Smart Master Planning for Cities

This book explores the capabilities of Smart Master Planning as against legacy Master Planning of cities practised. Master Planning of cities exists because cities under change need uninterrupted integrated area development and urban regulation that benefits and protects the rights of all citizens under the constitution. Despite many shortcomings of Master Planning as discussed in this chapter, and which made some big-ticket national urban development projects replacing it with other short-lived plans with different names by the Union Government, it still exists in India and all countries being revised once every 20 years as per the constitution since no alternative has emerged to replace it. The 100 Smart City Programme and Jawaharlal Nehru Urban Renewal Mission (JNNURM) of India were two big-ticket National projects involving a larger amount of public investment ever received by Indian cities so far, were not using Master Plan and detailed town planning schemes for its implementation for integrated area development but is based on some other non-statutory limited time and limited scope plans which by design is short-lived and intend to die soon after the project is over with no continuity for integrated development of cities. The 100 Smart city project is strictly not even using local self-government institutional mechanism under the constitution but a special purpose vehicle to implement, unlike JNNURM. Despite all these circumstances, local self-governments continues to prepare and execute Master Plans as their constitutional responsibility despite some plan holidays years. One intend of this book is to evolve and not replace Master Planning of cities with Smart Master Planning which can broadly be classified as digital master Planning or based on innovations in some domains of Master Planning practices as alternatives keeping the intent of intention of Constitution of India respected and implemented. This book searches for an effective strengthening of Master Planning mentioned in the 74th constitutional amendment of India which we call Smart Master Planning. This can be digital or with domain-specific changes in master planning. This chapter assesses quantitatively the candidate cities for Master Planning in India based on the census 2011 and compares them with registered professional urban planners to plan it. Then discuss how the supply of candidates master Planning cities and demand of Planners can be balanced in India. This chapter explores the first scope and approach of past colonial legacy in Master Planning followed by a critique by many scholars and practising planners. This will be the basis of domain-specific master planning innovations. The Digital Master Plan which is emerging in a limited manner is then studied from practices of certain countries as an alternative for legacy master planning first with its architecture, followed by three international case studies Barcelona in Spain, Greater Spring fields in Brisbane Australia and Dublin in Ireland. Finally, it is followed by an introduction to the case study chapter by the author and his study team in one of two volumes entitled Smart Master Planning: domain innovation and digital innovation.

An urban ecosystem is intricate, and several factors collaborate to produce what we see as a city. While the dynamics of urban areas are functioning in complex ways, the conventional planning methods are generally linear and rational. This leads to an incongruity between the actual structure and the methods used to solve the resulting issues. Moreover, the accuracy and efficiency of plans prepared by conventional methods are often very less and they are not flexible. These plans do not properly respond to changes that may occur in the future. These challenges create a need to develop better planning methods for planning cities and machine learning methods can help us solve the issues. Artificial Neural Network (ANN) is one of the Machine Learning (ML) algorithms which consider various intangible, complex and nonlinear agents affecting any urban fabric. Artificial neural networks represent biological neurons and their networks. It is a black-box model, which means that the programme gets executed but the equations governing it cannot be extracted and examined. Using ANN can help in simulating various factors that are required for the preparation of a Master plan, thus improving its accuracy, time efficiency and flexibility. Using such tools can also help in better monitoring of the plans, which is otherwise time-consuming and challenging. In this study, Bhopal was selected as a case study. Even though Bhopal is the capital of the state of Madhya Pradesh, it is lagging in development as compared to several other state capitals in the country. The last master plan of the city was published in 1992, and afterwards, several attempts to make a plan have failed due to various objections arising from the side of the city’s citizens. The recent Draft Development Plan 2031, also a GIS-based Master Plan (Directorate of Town and Country Planning, Madhya Pradesh, Bhopal Development Plan‐2031, (Draft) Volume-I, Existing conditions, studies & analysis, 2020), is amid controversies regarding its ecological impacts and inaccurate mapping. In this study, ANN was used to simulate land use and land cover changes for the city of Bhopal. Using the ANN algorithm, the programme was trained with data for changes in land use and land cover from 2005 to 2018. The datasets were classified, and the algorithm was trained to check the desired accuracy. The same parameters were simulated for the year 2031 and the results were compared with the recently proposed draft development plan of the Bhopal city. The study was demonstrated how ANN could produce results that can directly be utilised as a crucial component while preparing subsequent master plans.

As 3D modeling tools and methodologies become more widespread, urban planners are beginning to think three dimensionally to address the ever-growing urban concerns, particularly in dealing with the built environment. In this chapter, the viability and necessity of using 3D GIS as a planning support system for smart master plan are examined. The interactive, dynamic, and information-rich 3D model used in this research provides an innovative method for sharing urban planning data with both urban planners and the general public. This study's methodological approach shows how 3D models can be employed as a smart master plan tool in regular urban planning activities. Every city has its planning procedure, and industry standards must be followed when integrating 3D models and 3D volumetric evaluation methodologies. More research into customization in the integration of 3D models is needed, from data collecting tactics through analysis and display. The research described in this chapter has aided in the expansion of 3D city model applications in urban planning toward a smart master plan approach. Although 3D city models improve analytical powers, adopting them into daily planning procedures necessitates more study in terms of greater analytical capabilities and adaptability. For the assessment and monitoring of growth and development, 3D technologies are an unavoidable prerequisite. Tools that are easy to use and free to download, as well as those that integrate spatial and non-spatial data more extensively. By combining 3D volumetric studies into day-to-day operations and planning processes to understand the threshold limits for growth and development, urban planners, city administrators, and lawmakers will be able to plan more efficiently.

A master plan is a dynamic long-term document to guide the future growth and development of an area. It is multidisciplinary considering all the aspects that affect the quality of life of people and the interrelationships between them.

This chapter has two parts. In the first part, objectives and the organizational details of the international collaborative research project ‘Smart Master Planning’ is discussed. The second part is presented in consultation with the team leaders of the city study, their general conclusions of the study Smart Master Planning.