What is a compact city? How could it be measured? Madhu Singh Transport Planner Directorate of Urban Land Transport, Bangalore Guided By: Professor H. M. Shivanand Swamy CEPT University, Ahmedabad
Cities are facing problems in terms of living quality. Reason is said to be the sprawl. Sprawl consumes more space and resources and pays back less which needs to be regulated. In this background the Compact City concept is being put forward to contain the Sprawl and also to achieve sustainability. (Brundtland report (1987) and the Rio Declaration (1993).) Benefits of the model is outlined but consensus on the definition and measurement of the same is still lacking.
At gross level, measurement of Urban Form taking 19 cities as sample. At detailed level, measurement of Urban Form by taking two cities as case study in a spatio-temporal context. Measurement of sub forms of broader Urban form. Analyzing the effectiveness of measurement methods and the issues involved in the same.
Study does the measurement of urban form at two levels: At gross level on visual basis. Variables: Area At detailed level on visual and statistical basis. Variables: Area, density, degree of equal distribution and degree of clustering Measurement methodology at gross level: Preparation of maps for 19 cities based on some parameters. Application of formula for compactness and sprawl on cities and assigning the ranking. Preparation of network maps to see the pattern, adequacy and completeness of network.
Two boundaries of cities were required to calculate two indices that is compact and sprawl. The Parameters for contiguous area to measure compactness are: 1. Up to the contiguity of Built-up,1.* 2. Excluding water bodies, major green and open spaces, airports.2* The parameters for identifying sprawl area are: 1. Leap frog,* 2. Infill,* 3. Strip development,* 4. Using major roads as demarcation 1. metropolitan boundaries may be redefined with density and contiguity criteria (Galster et al., 2001; Tsai, 2001). 2. within a metropolitan area, undeveloped sub areas (such as rivers, mountains) may be excluded in calculating the metropolitan-form variables to reflect only the land use policy; in this way, urban sprawl caused by natural constraints can be excluded. * Jason Parent and Daniel Civco: Urban Growth Analysis: Calculating Metrics to Quantify Urban Sprawl)
A circle of area equal to that of the contiguous Built-up is drawn taking the shape centre and the proportion of the part that comes under the circle is seen to that of the total area.(jason Parent and Daniel Civco: Urban Growth Analysis: Calculating Metrics to Quantify Urban Sprawl) Sprawl Index has been calculated by taking the ratio of the total area (sprawl and contiguous Built-up) to that of the contiguous Built-up. Road Density uses the total Road Length divided by total Area (both sprawl and contiguous Built-up). Areal Extent of Two cities Bangalore Ahmedabad Legend Contiguous Area Sprawl Area
Bangalore Ahmedabad Indore Jaipur
Calculation of Compact Index using satellite imagery Timeline analysis for getting an idea of growth trends Classifying cities as per density(high, medium and low) and Analyzing the status of cities whether they are monocentric, polycentric or decentralized.
Bangalore in year 2000 Bangalore in year 2011 Ahmedabad in year 2000 Ahmedabad in year 2011 0.57 0.64 Bangalore 0.50 0.67 Ahmedabad Areas in year 2000 Areas in year 2011 Areas in 2000 Areas in 2011 2% 33% 65% water body built non-built 1% 52% 47% water body built non-built 48% 1% 51% water body built non-built 38.5 % 0.50 % 61% water body built non-built Ahmedabad Bangalore Years Change in Built-up in contiguous areas in % Change in Built-up in contiguous areas in % 2000-2011 25 % increase in built-up 21% increase in built-up
Areas in % Areas in % Area in % Areas in % Ahmedabad Percentages of built and non-built areas in 2000 120 100 80 60 % of non-built 40 % of built-up 20 0 1 3 5 7 9 11 13 15 17 19 21 23 Buffer zones Percentage of built and Non-built areas in 2011 120 100 80 60 40 % of non-built 20 % of built-up 0 1 3 5 7 9 111315171921232527 Buffer zones Bangalore Percentage of built and non-buil-up areas in year 2000 120 100 80 60 40 non built-up 20 built-up 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 Buffer zones Percentage of built and non-buil-up areas in year 2011 100 80 60 40 non built-up 20 built-up 0 1 3 5 7 9 111315171921232527293133 Buffer zones
Densities in year 2000 7% Densities in year 2011 13% high high 74% 19% medium low 61% 26% medium low Densities in year 2000 8% 12% Densities in year 2011 13% 16% High Medium Low High Medium Low 80% 71%
Gini Coefficient for Ahmedabad Gini Coefficient for Bangalore Method Index in year 2000 Index in year 2011 Gini Coefficient 0.51 0.48 Method Index in year 2001 Gini Coefficient 0.50 As per table population density in both the cities is concentrated in fewer areas though the trend for Ahmedabad can be said to be going towards the equal/even distribution. Moran Index in Ahmedabad Moran Index in Bangalore Method In year 2000 In year 2011 Moran I 0.24 0.20 Method 2001 Moran I 0.27 As per Moran I Ahmedabad was more clustered, monocentric and highly dense in 2000 while its clustering and density has decreased in the year 2011. Bangalore is more clustered, monocentric and highly dense.
Data availability and accuracy Incoherence between the administrative maps and the ground reality No uniform method and parameters Limitations of statistical methods
Study finds that there is no universal/comprehensive definition of Compact city till date. No precise characteristics have been established and authors define as per contexts and parameters. Common agreement till now is that the concept has to do with the concentration of development, using less space and consequently high density. No fixed number and framework has been put forward to let the concept fit into.
Shape of cities plays a role and circular cities tend to be more Compact rather than linear ones. Compact cities have a tendency towards Ring-Radial pattern. There is a relationship between compactness of cities and road density. Remote sensing data provides accurate details of land use as it carries vital information to be classified and analyzed in softwares like GIS and ERDAS. No single variable is able to quantify urban form on its own. Hence, a combination of all or part of the methods seems fit to be applied as per the suitability of the context. The present study brings forward data and factors which may help in decision making while planning the direction of growth of cities.
Exploring more parameters and variables to demarcate city boundaries as well as for calculation of indices. Cities should be seen from the perspective of planning history and the preparation of master plan. A look into the socio-economic dimension of cities is necessary to understand the comprehensive scenario.
* Page 231 Mike Jenks, Elizabeth Burton and Kate Williams: The Compact City: A Sustainable Urban Form?