.27) while they were significantly different from amenities (p=0.00093)
    41. 65. <ul><li>Non-metric Multi-Dimensional Scaling was performed </li></ul><ul><li>Variables considered were: </li></ul><ul><ul><li>population, per capita expenditure, amenities score, services score, healthcare score, nativity, house ownership, house-type: brick-walled and asbestos sheet, and brick-walled and RCC roof, access to energy sources: electricity, LPG, kerosene, firewood, solar and biogas, access to water: BWSSB/CMC, borewell, private water supply (tankers), community water taps, wastewater disposal by sewage pipe and solid waste disposal: door-to-door collection, community bins and roadside dumping </li></ul></ul><ul><li>Statistical Analysis performed using PAST </li></ul><ul><ul><li>Stress = 0; Shepard Diagram </li></ul></ul>
    42. 67. Planning and Governance Dispersed Compact Extent of Outgrowth Sprawl City with Poor Level of Services III Compact City with Good Level of Services I Compact City with Poor Level of Services II Sprawl City with Good Level of Services IV Level of Service Poor Good Poor Good C
    43. 68. <ul><li>All things appear and disappear because of the concurrence of causes and conditions. Nothing ever exists entirely alone; everything is in relation to everything else. </li></ul><ul><li>- Buddha </li></ul>
    44. 69. <ul><li>Issues </li></ul><ul><ul><li>When, What and Where? </li></ul></ul><ul><ul><li>Why & How? </li></ul></ul><ul><li>Approaches </li></ul><ul><ul><li>Statistical Models </li></ul></ul><ul><ul><li>Markov Chain Analysis </li></ul></ul><ul><ul><li>System Dynamics </li></ul></ul><ul><ul><li>Cellular Automata </li></ul></ul><ul><ul><li>Agent-based Models </li></ul></ul>
    45. 70. <ul><li>SD captures the system based on complexity involving dynamic relations represented by stocks and flows determined by various activity volumes in the city, which were synthesised from casual knowledge and observation </li></ul><ul><li>SD framework is responsive and accounts for feedback, while it is inept to represent models over a spatial domain </li></ul>
    46. 71. <ul><li>Extensively used in Urban Growth and Land-use / Land Cover Change Models </li></ul><ul><li>Can represent self-organisation and emergence of systems </li></ul><ul><li>Good for Regional level </li></ul><ul><li>Cannot reflect external dynamic drivers like </li></ul><ul><ul><li>Migrating Population </li></ul></ul><ul><ul><li>New Infrastructure, say New Outer Ring Road / New Residential Layout </li></ul></ul>CA: Cellular Automata
    47. 72. <ul><li>Using Multi-Agent Systems </li></ul><ul><li>Agents? </li></ul><ul><ul><li>From AI to Distributed Simulation Systems </li></ul></ul><ul><ul><li>In simulated time and over Cellular Space (CA) </li></ul></ul>AI: Artificial Intelligence
    48. 73. <ul><li>Issues </li></ul><ul><ul><li>Scale </li></ul></ul><ul><ul><ul><li>Spatial </li></ul></ul></ul><ul><ul><ul><li>Temporal </li></ul></ul></ul><ul><ul><li>Representation of Causal Factors </li></ul></ul><ul><ul><ul><li>Spatial: </li></ul></ul></ul><ul><ul><ul><ul><li>Vectors: Point / Line / Polygon ? </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Raster: Cell - Pixel </li></ul></ul></ul></ul><ul><ul><ul><li>Non-spatial Nature of Certain Factors </li></ul></ul></ul><ul><li>Challenges </li></ul><ul><ul><li>Integration of SD & ABM over Geospatial domain </li></ul></ul>
    49. 74. <ul><li>Identifying the variables </li></ul><ul><li>Building Causal Loop Diagrams and translating them to Stock and Flow Diagrams </li></ul><ul><li>Representing Driving Factors as Agents </li></ul>
    50. 75. <ul><li>Transportation Planning </li></ul><ul><ul><li>Key variables : travel time, desired travel time, pressure to reduce congestion, interventions by road widening / other construction, road capacity, attractiveness of driving, adequacy of public transport , public transit fare, trips per day, average trip length, traffic volume, public transit ridership, vehicles per person, vehicles in the region, extent of city within desired travel time, population and economic activity </li></ul></ul><ul><li>Land-use Planning </li></ul><ul><ul><li>Key variables: population growth, economic activity, pressure for new housing and industrial areas, land-use zoning , available land, built-up area, level of services and building height restrictions </li></ul></ul>
    51. 77. <ul><li>Reinforcing Feedbacks: outgrowth of city (R1) </li></ul><ul><li>Balancing Feedbacks: </li></ul><ul><ul><li>Capacity Expansion (B1) </li></ul></ul><ul><ul><li>Discretionary Trips (B2) </li></ul></ul><ul><ul><li>Extra Travel (B3) </li></ul></ul><ul><ul><li>Availing Public Transport (B4) </li></ul></ul>
    52. 79. <ul><li>Reinforcing feedbacks: </li></ul><ul><ul><li>housing demands (R1); </li></ul></ul><ul><ul><li>industrial demands (R2); </li></ul></ul><ul><ul><li>relocation (R3) and </li></ul></ul><ul><ul><li>infrastructure provision (R4); </li></ul></ul><ul><li>Balancing feedback: outgrowth of the city (B1) </li></ul>
    53. 80. <ul><li>Land-use Change: </li></ul><ul><ul><li>f (S t+1 ) ≈ f (LUCM, GOV, PGM, DM) + ε </li></ul></ul>
    54. 81. <ul><li>Future Land-use (S t+1 ) </li></ul><ul><li>Land-use Change Module ( LUCM = f (S t , N t , Z t , S t c ) ) </li></ul><ul><ul><li>Model Current Land-use (S t ) </li></ul></ul><ul><ul><li>Neighbourhood Land-use (N t ) </li></ul></ul><ul><ul><li>Suitability Factor (Z t ) </li></ul></ul><ul><ul><li>Land-use Constraints (Water bodies, Parks, Open spaces, etc.) (S t c ) </li></ul></ul><ul><li>Governance (GOV) </li></ul><ul><ul><li>Level of Access to Services and Amenities </li></ul></ul><ul><li>Population Growth Module (PGM) </li></ul><ul><ul><li>Birth Rate, Migration Rate, Avg. Lifetime </li></ul></ul><ul><li>Planning Module (PM) </li></ul><ul><ul><li>Land-use Policy (Comprehensive Development Plan) </li></ul></ul><ul><ul><li>Mobility </li></ul></ul><ul><ul><ul><li>Transportation Networks </li></ul></ul></ul><ul><ul><ul><li>Modal Share of Commuting </li></ul></ul></ul><ul><ul><li>Regional Growth Factor (City Development Product, District Domestic Product) </li></ul></ul><ul><li>Error ( ε ) - Random Development Probability </li></ul>
    55. 82. <ul><li>Prediction is very difficult, especially if it’s about the future. </li></ul><ul><li>- Niels Bohr </li></ul>
    56. 83. <ul><li>With an understanding of the pattern; process and causes, it is important to forecast the consequences of urban sprawl for land-use planning </li></ul><ul><li>Critical challenges for spatial planning support systems </li></ul><ul><ul><li>Participatory and Citizen Centric </li></ul></ul><ul><li>Planning in the Digital Age: Spatial Analysis and Planning Tools </li></ul><ul><li>Generating alternate futures </li></ul>
    57. 85. <ul><li>Prototype Design and Implementation </li></ul><ul><ul><li>Visualisation environment, design and implementation </li></ul></ul><ul><ul><ul><li>Implemented using NetLogo (Wilensky, 1999) - an agent-based modelling environment developed by the Centre for Connected Learning and Computer Based Modelling, Northwestern University, USA </li></ul></ul></ul><ul><ul><li>Development of prototype and evaluation </li></ul></ul>
    58. 86. INITIALIZATION Set Parameters -> User Defined or Set from earlier start-up Import land-use data, elevation, transportation networks and CDP (Land-use Policy) Initialise System Dynamics setup - Initialise for Population, Economic Growth Rate (City Development Product), Available Land   EACH TIME STEP Check for Simulation End Time and Available Land [Stop run if exceeds either of them] Compute Demand for Land (Inputs from System Dynamics Model – Stock & Flow Diagram) - Population Growth Model Runs -> Current Population - Current Population -> Population Density -> Land-use Change - Land-use Change ~ Population Density, Available Land, Economic Growth Rate - Land-use Change ~ Requirement for New Built-up Change Land-use - Obtains Built-up Demand from Land-use Change - Site-Suitability - Suitability for patches based on Distance from City Centre, Transportation Networks, Weightages for Certain Land-use based & LU Policy, and Proximity to Growth Pole - Allocate Land - Check for Built-up Demand [Stop run if exceeds current built-up or No Available Land] - Check for Maximum Site Suitability in the Neighbourhood (3x3) and allocate Land-use to Built-up Compute Metrics ~ Check for Impacts on Resources and Access to Services Update Views and Draw Plots END Agents are Growth Pole centres influencing land-use in their neighbourhood
    59. 87. <ul><li>Spatial resolution: 100 m x 100 m </li></ul><ul><li>Temporal resolution: 1 year </li></ul><ul><li>Economic Growth Rate directly affects Land-use Change through larger demand of land </li></ul><ul><li>Growth Poles » Key Work Places » Industrial Estates </li></ul>
    60. 90. <ul><li>Classified land-use (2006) </li></ul><ul><li>Simulated land-use (2006) </li></ul>The Kappa statistic (built-up areas) was 0.413 & Kloc was 0.427 with Moran’s I for the simulated and classified image was 0.643
    61. 91. <ul><li>Simulations for 2015 reveal </li></ul><ul><ul><li>Relaxed FAR resulted in increase of built-up areas (386.64 sq. km) with high densities and the rate of built-up growth declining </li></ul></ul><ul><ul><li>In the duration of increase in density of built-up areas, the population-b-density (population over built-up area) depicted “U” type behaviour </li></ul></ul><ul><li>SPSS was effective in locating areas with higher densities of built-up area and requiring augmentation of infrastructure and services to relieve the impending congestion in these localities </li></ul>
    62. 92. <ul><li>The success of these will rest on the modellers, planners who can identify and capture these processes to realise the best possibilities from SPSS </li></ul><ul><li>The scale of analysis affects the computational complexity of the system </li></ul><ul><li>Validation of SPSS :: Process Accuracy (Brown et al. , 2005) </li></ul>
    63. 93. <ul><li>Insights from Modelling Exercise </li></ul><ul><ul><li>Can represent external causal drivers </li></ul></ul><ul><ul><li>Explore implications </li></ul></ul><ul><ul><li>Reason change in land use </li></ul></ul><ul><li>But then, what about? </li></ul><ul><ul><li>Effects of New Growth Centres </li></ul></ul><ul><ul><li>Outer Ring Roads/Expressways </li></ul></ul>
    64. 94. <ul><li>Distributed Simulation </li></ul><ul><li>Community participation </li></ul><ul><li>Over the Internet </li></ul>
    65. 96. <ul><li>The Concept of Urban Sprawl </li></ul><ul><li>Theoretical Framework for Dynamics of Sprawl </li></ul><ul><li>Case of Bangalore </li></ul><ul><li>Patterns </li></ul><ul><li>Processes and Causes </li></ul><ul><li>Consequences and Evolution of SPSS </li></ul>
    66. 97. <ul><li>Patterns of Sprawl and their Indicators </li></ul><ul><li>Dynamics of Sprawl </li></ul><ul><li>Planning Support System for Managing Sprawl </li></ul>
    67. 98. <ul><li>Scale of Analysis </li></ul><ul><ul><li>Spatial </li></ul></ul><ul><ul><li>Temporal </li></ul></ul><ul><li>Limited scope on Economic and Financial Implications </li></ul><ul><li>Limited largely on existing policy levers for Land-use Planning </li></ul>
    68. 99. <ul><li>Employing Spatial Planning Support Systems for undertaking Land-use Planning and Operational Planning in urban contexts </li></ul><ul><ul><li>Requires change in KTCP Act </li></ul></ul><ul><li>Planning and Governance </li></ul><ul><ul><li>From Urban Planning towards Regional Planning </li></ul></ul><ul><ul><li>Empowering Urban Local Bodies </li></ul></ul><ul><ul><li>Evolving Best Practices (MPC, BMLTA) </li></ul></ul><ul><ul><li>A Common Jurisdiction: Key for Coordination </li></ul></ul>
    69. 100. <ul><li>Tackling Sprawl: Regulating Development </li></ul><ul><ul><li>FAR and Development Charges </li></ul></ul><ul><ul><li>Impact Fee </li></ul></ul><ul><ul><li>Restricted Development along Ring Roads </li></ul></ul><ul><ul><li>Regulation of Change in Land-use </li></ul></ul><ul><li>Integrated Land-use and Transportation Planning </li></ul>
    70. 101. <ul><li>Planning for Urbanisation </li></ul><ul><ul><li>Acknowledging the City Functions and Resource: Beyond idealised geometric plans </li></ul></ul><ul><ul><li>More Operational Tools for City Planning and Management </li></ul></ul><ul><li>A new science for City Planning ? (Batty, 2008) </li></ul><ul><ul><li>Cities as Complex Systems </li></ul></ul><ul><ul><li>Bottom-up rather than Top-down </li></ul></ul><ul><ul><li>Planning for Evolution of Cities </li></ul></ul><ul><ul><li>Requires more theories and insights </li></ul></ul><ul><li>We are but at the beginning. </li></ul>
    71. 102. <ul><li>Thesis Advisors: Dr. TV Ramachandra & Prof. MH Bala Subrahmanya </li></ul><ul><li>Prof. KS Jagadish & Prof. NJ Rao </li></ul><ul><li>Prof. KR Yogendra Simha </li></ul><ul><li>Prof. NV Joshi & Prof. Y Narahari </li></ul><ul><li>Dr. KV Gururaja, Karthick B, Sreekantha and all members of EWRG, CES </li></ul><ul><li>Faculty of CST, MGMT & CES </li></ul><ul><li>All Friends (Specially at IISc and ILP) </li></ul><ul><li>Staff of CST, MGMT & CES (Especially Bhanumathi M’am, Saleem, Sundaresh & Ananta) </li></ul><ul><li>Indian Institute of Science </li></ul><ul><li>Bruhat Bengaluru Mahanagara Palike (BBMP) </li></ul><ul><li>Global Land Cover Facility (GLCF, UMD) </li></ul><ul><li>National Remote Sensing Agency (NRSA) </li></ul><ul><li>Council for Scientific and Industrial Research (CSIR) </li></ul><ul><li>Sri. Rajeev Chandrashekar MP, Rajya Sabha </li></ul><ul><li>Sri. K Jairaj, IAS </li></ul><ul><li>Sri. Gaurav Gupta, IAS </li></ul><ul><li>Dr. DS Ravindran, IFS </li></ul><ul><li>Sri. BN Viswanath, GoK </li></ul><ul><li>Prof. Utpal Sharma, CEPT </li></ul><ul><li>Prof. Stan Geertman, Utrecht, NL </li></ul><ul><li>Dr. Moira Zellner, UIC </li></ul><ul><li>Prof. Michael Goldman, UMN </li></ul><ul><li>Dr. MB Krishna , Dr. Ajay Narendra & Vaishnav Byrappa </li></ul><ul><li>Ajay Katuri, Parth Shah & Yedendra Shrinivasan </li></ul><ul><li>Vinay Baindur & Gopi Prasad </li></ul><ul><li>Rohan D’souza, Balraj KN & Sunil </li></ul><ul><li>Ashwin (TIDE) & Shivaramu </li></ul><ul><li>My Family! </li></ul>