THE CASE OF DELHI

Delhi is in essence, a high-density, poly-centric city, ringed around a low density core occupied by the machinery of governance. The Masterplan⁷ (Figure 1) sets out land usage distribution for the city and identifies development controls in the form of setbacks, F.A.R and height restrictions. 70% of the city is built up of which approximately 70% is residential, and 30% includes commercial, industrial and other facilities. Implementation of the plan is haphazard at best and as such the city reflects both planned and emergent patterns. spatial measure used is Normalised Angular Choice (NACH)¹⁰ measured at various scales. The resultant spatial character (Figure 2) has been compared with actual observed built use characteristics.

It was found that the highest order of non-residential activity aligned with

the highest intensity of activity. The next order of intensity was found where a street had exceptionally high radius N or radius 5km NACH values indicative of singular high order movement. Low order non-residential activity was observed at the overlap of high 1km and 2km NACH values, again indicative of a diversity of local movement patterns. The distribution of these values are illustrated in Figure 3, and tabulated in Table 1 below.

Figure 1: Master Plan for Delhi (Source: Delhi Development Authority)

Urban blocks have been created by ‘subtracting’ the axial lines from a background assuming an average road with of 20m. These urban blocks are given an RPI value as the maximum RPI value available on the line segments immediately proximate. Several blocks identified for future development have areas well in excess of 1 million sq m, and all such areas have been subsequently devalued to an RPI of 0. It is envisaged that these areas can be revalued once primary grids are in place.

The derived RPI values of these urban blocks have been represented in a proposed RPI Block Map (figure 4) graded from dark to light. The highest RPI value of 3 (coloured black) reflects the city level foreground network suitable for city level facilities. Similarly an RPI value of 2 (coloured dark grey) represents the intermediate (sub-city) centres, while RPI of 1 (coloured light grey) corresponds to local neighbourhood centres. All other areas have an RPI of 0 denoting the background (mainly residential) network of the city. Here, approximately 19% of the city forms the high resource consuming foreground network, with the remaining 81% forming the mainly residential background fabric.

This map, though similar in some respects to the land-use map, is based on natural accessibility patterns of the city network, clearly articulates the preferred corridors of commercial development in the city, provides an analytic approach to identifying these corridors and forms the primary tool for planning a sustainable city. (Figure 5)

Outcomes

The outcome of such a system affects the environment, society and the economy. It provides a single framework that ties these three strands of sustainable development together. Since the system embraces the idea that resources are finite it requires thinking at planetary, national and local levels simultaneously, and combines a high degree of control over consumption levels with substantial flexibility to the end users. While developing the individual parameters of the RPI, planners can take into account local climatic conditions, socially acceptable comfort conditions, dependence on resource consuming appliances, lifestyles and resource availability in addition to determining an equitable distribution pattern providing a baseline value to the general background network and higher resource densities to foreground networks.

Economically, it allows demand and supply mechanisms at all scales to optimize the emergent patterns of built form, providing for a greater variety of economic activities and opportunities located to maximize efficiency and economic returns. It also allows traditionally low-profit but lower-consuming sectors like social housing to compete effectively with high-profit, high-consuming sectors. Socially, the system actively rewards low-consuming lifestyles, facilitates the provision of a variety of building functions where most needed, equitably redistributes resources and encourages decision making at the local level. Ecologically, this approach sets limits to resource consumption and waste, actively rewards low-consuming buildings, renewables and recycling, provides for localization of economic activity and as a result reduces travel distance, time and number of vehicular journeys. Considering that city functions are distributed according to demand at various scales, it is most likely that local demands will be met at the most appropriate locations locally and city level demands at suitable locations globally, substantially reducing the need for vehicular and long distance public transport journeys. Particular to the case of Delhi, as of 2011, is that the modal mix indicates only 30% of all journey is by personal vehicles reduced from 36% in 2001.¹¹ RITES differs slightly, identifying the 2011 share as 40%.¹² However, the reality is that both population and car ownership per person has risen exponentially.¹³ This is characterized by high pollution, road congestion and parking shortage.¹⁴ Considering that the primary

variable is the total number of journeys, and that more short journeys are undertaken than long ones, it seems reasonable to suggest that in a situation where most origin destination pairs are closely located (due to demand and supply mechanisms) the total number of trips required would substantially reduce.

Further, such a system allows a high degree of responsiveness and flexibility without the need for substantive ‘updates’ of the plan. A sustainable masterplan as proposed objectively identifies the most accessible areas at various scales and pairs them with resource consumption limits. Adjustments to the resource ‘allowance’ alone would be adequate to respond to changing urban demands, new technologies or revised international commitments. For example, were additional housing a priority, the resource share of RPI-0 could be increased. Alternatively, an increased allowance for RPI-1 areas would facilitate expansion of local and community centres. The system also utilizes a single genotype to effect a large number of phenotypes, providing substantial flexibility in determining and adapting building form and function to changes in demand and supply.

Using New Delhi as a case study, this paper demonstrates that such a framework is possible, and in general can well reflect actual emergent patterns of development.

Table 2: Sample Resource Performance Index Chart (Source: Author)

Resource

Figure 2: Normalised Angular Choice for New Delhi National Capital Region at A. radius N, B. radius 5km and C. radius 1km (Source: Author)

Figure 3: Central Delhi Segment Map with RPI Values (Source: Author)

Figure 4: Central Delhi Urban Blocks with RPI Values (Source: Author)

REFERENCES

1 Porritt, J. Capitalism as if the world matters. (London: Earthscan, 2007)

2 Arcadis. Sustainable Cities Index. Arcadis. Accessed April 25, 2015. http://www.sustainablecitiesindex.com/.

3 Hiller, B. "Cities as Movement Economies." Urban Design International, 1, (1996), 49-60.

4 Hillier, B. "Spatial Sustainabilities in Cities: Organic Patterns and Sustainable Forms." Proceedings of the 7th Space Syntax Symposium. Stockholm, 2009. Key Note 1.

5 ibid

6 Hiller, B. "Cities as Movement Economies." Urban Design International, 1 (1996), 49-60.

7 DDA. Master Plan of Delhi 2021. (New Delhi: Delhi Development Authority, 2007)

8 Axial Map is the network of least number of longest lines that represent the whole system.

9 Hillier, B, and S Iida. 2005. "Network and psychological effects in urban movement." Proceedings of Spatial Information Theory: International Conference, COSIT 475-490.

10 Hiller B., Yang T., Turner A. "Normalising least angle choice in Depthmap." The Journal of Space Syntax 3 no.2, (2012): 155-193.

11 DDA. Master Plan of Delhi 2021. (New Delhi: Delhi Development Authority, 2007)

12 RITES. Transport Demand Forecast: Delhi. RITES, 2010

13 Das, D. Dutta,S and Sharifuddin. "Car Ownership Growth in Delhi." Decision, Vol 37, No 2 (Indian Institute of Management, 2010 ).

14 Govt. of Delhi, Transport. Department of Transport, Govt of Delhi. 2010

http://www.delhi.gov.in/wps/wcm/connect/6f2ff080486859d58728c7e83e6e4488/Chapter2.pdf?MOD=AJPERES&l

mod=-336296642&CACHEID=6f2ff080486859d58728c7e83e6e4488&lmod=288106174&CACHEID=6f2ff080486859d5 8728c7e83e6e4488.

Figure 5: Detail of South Delhi showing alignment between Spatial Modelling and observed Non-Residential building uses. (Source: Author)

BIBLIOGRAPHY

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http://www.sustainablecitiesindex.com/.

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s communities have tended to consume more than what they produce. We need to urgently develop new approaches, initiatives and programmes to use the existing ones in a more effective way without over consuming. In recent years, governments and organisations have been developing some national and international programmes for providing sustainability in the cities. These programmes are generally focusing on existing building stock that is a very important source in terms of social, cultural and economic sustainability. Sustaining this stock is directly related with its quality. To ensure the sustainability idea, it is necessary to improve spatial quality in urban areas.

There are different types of buildings in existing stock in urban areas. A large part of this stock has been formed with residential buildings from different terms and has several quality problems. The main causes of the problems are related with physical, structural and infrastructural deterioration that occurred over time. For sustaining the quality, firstly, these problems should be understood and solved. This study focuses on ‘housing quality’ in terms of installations and infrastructure and aimed to understand ‘how the installing and infrastructural problems can affect housing/spatial quality?’

Installation and infrastructural problems are common physically in existing housing stock. Some reasons can be listed about the problems: short lifespan of materials, improper use, deteriorations, climate change, etc. Whatever the reason, it is important to understand user behaviours and tendencies for solving problems on this issue. Examining and understanding the maintenance behaviours and tendencies and quality perceptions of the users are important for developing an approach for improving housing quality. A field study was conducted in the 4th Levent Housing Estate that was built in the 1950s in Istanbul with modern architectural ideas. The site has been listed as an ‘urban protected area’ since 2008. The 4^th Levent Housing Estate, in which can be seen physical deterioration and functional changes, has significant spatial quality problems. The study focused on installations and infrastructural problems related with spatial quality.

A literature review on the relationship between sustainability and spatial quality was conducted.

Different refurbishment examples from European countries were examined in terms of installations and infrastructural problems along with their solutions. To understand the effects of physical problems such as installations and infrastructural problems on housing quality, a questionnaire was conducted