Ronita Bardhan

Pinch Analysis as a Quantitative Decision Framework for Determining Gaps in Health Care Delivery Systems

With “good health and well-being” being set as one of the targets of the Sustainable Development Goal (SDG), this paper proposes the application of pinch analysis, a quantitative method originally applied to conserve scarce resources in source-demand allocation networks, for identifying gaps in health care service delivery. This method is also found to be useful for health care infrastructure capacity planning and policy testing. The major contribution of this method in this context is identification of marginalized sections and testing specific policies targeted towards them, which will justify release of financial aid and infrastructure development for appropriate sections. We explored this concept for investigating the in-patient health care delivery system in the context of developing nations, where the health care facilities (both public and private) thrive by offering services at drastically different prices. A novel framework is developed in this paper, supported by a case study of Kolkata, India where both the gaps and surplus in the health care services faced by different sections of population are identified. In order to offset these gaps, we offer recommendations for possible policy implementation. A few hypothetical scenarios are also examined in order to understand the importance of pinch analysis for policy testing. We conclude by proving that pinch analysis can be a robust integrated decision-making framework for the health care sector, especially in resource-constrained communities.

A data-driven design framework for urban slum housing: Case of Mumbai: Poster Abstract

The current building assessment tools are limited to building performance analysis with respect to box models derived from the urban morphology of developed countries. Complex sociotechnical issues associated with rapidly urbanizing cities like Mumbai are often missed. Here, we forward a conceptual framework for designing slum habitation adheres to norms of energy, health and environmental sustainability. This can enable in designing slum rehabilitation projects such that they are not only energy efficient, but are also acceptable to the occupants. This conceptual framework attempts to bridge the missing link currently existing in the early design stages of slum rehabilitation projects. The proof of the concept is a work currently in progress, hence, here, we only elaborate on the conceptual framework exemplified through three cases of slum rehabilitation houses in Mumbai.

Applying fuzzy logic to open data for sustainable development decision-making: a case study of the planned city Amaravati

The Indian State of Andhra Pradesh is in the process of designing and constructing a planned capital city on the southern banks of the Krishna River at Amaravati. This region will see a significant increase in urban land cover and impervious surface area (ISA) under the 2050 draft perspective plan from the Andhra Pradesh Capital Region Development Authority. As the city central zone sits on the former floodplain of the Krishna River and is subject to concentrated rainfall during monsoon seasons—this increase in ISA risks increasing flood risk through preventing infiltration of storm water and causing increased peak storm water flow (NRSC 2014). The State has announced plans for a “zero-flooding city” through implementation of technologies including green roofs, porous pavement, and detention ponds (ADC 2017). This study aims to facilitate these efforts through mapping of present and future land usage, regional flood risk, and environmental services utilizing open-source data in order to maximize efficiency of installed green infrastructure and minimize future flood damages. A map of relative soil infiltration capacity was created through fuzzy overlay of sand percentage, clay percentage, and bulk density at several depths. Relative flood risk maps for both present-day land cover and a 2050 scenario were developed using several factors: elevation, flow accumulation, surface runoff, and soil properties. A novel Relative Environmental Services Provided Index is proposed here to in order to encourage cost-effective and ecologically sound development through composite visualization of carbon storage, greenery, runoff coefficients, and soil flood prevention.

Integrating rapid assessment of flood proneness into urban planning under data constraints: a fuzzy logic and bricolage approach

ABSTRACT To increase city climate resilience, a rapid data-constrained flood-proneness assessment (FPA) technique for the Kolkata Metropolitan Region (KMR) in India is proposed, and a conceptual urban-climate plan (UCP) framework capable of incorporating the FPA outputs into the mainstream planning process is developed. To overcome data and computational demands of FPA mapping, this integrated framework is based on the concept of data bricolage and integrates four flood-conditioning factors – surface elevation, normalized difference water index (NDWI), flow accumulation and surface run-off – into a single output using fuzzy inference. The KMR results show that elevation had the most significant impact on flood proneness, and that NDWI and surface run-off played a vital role in more urbanized areas.

Designing a game based persuasive technology to promote pro-environmental behaviour (PEB)

It is generally argued that the current state of degradation to environment is predominantly due to lack of appropriate human behaviour. Members of the civil society are slowly awakening to the ill-effects of inefficient waste disposal and are trying to contribute to the well-being and maintenance of the world we live in. While rules and regulations have been formulated by the governing bodies for segregating waste, efforts in this direction have not translated into a veritable pro-environmental behaviour among citizens. Pro-environmental behaviour (PEB) refers to behaviour that benefits the environment or harms the environment as little as possible. Many social processes and norms exert influence over our behavior. According to a popular thesis on human behaviour, known as the theory of planned behaviour (TPB), an individuals intention towards behavior, subjective norms and perceived control over his/her behaviour together leads to intentions and behavior [1]. School children exhibit a responsibility to induce changes in social norms for environmental friendly behaviours and are also natural early adopters of technology in this endeavor. We explore the use of persuasive technologies where behaviour-oriented design techniques are employed to change behaviors of users through persuasion and social influence. In this paper, we propose an approach for designing persuasive technologies for stoking pro-environmental behaviour and initiating waste segregation at source.

Simulation of Land Use Consequences of Urban Corridor in Kolkata: An Integrated Spatial and Expert System Model

The probability of land use to transform under the influence of transport corridors is an economic measurement unit of a specific land use defined by its accessibility level, economic level and spatial interactions. This study examines land use transitions due to development of transport corridor using expert judgement analytic hierarchy process (AHP) for measuring priority ranking of a particular land use to transit to other use, along the second Vivekananda Bridge- Belghoria Expressway(2VBBE) running through a relatively depressed urban fringe of Kolkata, India. Using the rank scores from AHP, a spatial model-Multivariate Grid Analysis (MVGA) was conceptualized to analyze the probability of transition of land activity in the zone of influence. The model has used data of over a period of 16 years (1999–2006) to find out the Transition Probability Index (TPI) of land use in the congruous lands. MVGA cumulatively uses property values, accessibility, environmental and demographic factors to project the proposed land use structure for 2020. It spatially predicted the land uses which might undergo incredible changes due to the facility development. These results can implicate policies for internalization of benefits of the corridor in urban development of Kolkata Metropolitan Area.

Building Science for low-income habitat

Lack of standardised sustainable habitat design guidelines for low-income housing plays a vital role in determining the poor quality of life in these settlements, particularly in the slums. Our work investigates process-driven pathways for developing and delivering sustainable habitat design guidelines using sociotechnical frameworks. We employ mixed-mode research methods to understand low-income habitat from the perspective of people, places and practices. We combine urban experimentation with sound simulation techniques to derive practical solutions for improving the quality of life (QoL) of the urban poor.

Urban Informal Housing and Surface Urban Heat Island Intensity: Exploring Spatial Association in the City of Mumbai

Urbanization leads to the densification of built-up areas, and thereby increases surface heat island intensity which is one of the growing concerns in the rapidly urbanizing cities. Another notable aspect of cities like Mumbai is the uncontrolled growth of informal slum housing clusters, which have emerged as a significant urban built form in the landscape of cities. This study presents a case of Mumbai that aims to explore the linkages between slum housing—here referred as ‘slum urban form’ (SUF)—and surface urban heat island (SUHI) supported by spatial-statistical analysis. The magnitude of the impact of urban form on SUHI, measured by land surface temperature (LST), is examined using Cohen’s d index, which measures the effect size for two groups—SUF and ‘formal’ housing—on LST. The results confirm a ‘large’ effect indicating a significant difference in mean LST between the two groups. The spatial analysis reveals a statistically significant spatial clustering of LST and SUF (p-value < 0.05), and bivariate local indicator of spatial association (LISA) confirms that the spatial association of SUF is surrounded by ‘high’ LST (Moran I: 0.49). The exploratory spatial analysis indicates that the contribution of SUF in elevating SUHI intensity is more than the formal housing areas and has increased vulnerability to heat stress. The results were validated on the ground using environmental sensors, which confirms the susceptibility of SUF to heat stress.