Advances in Urban Design and Engineering

This study looks at the background of a process of intensification that cities all over the world are experiencing with the advent of globalization. This intensification process has led to high density, spurring significant debate on the effect it has on the Sustainable Quality of Life experienced by citizens. Hence, this study will explore the manner in which density has been enabling or disabling for cities, with specific reference to Indian cities. It is recognized that density is already inherent in these cities due to the spontaneous growth of informal settlements caused by migration into such cities, inequities promoted by liberalization, and lax governance. Studies show that this process of informalization has increased with liberalization and is an inherent aspect of advanced capitalism. Thus, authorities promote high density in cities through smart cities, compact-sustainable cities, transit-oriented developments, and redevelopment projects. This exists in concomitance with the growth of an informal density that is people-driven and one which grows organically. This study, thus, identifies the need to evolve a framework for exploring these densities simultaneously in the varied typo-morphologies of these cities. For such an investigation, one needs to expand the notion of density as a numerical construct closely impacted by such cities’ diverse social processes and practices. The framework should help in analyzing and observing actual patterns. The assumption is that there are many enabling aspects due to density within the present urbanization process that merit consideration. These aspects necessitate numerical methods to study density to embrace the complexity paradigm suited to explore complex social formations.

Towns and cities are cauldrons of economic opportunity and attract large labour forces of different socio-economic groups in search of a living. However, in most Indian towns, the formal housing and planned infrastructure are largely out of bounds of the urban poor. With limited resources of Urban Local Bodies, investments in housing, transport, and urban infrastructure are inadequate, usually through centrally funded schemes and are questionable in their efficacy for intended target groups. While the need for robust links between housing, mobility and access to livelihoods, is well researched and established, implementation of these principles in India is still far from adequate. This research turns the spotlight on households and their compulsions in the choice of housing locations to meet their first priority of access to livelihoods. The inevitable tradeoff between housing location and quality of housing environment results from barriers to equitable access to serviced land, housing, and mobility options in most Indian towns. From an analysis of empirical data from household level case studies, it is asserted that the State’s solutions need to also consider and link livelihood, housing and mobility choices, focusing on small and medium towns of India, to ensure target households benefit from planning interventions.

Urban economic restructuring in this information age emphasises in knowledge and innovation as key drivers of urban agglomeration and cluster. The spatial transformation of traditional settlement and rural areas occur due to the influx of knowledge and creative companies’ workers. The traditional studies on gentrification focuses on downtown regeneration by looking into the drivers of this ubiquitous characteristic of urbanism. It often overlooks the concurrent factors of change e.g., involuntary migration, accessibility and affordability of housing, and the co-existence of formal and informal economy in a developing economy. The study offers a novel patch-based analysis using Landscape Expansion Index identifying different pattern of gentrifications in the context of a developing economy where the duality creates a different facet of gentrification not explored much in literature. The chapter presents the case of Bengaluru as a knowledge city and investigates the gentrification process. It will help to understand the relationship between spatial development and economic growth.

Despite the upcoming new towns in India attempting to comply with ‘smart city’ initiatives, the determinants of sustainable planning remain elusive, thus leading to rupturing of urban systems. The conceptual shortcomings include ineffectiveness in integrating sustainable planning principles to new towns and paucity of predisposition towards people-centric development as recommended in SDG 11. This empirical research investigates the sustainability assessment of the new town ‘Navi Mumbai’, by elucidating inhabitants’ perception towards their living, transport, and community well-being. A survey was conducted among 200 recently shifted households in Navi Mumbai. In addition to the socio-economic and demographic details, the survey captured the trip details of non-mandatory activities and overall perception of liveability in the new community. Here, we hypothesize that ‘a well-planned sustainable city would derive higher satisfaction from living and travel environment which is a subject of non-polluting trips’. Exploratory analysis coupled with statistical logistic regression models was applied to understand the residents’ mode choice behaviour for short and leisure trips, weekday and weekend trips with respect to their socio-economic and demographic characteristics. It was found that 69.2 and 78% of the households availed non-motorized modes for using facilities like banks/post office and leisure facilities with 85% satisfaction response rates from female household members. While only 50% were satisfied with earlier communities, around 70–80% of the households perceived higher satisfaction after shifting to the new community. 84.6% of the households were satisfied with the living environment, whereas 80.1 and 83.6% were satisfied with the transport and traffic safety environment. Walking was the most significant mode for weekend non-mandatory trips followed by public-transit use for mandatory activities. This study would pave the way to the identification of determinants for sustainable new town planning, and formulation of environment-sensitive policies by reducing travel-based carbon footprint through efficient city planning.

Floods are one of the most frequently occurring natural disasters, causing widespread devastation, economic damage, and threat to human lives. Hydrologic impacts of climate change and intensification of urbanization are two root causes of increased flood occurrences, and recent research trends are oriented towards understanding these aspects. Due to rapid urbanization, the population of cities across the world has increased exponentially leading to improperly planned developments. On the other hand, climate change due to natural and anthropogenic activities in our environment has resulted in spatiotemporal changes in rainfall patterns. The combined effect of both aggravates the vulnerability of urban populations to floods. In this context, an efficient and effective flood risk management with its core component as flood risk mapping is essential for adaptation and mitigation of flood disasters. Urban flood risk mapping involves zoning of an urban region based on its flood risk, which depicts the spatiotemporal pattern of frequency and severity of hazards, exposure to hazards, and degree of vulnerability of the population in terms of socio-economic, environmental, and infrastructural aspects. Although vulnerability is a key component of risk, its assessment and mapping are often less advanced than hazard mapping and quantification. A synergic effort from technical experts and social scientists is vital for enhancing the effectiveness of flood risk management programmes. Despite an increasing volume of quality research conducted on urban flood risk, a comprehensive multidisciplinary approach towards flood risk mapping still remains neglected, due to which many of the input parameters and definitions of flood risk concepts are imprecise. Thus, the objectives of this review are to introduce and precisely define the relevant input parameters, concepts, and terms in urban flood risk mapping, along with its methodology, current status, and future scope. The review also aims at providing thought-provoking insights to potential future researchers and flood management professionals.

The super-cyclonic storm “Amphan” hit Eastern India, specifically the state of West Bengal, Odisha and parts of Bangladesh in May 2020 and caused severe damage to the regions. In this study, we aim to understand the self-reported effects of this natural disaster on residents of the state of West Bengal. To that end, we conducted an online survey to understand the effects of the cyclone. In total, 201 participants (spanning five districts) from the worst-affected state of West Bengal participated in the survey. This report describes our findings from the survey, with respect to the damages caused by the cyclone, how it affected the population in various districts of West Bengal, and how prepared the authorities were in responding to the disaster. We found that the participants were most adversely affected in this disaster due to disruption of services like electricity, phone and internet (as opposed to uprooting of trees and water-logging). Furthermore, we found that receiving responses to Amphan-related queries is highly positively correlated with the favorable perception of people about the preparedness of authorities. Additionally, we study the usage of online social media by the affected population in the days immediately after the disaster. Our results strongly suggest how social media platforms can help authorities to better prepare for future disasters. In summary, our study analyzes self-reported data collected from grassroots and brings out several key insights that can help authorities deal better with disaster events in future.

Systems based on Artificial Intelligence, namely Data-driven decision systems have been used in the private sector in areas such as retail, finance, and telecommunications. More recently, data-driven decision systems started to be applied in different areas of public interest, such as health, urban planning, education, criminal justice, and public administration. Several countries have been defining their own Artificial Intelligence (AI) Policies, with respective national strategies. Data-driven decision systems are, therefore, becoming an essential part of the operations of different companies and public services, on a daily basis, while creating new challenges for society. Part of those challenges is related to the risks of those systems, namely the dimensions: Bias, Explainability, and Accuracy. The ethical problems that emerge from these risks, in particular, in the public domain, make them a concern and a new challenge for Public Policy decision-makers. The goal of this work is to understand how are Bias, Explainability, and Accuracy addressed in the Cross-Industry Standard Process for Data Mining (CRISP-DM) and the Public Policy (PP) processes, and establish the parallel between these processes. In order to do that, the documents related to these topics that are listed in the “Law and Policy Reading”, published by the “AI Now Research Institute” from New York University are analyzed. In this way, Public Policy decision-makers and developers are able to identify which phases should be looked at, in both processes, when identifying, using, evaluating, and comparing these risks in tools based on Data-driven Decision Models.

India is presently the third-largest producer of electricity globally, and the growth of this sector has depended on policy decisions and legislative interventions since independence. This chapter examines the combined effects of various legislations and policy initiatives on the power sector with a focus on sustainable development, specifically the real-world consequences of these changes and their impact on the Sustainable Development Goals (SDGs). In addition, the evolution of metering in the Indian power sector through policy and legislation is also examined in detail. The recent focus on compulsory smart metering is studied in the Indian context and compared to various international initiatives. It can be concluded that smart metering can aid in reducing the financial burden on the presently distressed distribution sector while working toward achieving the related SDGs. The various challenges that are likely to be faced during the implementation of smart metering and examples of successful interventions from other countries are discussed. It is concluded that smart metering with adequate institutional support and awareness can aid in the sustainable and financially viable development of the Indian power sector.

This study presents a brief review on the current global trends in data-driven urban building energy modeling (UBEM) and explores the possibilities of applying data-driven UBEM to Indian cities. The existing research shows that availability of data that are required for UBEM is uncommon. This has led researchers to employ hybrid models that combine measured data with simulated or generated data. This study also looks into three case studies that apply data-driven techniques to conventional UBEM research. Finally, the case of data-driven UBEM in India is explored and it is seen that there exists a gap in both modeling methodologies and data sets. The DataSmart Cities strategy by the Ministry of Housing and Urban Affairs (MoHUA) provides a useful platform for data exchange. However, the current data sets available therein are not directly useful for UBEM. There is a need, therefore, to populate data sources that enable the application of  data-driven UBEM to Indian cities. This will help in addressing major energy challenges in cities while developing and supporting technology that acquires building and urban-related data at low-cost and high accuracy.