ORCID Profile
0000-0002-7383-2751
Current Organisation
University of Miami
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Publisher: Elsevier BV
Date: 2017
Publisher: Unpublished
Date: 2014
Publisher: National Institute of Urban Affairs (NIUA)
Date: 2013
Publisher: MDPI AG
Date: 31-03-2023
Abstract: The flood hazard risks and vulnerability in the urban areas alongside major rivers of India have been gradually increasing due to extreme climatic events. The present study is intended to assess flood hazard vulnerability and potential risk areas and aims to ascertain the management strategies in Nabadwip Municipality, a statutory urban area of West Bengal. The multi-criteria decision making (MCDM) of selected criteria and geospatial techniques have been employed to determine the urban flood vulnerability in the study area. The study has been conducted using secondary datasets including relevant remotely sensed data and participant observation. The potential flood-affected zones have been determined using the normalized difference flood index (NDFI) and flood vulnerability index (FVI). The analysis of the standardized precipitation index (SPI) of 20 years of monthly precipitation shows the variability of seasonal rainfall distribution in the study area. Furthermore, the spatial distribution of the composite Ibrahim index of socio-economic development accents that the urban development of the study area was uneven. The municipal wards situated in the central and northeastern portions of Nabadwip Municipality were extremely vulnerable, whereas the western and southwestern wards were less vulnerable. It is also revealed from the strengths–weaknesses–opportunities–challenges (SWOC) of the principal management strategies of the flood situation analysis that the unplanned sewerage system is one of the most effective weaknesses in the area. All-embracing and integrative flood management strategies need to be implemented in the study area considering the intra-regional vulnerability and development for the resilient and sustainable development of the study area.
Publisher: Cogitatio
Date: 17-11-2021
Abstract: Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area-based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case-study cities. The article examines the claims of the so-called “smart cities” against actual urban transformation on-ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT-driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.
Publisher: Elsevier BV
Date: 03-2021
Publisher: Springer International Publishing
Date: 02-07-2020
Publisher: Elsevier BV
Date: 03-2018
Publisher: Informa UK Limited
Date: 04-08-2021
Publisher: Elsevier BV
Date: 09-2019
Publisher: Wiley
Date: 02-09-2022
Abstract: Human mobility triggers how fast and where infectious diseases spread and modelling community flows helps assess the impact of social distancing policies and advance our understanding of community behaviour in such circumstances. This study investigated the relationship between human mobility and the surging incidence of COVID‐19 in India. We performed a generalised estimating equation with a Poisson log‐linear model to analyse the daily mobility rate and new cases of COVID‐19 between 14 March and 11 September 2020. We found that mobility to grocery and retail locations was significantly associated ( p 0.01) with the incidence of COVID‐19, these being crowded and unorganised in most parts of India. In contrast, visits to parks, workplaces, and transit stations did not considerably affect the changing COVID‐19 cases over time. In particular, workplaces equipped with social distancing protocols or low‐density open spaces are much less susceptible to the spread of the virus. These findings suggest that human mobility data, geographic information, and health geography modelling have significant potential to inform strategic decision‐making during pandemics because they provide actionable knowledge of when and where communities might be exposed to the disease.
Publisher: Network Design Lab - Transport Findings
Date: 19-10-2020
DOI: 10.32866/001C.17590
Abstract: To reduce the spread of COVID-19, governments across the world enacted various levels of “shelter-in-place” policies, leading to a notable reduction in urban mobility. To understand the relationship between policy implementation and mobility effects, we use Apple COVID-19 Mobility Trends Reports to assess how urban travel, by mode, changed in response to public policy. The data were used to statistically evaluate and visualize the changes in urban mobility patterns across four regions: Sydney, London, Phoenix, and Pune, which reflect the global nature of the pandemic and the local nature of policy responses. The results provide insights into how policies can receive a starkly varied response from communities across global regions.
Publisher: Springer Nature Singapore
Date: 27-09-2020
Publisher: International Information and Engineering Technology Association
Date: 02-2018
Publisher: Copernicus GmbH
Date: 14-10-2022
DOI: 10.5194/ISPRS-ANNALS-X-4-W3-2022-33-2022
Abstract: Abstract. Rapid urbanization in the emerging economies leads to immense pressure on existing amenities and urban services, and hence the congregation of smart technologies, with efficient data-driven solutions are a desirable requisite for a better quality of life, thus forming the basis of Smart cities. The concept of a smart city is multi-dimensional and is a mix of multiple factors and indicators that constitute the core concept of sustainability. One of the key indicators of a smart city is active public spaces and their consolidated wholesome implications on well-being. Hence, addressing the consequences of smart city initiatives, with respect to the access to the public realm to engage, interact, share, and recreate, through extensive literature review and case-based study seemed of prime importance. This paper attempts to unpack the smart city paradigm in India, in conjunction with aspects of social sustainability, technological interventions, and the on-ground reality while learning about their implications on the quality of life, specifically, in the case of the marginalized groups. The literature review and case-based study of three Indian smart cities, namely New Delhi, Indore, and Bhopal have opened possibilities for the identification of factors responsible for the smartness of public spaces and a realization of the extent to which theoretical concepts translate from paper to ground realities, and their immediate implications on the ‘informal’ aspects and groups of our society.
Publisher: Informa UK Limited
Date: 23-11-2020
DOI: 10.1080/09603123.2020.1847258
Abstract: This study aims to examine the spatially varying relationships between social vulnerability factors and COVID-19 cases and deaths in the contiguous United States. County-level COVID-19 data and the Centers for Disease Control and Prevention social vulnerability index (SVI) dataset were analyzed using local Spearman's rank correlation coefficient. Results suggested that SVI and four social vulnerability themes have spatially varying relationships with COVID-19 cases and deaths, which means spatial heterogeneity is an essential factor that influences the relationship, and the strength of association varies significantly across counties. County hot spots that were subject to all four social vulnerability themes during the pandemic were also identified. Local communities and health authorities should pay immediate attention to the most influential social vulnerability factors that are dominant in their region and incorporate measures tailored to the specific groups of people who are under the greatest risk of being affected during the COVID-19 pandemic.
Publisher: SAGE Publications
Date: 07-12-2022
DOI: 10.1177/23998083221142863
Abstract: COVID-19 dashboards with geospatial data visualization have become ubiquitous. There is a growing sense of responsibility to report public health data pushing governments and community organizations to develop and share web-based dashboards. While a substantial body of literature exists on how these GIS technologies and urban analytics approaches support COVID-19 monitoring, their level of social embeddedness, quality and accessibility of user interface, and overall decision-making capabilities has not been rigorously assessed. In this paper, we survey 68 public web-based COVID-19 dashboards using a nominal group technique to find that most dashboards report a wealth of epidemiologic data at the state and county levels. However, these dashboards have limited emphasis on providing granular data (city and neighborhood level) broken down by population sub-groups. We found severe inadequacy in reporting social, behavioral, and economic indicators that shape the trajectory of the pandemic and vice versa. Our survey reveals that most COVID-19 dashboards ignore the provision of metadata, data download options, and narratives around visualizations explaining the data’s background, source, and purpose. Based on these lessons, we illustrate an empirical experiment of building a dashboard prototype—the COVID-19 Economic Resilience Dashboard in Arizona. Our dashboard project demonstrates a model that can inform decision-making (beyond plain information sharing) while being accessible by design. To achieve this, we provide localized data, drill-down options by geography and sub-population, visualization narratives, open access to the data source, and accessible features on the interface. We exhibited the value of linking pandemic-related information with socioeconomic data. Our findings suggest a pathway forward for researchers and governments to incorporate more action-oriented data and easy-to-use interfaces as they refine existing and develop new information systems and data analytics dashboards.
Publisher: Emerald
Date: 18-11-2019
DOI: 10.1108/SASBE-04-2019-0056
Abstract: The Smart Cities Mission (SCM) in India is generating significant interest among researchers and policymakers globally. Cities under the SCM, irrespective of their locations, size, capacities or local needs, are heavily investing in technological solutions to improve civic conditions. The purpose of this paper is to build a typology and urban classification system of these 100 smart cities using a series of key performance indicators (KPIs) around urban development and access to public services. The paper also systematically recognises the ersity of challenges facing these cities and assess whether a generic technology-based approach is adequate to address them. A two-stage statistical process is employed in this typology building exercise – first, a cluster analysis is conducted to classify the selected cities, then a multiple discriminant analysis is used to characterise each classified city. The urban typology analysis finds that vast disparities remain across India’s urban centres, located in different geographical regions, in terms of access to social capital and physical infrastructure. The KPIs around education, health and social services emerged from the analysis as the most significant drivers in the urban typology building process. The lack of basic community infrastructure, especially in the small-to-medium-sized cities in India, exposes the shortcomings of a one-size-fits-all technocratic smart city development strategy that assumes foundational infrastructure is already in place for technology to take effect. The research methodologies developed in this paper offers a novel planning approach for smart city policymakers to devise place-based smart city interventions, acknowledging erse cultures and specific community needs.
Publisher: 211
Date: 2017
Publisher: Springer International Publishing
Date: 2018
Publisher: Common Ground Research Networks
Date: 2021
Publisher: Cold Spring Harbor Laboratory
Date: 22-12-2020
DOI: 10.1101/2020.12.21.20248523
Abstract: Human mobility plays a crucial role in determining how fast and where infectious diseases can spread. This study aims to investigate visit to which category of places among grocery, retail, parks, workplaces, residential, and transit stations is more associated with the incidence of COVID-19 in India. A longitudinal analysis of generalized estimating equation (GEE) with a Poisson log-linear model is employed to analyze the daily mobility rate and reported new cases of COVID-19 between March 14 and September 11, 2020. This study finds that mobility to places of grocery (food and vegetable markets, drug stores etc.) and retail (restaurants, cafes, shopping centres etc.) is significantly associated (at p .01) with the incidence of COVID-19. In contrast, visits to parks, transit stations and mobility within residential neighbourhoods are not statistically significant (p .05) in changing COVID-19 cases over time. These findings highlight that instead of blanket lockdown restrictions, authorities should adopt a place-based approach focusing on vulnerable hotspot locations to contain the COVID-19 and any future infectious disease.
Publisher: Wiley
Date: 30-05-2022
DOI: 10.1111/GEAN.12336
Abstract: In less‐developed countries, the lack of granular data limits the researcher's ability to study the spatial interaction of different factors on the COVID‐19 pandemic. This study designs a novel database to examine the spatial effects of demographic and population health factors on COVID‐19 prevalence across 640 districts in India. The goal is to provide a robust understanding of how spatial associations and the interconnections between places influence disease spread. In addition to the linear Ordinary Least Square regression model, three spatial regression models—Spatial Lag Model, Spatial Error Model, and Geographically Weighted Regression are employed to study and compare the variables explanatory power in shaping geographic variations in the COVID‐19 prevalence. We found that the local GWR model is more robust and effective at predicting spatial relationships. The findings indicate that among the demographic factors, a high share of the population living in slums is positively associated with a higher incidence of COVID‐19 across districts. The spatial variations in COVID‐19 deaths were explained by obesity and high blood sugar, indicating a strong association between pre‐existing health conditions and COVID‐19 fatalities. The study brings forth the critical factors that expose the poor and vulnerable populations to severe public health risks and highlight the application of geographical analysis vis‐a‐vis spatial regression models to help explain those associations.
Start Date: 2016
End Date: 2017
Funder: Department of Foreign Affairs and Trade, Australian Government
View Funded Activity