India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling.

India locked down 1.3 billion people on March 25, 2020, in the wake of COVID-19 pandemic. The economic cost of it was estimated at USD 98 billion, while the social costs are still unknown. This study investigated how government formed reactive policies to fight coronavirus across its policy sectors. Primary data was collected from the Press Information Bureau (PIB) in the form press releases of government plans, policies, programme initiatives and achievements. A text corpus of 260,852 words was created from 396 documents from the PIB. An unsupervised machine-based topic modelling using Latent Dirichlet Allocation (LDA) algorithm was performed on the text corpus. It was done to extract high probability topics in the policy sectors. The interpretation of the extracted topics was made through a nudge theoretic lens to derive the critical policy heuristics of the government. Results showed that most interventions were targeted to generate endogenous nudge by using external triggers. Notably, the nudges from the Prime Minister of India was critical in creating herd effect on lockdown and social distancing norms across the nation. A similar effect was also observed around the public health (e.g., masks in public spaces; Yoga and Ayurveda for immunity), transport (e.g., old trains converted to isolation wards), micro, small and medium enterprises (e.g., rapid production of PPE and masks), science and technology sector (e.g., diagnostic kits, robots and nano-technology), home affairs (e.g., surveillance and lockdown), urban (e.g. drones, GIS-tools) and education (e.g., online learning). A conclusion was drawn on leveraging these heuristics are crucial for lockdown easement planning

Building Science for low-income habitat

Lack of standardized sustainable habitat design guidelines for low-income housing plays an important role in determining the poor quality of life in these settlements, particularly in the slums. My work investigates process-driven pathways for developing and delivering sustainable habitat design guidelines using socio-technical frameworks. I employ mixed-mode research methods to understand low-income habitat from the perspective of people, places and practices. I combine urban experimentation with robust simulation techniques to derive practical solutions for improving the quality of life (QoL) of the urban poor. Urban experimentation includes data acquisition through in-situ environmental sensing of the low-income habitations, modelling of the houses, calibration of the sensed data, and its urban scale building energy calculations using state-of-the-art building energy simulation techniques. I integrate the socio-cultural stochastics in the building simulation framework to derive empirical evidence of the urban QoL in these settlements. There are three cohorts of my research: 1) Investigation of building performance; 2) Spatial analytics for urban sustainability and policy analysis; 3) Data-driven simulation and modelling techniques for derivation of low-income sustainability heuristics.Ministry of Human Resource Development, Government of Indi

Factors Affecting Residential Satisfaction in Slum Rehabilitation Housing in Mumbai

Affordable housing for the low-income population, who mostly live in slums, is an endemic challenge for cities in developing countries. As a remedy for the slum-free city, most of the major metropolis are resorting to slum rehabilitation housing. Rehabilitation connotes the improved quality of life that provides contentment, yet what entails residential satisfaction in such low-income situations remains a blind spot in literature. The study aims to examine the factors affecting residential satisfaction of slum rehabilitation housing in Mumbai, India. Here, the moderation effects of sociodemographic characteristics between residential satisfaction and its predictors are elaborated using a causal model. Data on residents’ perception of the residential environment were collected from 981 households in three different slum rehabilitation housing areas spatially spread across Mumbai. The causal model indicated that residential satisfaction was significantly determined by internal conditions of dwelling resulting from design, community environment and access to facilities. Gender, age, mother tongue, presence of children, senior citizens in the family, and education moderate the relationship between residential satisfaction and its predictors. The need for design and planning with the user’s perspective is highlighted to improve the quality of life

A data-driven and simulation approach for understanding thermal performance of slum redevelopment in Mumbai, India

Over 54% of the world’s population reside in informal settlements like slums. Thus, any meaningful strategy for transitioning the world toward a more sustainable urban built environment must address the redevelopment of slum communities. This study aims to take a first-step towards the design optimization of slum redevelopment by evaluating the thermal performance of various urban slum redevelopment morphologies in Mumbai, India. We propose a data-driven and simulation-based approach to understand how slum redevelopment morphologies impact thermal performance and validate our approach using real data collected from a field site in the Dharavi slum, Mumbai, India. Results indicate that the existing horizontal form outperforms proposed vertical redevelopment forms in terms of maintaining lower operating temperatures. In other words, vertical redevelopment could worsen thermal comfort conditions for existing residents. Given the current push towards vertical housing structures by the Indian government, our results have substantial implications for the design and redevelopment of such informal settlements and lays the groundwork for establishing design guidelines and processes that ensure more sustainable and inclusive redevelopment

開発途上国の急速に都市化する高密度都市における都市構造と生活の質の関係性評価 : インドのコルカタを例に

学位の種別:課程博士University of Tokyo(東京大学

The effects of urban morphology on enriching thermal experience : microclimates of courtyard spaces in Cambridge

The microclimate shaped by urban form is one of the critical determinants for the success of public spaces. To date, hundreds of studies have revealed the potential of mitigating heat and cold stresses by spatial-enclosure strategies to reduce thermal discomfort. However, most of them have placed more emphasis on taming the thermal extremes, rather than on enriching the microclimatic context to benefit the thermal experience. A rich thermal context with varied, mild thermal stress would enhance psychological adaptation, affording flexibility and meeting different thermal preferences of sun, shade, wind and stillness. Therefore, we aim to investigate the morphological effects on these thermal qualities, and to compare not only the cooling performance of geometries but also the microclimatic diversity and hourly fluctuation in thermal stress. More than a hundred fully enclosed courtyards (n=107) were selected across 31 colleges and 10 teaching sites at the University of Cambridge. We have completed 20-hour microclimate simulations at 33 domains with boundary conditions near the summer solstice and the ENVI-met simulation results were fed back into the heatmap through Urbano, Dragonfly and Ladybug plugs-in in Grasshopper. We found much stronger morphological effects on the variations of sun and wind than on air temperature and humidity. The inferential statistical analysis has also shown that the compacity of building shades and the vegetation configurations play crucial roles in taming thermal extremes and enriching the urban thermal contexts at the human scale

Inaugural Editorial of Urban Planning

This editorial is the introductory piece of Urban Planning, a new international peer-reviewed open access journal of urban studies aimed at advancing understanding of and ideas about humankind’s habitats in order to promote progress and quality of life

How does slum rehabilitation influence appliance ownership? A structural model of non-income drivers.

This study explores the effect of slum rehabilitation on appliance ownership and its implications on residential electricity demand. The low-income scenario makes it unique because the entire proposition is based on the importance of non-income drivers of appliance ownership that includes effects of changing the built environment (BE), household practices (HP) and appliances characteristics (AC). This study demonstrates quantitatively that non-income factors around energy practices influence appliance ownership, and therefore electricity consumption. The methodology consists of questionnaire design across the dimension of BE, HP and AC based on social practice theory, surveying of 1224 households and empirical analysis using covariance-based structural equation modelling. Results show that higher appliance ownership in the slum rehabilitation housing is due to change in household practice, built environment and affordability criteria of the appliances. Change in HP shifts necessary activities like cooking, washing and cleaning from outdoor to indoor spaces that positively and significantly influences higher appliance ownership. Poor BE conditions about indoor air quality, thermal comfort and hygiene; and product cost, discounts and ease of use of the appliances also triggers higher appliance ownership. The findings of this study can aid in designing better regulatory and energy efficiency policies for low-income settlements.RD is supported by the Bill & Melinda Gates Foundation (Grant no. OPP1144) through the Gates-Cambridge Scholarship. This study is in parts funded by Ministry of Human Resource Development, Government of India (Grant no. 14MHRD005) under the Frontier Areas in Science and Technology grant awarded to RB