Indian Cities Research Articles

Decadal trends and climatic influences on flash droughts and flash floods in Indian cities

Flash droughts/floods are extreme weather phenomena that are expected to become increasingly frequent and severe with the changing climate. Flash droughts result from a rapid decline in soil moisture, while flash floods occur due to a high extreme rainfall intensity over a short duration. This study analyzes the ERA5 reanalysis data (hourly temperature, soil moisture, and precipitation) from 1992 to 2022 to assess flash drought/flood attribute variations across fourteen Indian cities. Flash drought events are identified based on specific conditions using the obtained Soil Moisture Index (SMI) values. At the same time, we propose a novel approach to attribute flash floods by setting thresholds for precipitation and soil moisture.This study examines the frequency and trends of flash drought and flood events across India's various Köppen-Geiger climatic zones from 1992 to 2022. Jaipur and Dehradun show a statistically significant decrease in flash drought events with magnitudes of −0.0833 events/year and −0.0769 events/year, respectively. Conversely, Hyderabad exhibits a highly significant increase in flash flood events with a magnitude of 1.1851 events/year. Similarly, Bengaluru, Varanasi, and Vishakhapatnam also show substantial increases in flash flood events. These findings underscore the impact of climate change on flash droughts/floods, highlighting the necessity for sustainable strategies.

Quantifying the potential of evidence-based planting-pattern for reducing the outdoor thermal stress from a bio-meteorological perspective in tropical conditions of Indian cities.

The impact of declined natural greenery and increased built surfaces exacerbates heat stress in urban areas causing limited usage of outdoor spaces. Greenery strategies such as trees are capable of mitigating outdoor thermal stress gain because of their phytological properties. While urban greenery guidelines have suggested the ad-hoc procedure of tree planting-schemes based on aesthetic-value, soil-water preservation etc., understanding of their morphological character help in regulating extreme thermal condition. Hence, this study aims to investigate the most efficient planting pattern based on canopies densities and trees clusters for reducing the outdoor thermal stress from bio-meteorological perspective.It initiates with the measurement of the site's morphological and meteorological attributes in existing commercial market of Bhopal City which has a humid sub-tropical climate (Aw, Koppen climate categorization). Furthermore, it leads to the development of 4-different iterated clusters incorporating moderate to high-density canopies and their overlaps pattern to estimate reduction potential in outdoors using field surveys and validated simulation model. The reduction potential in terms of magnitude and duration of thermal stress is quantified across 3-thermal variables i.e., air temperature, mean radiant temperature and universal thermal climate index. Results indicate highly-dense canopies are more effective in reducing greater magnitude of thermal stress along longer duration. Also overlapped planting pattern within the same canopy density does not make significant difference in stress reduction as compared to the changing the densities. This study will help planners and landscape architects to adopt evidence-based planting-pattern strategies for improving outdoor microclimate.

Enabling gender responsive low-carbon transport in India using SDG5 framework

<p>Gender and mobility are strongly related and address challenges of safety and accessibility for women. Studies worldwide highlight the need to create more gender-responsive transport systems that maximize women’s mobility, civic participation, and safety. Gender inequality in urban transport is evident in Indian cities in terms of women’s longer walking trip lengths, longer time spent in commute and hence time poverty, impoverished health, and compromised personal safety. Even the public transport systems, often perceived as more gender-equal, overlook women’s needs and mobility concerns such as affordability and scheduling. This article presents transportation challenges faced by women (recorded through primary surveys and focus-group discussions) and further investigates how low-carbon urban transport, as perceived under the Paris Agreement and Sustainable Development Goals (SDGs), can be delivered with gender-equitable outcomes. For a more holistic perspective, the assessment is grounded in two Indian cities, Surat (4.5 million population), a fast-growing industrial metropolis, and Udaipur (0.5 million population), a small but important tourist destination in the nation.</p>

Comparative Study of Evaluation Indicators for Learning Cities and the Implications

With the development of society, more and more cities are participating in the initiative to build learning cities. Constructing an evaluation indicator system for learning cities to monitor the progress and promote their growth has become increasingly important. This paper analyzes the preliminary framework of the UNESCO Global Learning City Index and R3L+ Quality Framework. The comparison is made from the aspects of design philosophy, criteria of indicator, and the cycle of evaluation process. The findings suggest that the construction of an evaluation indicator system should be focused more on the diversity of learning city development, the construction of an evaluation process cycle, and the significance of building cooperative networks.

Whose city is it anyway? Place, community and the fractured urban

ABSTRACT This paper examines the everyday processes of othering and exclusion of particular religious communities in expanding urbanscapes. It maps how deliberate contests are produced over cities’ histories, politico-cultural legacies and spatial arrangements, to isolate and displace communities. Specifically, it addresses how exclusion of Muslim residents is constructed in social and spatial terms in contemporary urban India. Focussing on the middle-sized central Indian city of Bhopal, I explore the emergent tensions that have steadily consolidated invisible, yet often impermeable, mental borders within that setting. In doing so, I highlight the disturbing implications of these processes of boundary making and solidification. I discuss what they mean for the everyday existence of people and communities, and how they produce fractured urbanisms. Drawing upon a mixed approach, I piece together archival records, press reports and a wide selection of other literature, as well as on-field conversations and observations, to examine how the city of Bhopal is sought to be reimaged as Hindu, and its socio-spatial character reconfigured, isolating and disenfranchising its Muslim residents. Finally, I reflect on the manner in which such shifts frame the exclusion of specific communities and produce a contested urban.

Garbage prediction using regression analysis for municipal corporations of Indian cities

AbstractGarbage management is exceptionally critical and poses enormous environmental challenges. It has always been a vital issue in municipal corporations. However, municipal agencies have developed and used garbage management systems. Garbage forecasting still plays a crucial role in the management system and helps improve or create a garbage management system. This research examines the information from 212 cities to suggest a helpful regression model for garbage forecasting and control. To establish a connection between the variables, the descriptive study employs statistical techniques to learn about the composition of data collected from municipal corporations and conduct correlation analysis. Population and garbage depend highly on one another, as evidenced by their correlation coefficient of 0.922,144. The primary research is used to build an alternate hypothesis that shows the chosen variables are highly dependent on one another. The dataset is scaled and divided into a training and testing 80:20 ratio during the pre‐processing data phase. This research aims to do a regression analysis with daily garbage production, urban area, and population as independent variables. This research initiates a variety of regression models, including multiple linear regression (MLR), artificial neural network (ANN), decision tree regression (DTR), and random forest regression (RFR). The MLR model's R2 value of 0.85 indicates that it has the potential to accurately forecast daily garbage production based on just two independent variables and a single dependent variable. Random Forest Regression (RFR) with (MSE: 100,078.749 & MAE: 182.212) shows that it has the lowest MSE among all the models, which provides the most accurate predictions on average and the fit values of 8.85 and 316.23 obtained from the error distribution with a bin value 25. The estimated results from each model are compared to the test data values on line graphs and Taylor plots. The mean square error and the mean absolute error in the analysis and the Taylor plot show that the RFR model is best suited for predicting daily garbage production in a city. This research, therefore, provides a Random Forest model that is optimal for such challenges and is recommended for this class of problem.

Crisis as inflection point in the urban governance of domestic migration in India: a policy frames analysis

The exodus of millions of domestic migrants from Indian cities during COVID-19 highlighted the failure of urban governance to address their vulnerabilities and reconfirmed that migrant integration is an intractable policy problem, where actors take oppositional and irresolvable positions. Drawing on frame analysis, which outlines agenda-setting aspects of complex policy issues, this paper explores the ideas, perceptions and beliefs of diverse governance actors – politicians, bureaucrats and civil society members – and questions whether the COVID-19 migrant crisis generated new directions in the urban governance of migration. Results show that the COVID-19 crisis generated framing contests around the role of cities in migrant inclusion that shaped new governance agendas regarding improving urban services and welfare delivery. However, owing to a persistent belief in rural sedentarism, COVID-19 failed to act as a tipping point for definitive policy towards improved urban governance of migration. The findings suggest that deeper analysis of policy frames can enrich literature on the governance of domestic migration and encourage theoretical convergences between domestic and international migration.

Gaining agency? Pandemic governance and the Indian city

Gaining agency? Pandemic governance and the Indian city

An investigation on NGR failure in Indian smart cities while replacing the existing overhead lines by underground cables

Abstract Nowadays, Indian power distribution companies (PDCs) are implementing smart distribution networks. Older cities are becoming smarter as per the recent government’s policy. Existing overhead distribution lines are being replaced by underground cables as an essential criterion of a smart city. One of the main problems arising in this process is the overheating of the neutral grounding resistor (NGR) in 11 kV distribution systems, even in normal conditions. NGRs, placed inside the substations, are overloading the air conditioning and exhaust systems of the substation. Sometimes failure of the NGR occurs due to overheating. In this paper, a comprehensive investigation has been carried out to reach the roots of this problem. It is observed that long underground cables have a higher ground capacitance than overhead distribution lines. Due to the higher cable capacitance, the third harmonic current circulates through neutral, which overheats the NGR even in normal conditions. The situation becomes worse when the substation runs on diesel generators (DGs) in an isolated state under main grid failure, as a higher amount of third-harmonic current circulates depending on the type of winding and pitch factor of the DGs. Different solutions are proposed, and their advantages and disadvantages are analyzed. Finally, the rating of the NGR is modified, and louvers-cooling fan arrangement is preferred for the running substation.

Indoor air quality assessment of an existing apartment located in Indian tropical city, Bhubaneswar

Introduction: A proper investigation on indoor pollution level in economical apartments is important, where the provision for ventilation is limited. A series of experiments were conducted in the houses within an existing economical apartment in Bhubaneswar, India to evaluate various pollutant levels. Materials and methods: Temperature, relative humidity, CO, CO2, Particulate Matter (PM10 and PM2.5), Formaldehyde and Total volatile organic compounds in the bedrooms and kitchens are measured by pollution meters. The experiments were conducted with doors and windows closed conditions. The readings were taken on a four consecutive working day in February 2023 at an interval of 3 h (9:00 am to 9:00 pm). Results: The day wise temperature and humidity variations inside the bedroom and kitchen shows a reverse trend. At the afternoon, the indoor temperature becomes high, while during the night time humidity becomes the highest. The day wise indoor CO2 and CO variation trend is pretty similar. Both CO2 and CO concentrations in bedrooms are the highest in the evening. In contrast to that CO2 and CO concentrations in kitchens becomes maximum during noon time. High particulate matter concentration at outdoor and indoor is observed at the evening time. Higher formaldehyde (HCHO) and Total Volatile Organic Compounds (TVOCs) concentration at the indoor is observed at noon and afternoon time. Conclusion: The results obtained were compared with the recommended values of World Health Organization (WHO) and National Ambient Air Quality Standards (NAQIS). The results revealed that all measured parameters are at a higher level than the recommended values except the indoor CO2 concentrations.

Building usage prediction in complex urban scenes by fusing text and facade features from street view images using deep learning

Building usage maps are inputs to many urban planning applications, however, the existing methods and the available data have limitations in generating instance-level high-resolution usage maps. In this study we tackle this problem by utilizing Street View Images (SVIs) and proposing a novel ensemble learning architecture that leverages building facade features and text extracted from hoardings, posters, etc. on buildings to predict the usage class. A pre-trained object detection model i.e., Grounding DINO, is implemented to efficiently identify buildings. A novel manually labeled training data of detected buildings corresponding to their usage is used to extract features from building facades across diverse Indian cities (Hyderabad, Mumbai, Bangalore, Delhi) using Vision Transformer (ViT) model. Following this, CLIPSeg a pre-trained segmentation model is used to recognizes text specifically on building elements like signs, posters, and banners. We then leverage GPT-3.5 Turbo, a Large Language Model (LLM), fine-tuned with a specifically designed few-shot prompting method, to infer building usage from the recognized text. To achieve optimal performance, the proposed ensemble linear metaclassifier combines predictions from ViT and LLM model. The predicted building usages are attributed to their corresponding locations to develop spatial maps. An analysis of our framework compared against ground truth data collected from various Indian cities reveals significantly accurate outcomes. Our findings highlight the utility of textual information in classifying utilities and commercial buildings, while features extracted from vision models prove more informative for residential buildings. Our approach can automate the generation of roadside building attributes and usage details on a larger scale.

Municipal Solid Waste Management System: A Study of Aligarh City, Uttar Pradesh, India

Municipal solid waste management (MSWM) is a significant environmental challenge in Indian cities, including Aligarh. Inadequate handling of municipal solid waste (MSW) poses risks to public health and the environment. Studies indicate that approximately 90% of MSW in India is improperly disposed of in open dumps and landfills, leading to various ecological and health issues. A detailed examination of Aligarh's waste management system was conducted to assess the quantity, characteristics, and sustainable management options for its municipal waste. Findings from the study show that private collectors handle about 430 tons of waste per day in Aligarh, but neither residents nor collectors engage in waste segregation at the source. The combined collection efficiency of A2Z Private Limited and the Aligarh Municipal Corporation is estimated to be around 70%. Due to the high organic content in the waste, its energy potential remains untapped. Currently, about 80% of the collected waste is disposed of in open dumps, as Aligarh lacks a sanitary landfill. This study highlights the current state of municipal solid waste management in Aligarh focusing on the quantity, quality, and management strategies in Aligarh. Methodology: For this study, Aligarh, a medium-sized city with a population of roughly 8.7 lakhs, which is located 130 kilometres from Delhi, India's capital, was chosen. A thorough assessment of the literature was done to create a theoretical framework. Visits to fields were carried out to gather basic data and comprehend the city's SWMS, including interaction During interviews with several municipality employees and executives in charge of SWM and citizens of the city. A procedure was created to examine the sources, calculate the amounts, and ascertain the waste streams' makeup. Findings: Despite their best efforts, the local municipality's limited resources do not allow for the effectiveness of the solid waste management system in Aligarh. On the outskirts of the city, waste is frequently disposed of in open or low-lying regions without using the correct scientific or engineering techniques.

Sustainable transportation infrastructure in Indian cities of different size-class: towards a research and policy agenda

Owing to the fact that the planning and management of urban transportation systems are convoluted ventures, a sound number of cities in India, especially those lacking strong institutional and financial means – principally small and medium-sized cities – have become incapable of efficiently addressing their transportation challenges. Drawing on a pan-India comparative research on 54 cities, the present study well-demonstrates a previously undetected relationship between size-class of Indian cities and their existing state of sustainable transport infrastructure development. The results speak in accordance with the notion that betterment in non-motorized and public transit infrastructure is typically associated with increasing size of cities. Accordingly, this research argues that with regard to the production of knowledge in the field of urban transportation and associated policymaking, academicians and planners can rethink and branch out the understanding of transport sustainability beyond big-metropolises of the country. This study, therefore, enunciates in support of the need for a small and medium-sized city-based research and policy agenda that can focus on eliminating the ‘sizism’ which has conventionally influenced urban theory and policymaking in India and has led to the condition of such cities as the least understood and perhaps least studied element of urban and regional transport systems.

Social sustainability of neighbourhood parks in India - instrument content validity

Neighbourhood parks are the most proximate public spaces that promote physical and mental health, well-being and happiness, social cohesion, a sense of community, etc. This vital resource can help create socially sustainable neighbourhoods in global south cities. This paper aims to develop a validated assessment framework for the social sustainability of neighbourhood parks in India. Thematic literature analysis is used to construct an assessment instrument consisting of ten variables and eighty-one indicators related to the social sustainability of neighbourhood parks. The instrument is checked for content validity through expert review using the Content Validity Index. Use of parks by people engaged in informal economic enterprises in neighbourhoods and by non-residents, the significance of ‘third places’ in park use, safety concerns, and sociocultural aspects of perception of safety emerge as essential variables to be considered in the Indian context. The high CVI of the developed instrument indicates excellent content validity. The instrument is designed to assess the provision, user perception and social use of neighbourhood green spaces in Indian cities to promote social sustainability.

Fragmented marginalities: dispossessed peasantry and migrant labour communities in urban North India

ABSTRACT Analogous to the Euro-American context, Indian cities are usually conceptualised as socio-spatial forms where communities at the peripheries of ‘development’ constitute ‘urban margins’. However, such conceptualisations rarely interrogate the varied aspects of marginality within those spaces. Drawing from an ethnography with dispossessed peasantry (in ‘urban villages’) and migrant labour (in slums/jhuggis) in Noida, a north-Indian city, we unpack three aspects of marginality. First, the process of marginalisation; second, two communities negotiating their marginality differently; third, evolving social relations within each. We propose a relational framework: supra-sub levels of structural-spatial and economic-cultural marginalisation to better understand the fragmentations within urban margins.

Reimagining Architecture Education in India: Prioritizing Sustainability, Innovation, and Multidisciplinary Collaboration through the Lens of Ancient Indian Cities

This paper explores the potential transformation of architecture education in India by integrating principles of sustainability, innovation, and multidisciplinary collaboration, drawing inspiration from the ancient Indian city planning methodologies. Through an examination of historical urban design practices, this study proposes a re-evaluation of contemporary architectural pedagogy to address contemporary India’s pressing issues of environmental sustainability, technological advancement, and interdisciplinary engagement.

Decoding Urban Intelligence: Clustering and Feature Importance in Smart Cities

The rapid urbanization trend underscores the need for effective management of city resources and services, making the concept of smart cities increasingly important. This study leverages the IMD Smart City Index (SCI) dataset to analyze and rank smart cities worldwide. Our research has a dual objective: first, we aim to apply a set of unsupervised learning models to cluster cities based on their smartness indices. Second, we aim to employ supervised learning models such as random forest, support vector machines (SVMs), and others to determine the importance of various features that contribute to a city’s smartness. Our findings reveal that while smart living was the most critical factor, with an importance of 0.259014. Smart mobility and smart environment also played significant roles, with the importance of 0.170147 and 0.163159, respectively, in determining a city’s smartness. While the clustering provides insights into the similarities and groupings among cities, the feature importance analysis elucidates the critical factors that drive these classifications. The integration of these two approaches aims to demonstrate that understanding the similarities between smart cities is of limited utility without a clear comprehension of the importance of the underlying features. This holistic approach provides a comprehensive understanding of what makes a city ’smart’ and offers a robust framework for policymakers to enhance urban living standards.

Assessing the adequacy of health facilities for the aging population in Indian cities

India, a developing country and currently the most populous nation, has been experiencing a rapid and unpredictable increase in the proportion of its older population. The healthcare system is already struggling to meet the needs of the current population, and the rising number of older adults is expected to further strain resources. Therefore, this study aimed to investigate the distribution of the older population in Indian cities and their access to advanced health facilities. The study uses data from Census of India, 2011, which is the latest census data available. A Health Facilities Index was developed to assess the availability of health facilities, and a geospatial approach was adopted to determine aging patterns and access to health facilities across cities. Despite similar aging trends, health infrastructure was unevenly distributed across cities. The study revealed that advanced health facilities were concentrated in specific areas, primarily metropolitan cities, whereas smaller cities lacked adequate health facilities and accessibility. Therefore, improving health infrastructure in smaller cities to match that in larger ones should be prioritized. The findings highlight a notable infrastructure gap in Indian cities, which presents a significant challenge to achieving healthy aging in the country.

Assessing dynamics of urban solar PV power generation using grid divisional method

The assessment of solar energy potential and urban density has become a crucial prerequisite for urban sustainable development. However, two significant challenges persist: the high computational cost associated with assessments across large urban areas and the lack of detailed rooftop information for each building. This study aims to integrate solar photovoltaic (PV) systems in urban environments of varying built density in an Indian city and assesses the solar energy potential (SEP) using grid divisional method and simulations. The methodology involved extracting, filtering and developing a 2.5 D model with GIS using the open buildings dataset, followed by simulations of grid-connected PV systems using PV-Sol. The results demonstrated the dynamics in correlation of SEP and grid morphology indicators, with built density and roof area showing a strong positive relation. The financial analysis resulted in average payback period of 8–10 years. The study also highlighted significant CO2 emission reductions, with thermal power plants generating 26,982 tons/kWh compared to just 1,513 tons/kWh for solar power. The findings demonstrate the financial viability and environmental benefits of PV adoption in urban areas, offering crucial insights for sustainable energy planning and policy development.

An analytical study on urban indices and land surface temperature

Any urban landscape needs to investigate the rising trend of land surface temperature (LST) with its surface materials. The present study analyzes the relationship of LST with three urban indices namely normalized difference built-up index (NDBI), urban index (UI), and built-up index (BUI) (by Pearson correlation coefficient method) using nine Landsat 8 OLI and TIRS data of May from 2013 to 2021 in a tropical Indian city, Raipur. Results show that the mean LST of the city was above 40 oC in 2013 but it is controlled in successive years by executing some eco-friendly activities. All the indices build a moderate to strong positive correlation with LST. NDBI is the least deviating index and it generates the best correlation. As surface materials are directly responsible for the rise of LST, suitable ecological planning is necessary for long-term urban thermal sustainability.