Indian Cities Research Articles

Analyzing urban footprints over four coastal cities of India and the association with rainfall and temperature using deep learning models

Capabilities of deep-learning models CNN and ConvLSTM are explored for analyzing and projecting future urban growth in four Indian coastal cities, viz., Mumbai, Chennai, Kochi, and Vishakhapatnam. ConvLSTM performed better with higher overall accuracy, Cohen's kappa, macro F1-score (> 95 %), and R2 and NSE values (> 0.87). The urbanization trends indicate a higher growth in Kochi (∼90.5 %), and greater projected rate for Mumbai (∼42.5 %). The monthly accumulated rainfall and mean temperature are analyzed and forecasted through the ConvLSTM model. The Mann-Kendall test-based analysis (with p-value <0.05), suggest no significant rainfall pattern for the cities except Mumbai, which exhibits an increasing trend. The projected rainfall trend is unaltered except for Vishakhapatnam, which is expected to increase in the coming years. The mean temperature over all the cities, shows an increasing trend (slope ∼ 0.02). However, in the coming years, the ‘increasing trend’ is expected to change into a ‘no significant trend’ for Mumbai and Vishakhapatnam. The forecasted results indicate a continuous urban expansion, which is expected to have a significant impact on rainfall and temperature trends. The outcome could assist urban planners in defining the timeline for improving drainage and include green spaces in the city development plans.

Modelling traveller mode shift behavior from personalized two-wheelers to public transit for work trips : A stated preference approach for Indian metropolitan city

This study focuses on assessing potential thrust areas that can attract personalized vehicle based daily work trips to mass transit. The proposed study specifically targets to Tier-II medium sized Indian metropolises for the estimation of a probability mode shift from personalized 2-wheelers’ to public transport on the introduction of hypothetically designed improved mass transit services. Data pertaining to study were collected through a stated preference approach that involved home-interview and online survey methods. The Latent variable enriched binary logit mode-shift behaviour model was calibrated using the Statistical Package for the Social Sciences platform and validated using hold-back data. The utility function developed using coefficients obtained through calibrated model can be further used as a user friendly tool for predicting pobability of mode shifts.The current research is an attempt to incorporate latent variables in context of Indian metropolitan area which has rarely been attempted by any researcher.

Urban Competitiveness Assessment Using the Integration of the Global Power City Index and Multicriteria Decision-Making Methods

Urban Competitiveness Assessment Using the Integration of the Global Power City Index and Multicriteria Decision-Making Methods

Emerging Epidemic: Non-Smoker Lung Cancer in India\'s Urban Centres

Abstract: Recent research has revealed a concerning trend in the incidence of lung cancer among non-smokers in India, particularly within urban centers. Contrary to the traditional association of lung cancer with smoking, a significant proportion of cases in India are now emerging in individuals with no history of tobacco use. This phenomenon is primarily attributed to severe air pollution, which has become a critical public health issue in many Indian cities. Rapid industrialization and urbanization have led to increased exposure to airborne pollutants, including fine particulate matter (PM2.5), nitrogen dioxide (NO2), and other carcinogens, which are now recognized as significant risk factors for lung cancer. Genetic predispositions further exacerbate this risk, with studies indicating that certain populations are more susceptible to developing lung cancer due to genetic mutations influenced by environmental exposures. These mutations and biomarkers, such as EGFR and ALK gene rearrangements, have been increasingly identified in Indian non-smoker lung cancer patients, providing critical insights into the disease's etiology and potential targeted therapies. India currently ranks fourth globally in lung cancer prevalence, with urban areas experiencing the highest growth rates. Projections suggest that the incidence of lung cancer will continue to rise, potentially reaching alarming levels by 2025. This emerging epidemic highlights the urgent need for comprehensive public health strategies to address air pollution and its associated health risks. Efforts must be directed towards reducing pollution levels through stringent regulatory measures, promoting cleaner technologies, and enhancing public awareness about the health impacts of air pollution. Additionally, implementing widespread screening programs and advancing research on genetic and environmental interactions can aid in early detection and personalized treatment approaches for affected individuals. In conclusion, the rising incidence of lung cancer among non-smokers in urban India signifies a shifting landscape in the disease's epidemiology. Addressing this public health challenge requires an integrated approach that combines environmental, genetic, and healthcare interventions to mitigate the growing burden of lung cancer in non-smoking populations.

Citizens’ Perception on Livability in Indian Metropolitan Cities

Background:Livability is a complex and multifaceted concept, but is important in creating places where people can thrive. Investing in the factors contributing to livability can create more attractive, sustainable, and equitable communities. Livability is important for several reasons. It can affect people’s health, well-being, and productivity. It can also influence whether people live in a particular place and whether businesses are willing to invest there.Methods:A survey was conducted to review the top livable cities of India as per the Global Livability Index parameters such as sociocultural, environmental, healthcare, education, and infrastructure aspects. A mixed method approach, having both qualitative and quantitative analyses, was adopted for the survey. The targeted sample size was 100 people, covering stakeholders from around the campus.Findings:As an outcome of the survey analysis, the most livable cities were categorized.Conclusion:In conclusion, policy narratives and frameworks are outlined emphasizing the need and the importance of citizens’ participation in assessing the quality of life across Indian metropolitan cities.

PUBLIC HEALTH POLICY RESPONSES TO AIR POLLUTION IN INDIA: CHALLENGES AND STRATEGIES FOR SUSTAINABLE DEVELOPMENT

This study investigates the public health policy responses to air pollution in India, highlighting the challenges and strategies needed for sustainable development. Despite significant efforts to address air pollution through policies such as the National Clean Air Programme (NCAP), the effectiveness of these measures remains limited. The research involved a systematic review of existing literature, policy documents, and case studies from various Indian cities. Data were collected from government reports, academic journals, and interviews with public health and environmental experts. Key findings indicate persistent issues with policy enforcement, inadequate public awareness, and insufficient coordination among agencies. These challenges impede the achievement of meaningful reductions in air pollution levels and improved public health outcomes. The study emphasizes the need for more comprehensive and robust policy frameworks to address these issues effectively. Recommendations include enhancing policy implementation, increasing public engagement, and leveraging advanced technologies for air quality monitoring and management. Addressing these gaps is crucial for advancing sustainable development and mitigating the adverse health impacts of air pollution. The research provides actionable insights for policymakers and stakeholders aiming to improve air quality and public health in India.

Modelling climate change-induced nonstationarity in rainfall extremes: A comprehensive approach for hydrological analysis

Climate change and global warming have induced a dynamic shift in extreme rainfall patterns, leading to nonstationary behaviour. This alteration in behaviour challenges conventional hydrologic design, which assumes stationarity and can yield misleading outcomes. This study aims to address nonstationarity by modelling distribution parameters with covariates. Utilizing a 70-year (1951–2020) high-resolution India Meteorological Department (IMD) gridded dataset, extreme annual rainfall across diverse Indian cities was extracted and modelled. Previous research and goodness-of-fit tests favour the Generalized Extreme Value (GEV) distribution for modelling extremes. This study incorporates indices like Nino3.4, dipole mode index, global and local temperature, CO2, and time to characterize nonstationarity in extreme annual rainfall, leveraging climate cycles and global warming. Performance assessment employs the Akaike information criterion, Bayesian information criterion and Likelihood ratio test, while quantile reliability is evaluated through confidence intervals (CIs). Findings reveal widespread nonstationary trends in most grid points, translating to wider CIs in estimated quantiles for chosen non-exceedance probability and covariates in fitted models. Generally, nonstationary conditions are associated with broader confidence bands in return levels, highlighting nonstationary model weaknesses compared to stationary models. However, the results showed that the rainfall extremes follow a nonstationary pattern. Hence, there is a strong need to develop nonstationary models of low uncertainty.

Evaluating urban population carrying capacity of Surat: probability-satisfaction approach

With around 36% of urbanisation, Indian cities are becoming saturated because of increased migration. This results in excessive utilisation of natural resources and physical infrastructure. Given its limited resources and infrastructure, it is important to evaluate an urban area’s true population carrying capacity. It helps planners and policymakers in managing cities better. This paper shows an estimation of the urban population carrying capacity of Surat City using the probability-satisfaction method with the help of factors like water treatment, solid waste management, employment, and hospital beds, which cover physical as well as social factors. Analysis shows the population carrying capacity of Surat City at different probability-satisfaction levels and compares it with the current scenario. Some important results are that when the probability-satisfaction level changes from acceptable to ideal level, Surat City’s health infrastructure has a maximum population carrying capacity of 112.1 to 102.2 million simultaneously and solid waste management has the lowest population carrying capacity, which is 4.7 to 3.9 million simultaneously. Also, it is observed that factors such as healthcare, wastewater treatment, and green area show less rigidness, while factors such as wastewater treatment, road area, and electricity show more rigidness in increasing carrying capacity.

Urban Farming, Planning and Environmental Jurisprudence in Delhi

This article analyses the manner in which bourgeois environmentalism and aspirational urban planning have brought about a recalibration of justice for agrarian communities along the Yamuna in Delhi. Bela Estate, the research site, is one such agrarian community in the urban segment of the Yamuna. Following a ban on the farming of edible crops in this region, pronounced by India’s apex environmental court in 2015, the Delhi Development Authority has conducted multiple demolition drives for nearly a decade now to evict farmers and clear their land for redevelopment. Utilising archival sources and based on a close reading of planning documents and court judgements, this article contributes to discourses of public interest in the wider context of development and law. More specifically, it decodes the ongoing contentions involving farmers, planning agencies and the judiciary in this region as symptomatic of the larger erosion of social justice in an urbanising, aspirational India that undervalues the role of nature-based livelihoods in Indian cities.

Assessing travel time performance of multimodal transportation systems using fuzzy-analytic hierarchy process: A case study of Bhopal City

Insufficient multimodal transportation infrastructure in Indian cities increases travel time, waiting time, traffic congestion, traffic accidents, travel costs, fast-growing energy consumption, and walking distance. The multimodal transportation system's journey time performance must be analysed to tackle these transportation concerns. Thus, this research provides a fundamental method for assessing multimodal transportation system trip time performance. This study proposes three steps for assessing travel time performance: identifying factors, generating individual indices, and evaluating the Multimodal Transport System Travel-Time Performance Index. The travel-time performance index of Bhopal city was 0.79 after evaluating the results of the individual indices (Access 0.49, In-vehicle 0.39, and Egress 0.38). Consequently, this study will help identify areas for improvement in Bhopal's multimodal transportation system and provide insights for enhancing its efficiency and user satisfaction. The proposed methodology can be applied to other cities facing similar challenges, aiding in the development of more sustainable and user-friendly transportation systems.

Temple Corridors in Indian Cities: A Blend of Tradition and Modernity

Temples and heritage corridors have successfully contributed to the redesign of Indian cities, yielding positive outcomes in terms of cultural heritage, tourism, and business. Such projects aid in revitalizing historical districts, preserving traditions, and fostering greater public concern for urban environments. Nevertheless, several challenges persist, such as the risk of commercialization, altering the authentic image or identity of places, social inequality during gentrification, and balancing modernization with conservation. Despite these challenges, these initiatives highlight cultural identity, which should be safeguarded through careful planning to ensure sustainable and inclusive growth. A critical question remains: has the transformation of Indian cities diminished their aesthetic and cultural value? Temple corridors in Indian cities blend Indian culture with contemporary architectural and planning techniques. This paper reviews the development, significance, and evolution of temple corridors within the urban Indian context, focusing on their roles as cultural institutions, social amenities, and tourist attractions.

Land Surface Temperature Anomalies as Indicators of Urban Land Cover Change—A Study of Two Indian Cities

Rapid urbanisation over the years has led to the loss of natural land cover, thereby affecting Land Surface Temperature (LST) distribution in urban areas. This study aims to analyse LST anomalies (calculated as the deviation from the normal) over selected Indian cities and check if critical land cover changes can be identified. LST from Landsat Thermal Infrared (TIR) images acquired in March, April and May from 1988 to 2020 were used to estimate LST anomalies. Positive LST anomalies were observed mainly over barren and impervious areas; however, some areas showed a negative anomaly where the barren lands were converted to vegetated areas. The study has demonstrated that while some developed areas exhibit a positive anomaly indicative of significant changes or development, there are instances where the conversion of barren land to developed (i.e. built up) areas has resulted in a negative anomaly. Developed areas that are closer to the water creek or mangroves were associated with lower anomaly values indicating the cooling effect of the water body and vegetation. Conversely, the core urban areas generally exhibited higher LST values with positive anomalies indicating a warming effect. These findings can be used by city planners to identify hotspot areas and develop more effective strategies and policies to address the challenges of urban heat. They also highlight the regions that require infrastructural resources and policy changes to reduce the temperature.

Seasonal dynamics of land surface temperature and urban thermal comfort with land use land cover pattern in semi-arid Indian cities: Insights for sustainable Urban Management

The cities in semi-arid and arid regions generally exhibit distinctive land use land cover (LULC) pattern and seasonal variation in urban thermal comfort (UTC) and land surface temperature (LST). This study examines the seasonal variation in LST and UTC and quantify the importance of LULC pattern in influencing LST in eight Indian semi-arid cities using Landsat 8 datasets. Random forest regression (RFR) model has been applied to quantify the influence of LULC in determining LST. The study shows that bare soil and open spaces in outskirts of selected cities have comparatively high LST than the core of cities. The mean LST varies seasonally from 12.84 °C in Udaipur to 26.18 °C in Jaipur in winter and summer. Analysis of UTC shows that autumn and winter seasons have better UTC than spring and summer seasons. RFR analysis shows a robust correlation (R2 > 0.85) between LULC and LST across all cities. Notably, built-up areas, open land, and vegetation cover exert the greatest influence on LST. Study suggests that targeted LULC planning may effectively address UTC problem in semi-arid cities and enhance sustainability. Study may help in understanding the seasonality thermal environment and assist in mitigating UHI and maintain UTC in these cities.

Land Surface Temperature Dynamics during COVID‐19 Lockdown in Diverse Climatic and Physiographic Zones—A Study of Indian Mega Cities

Land Surface Temperature Dynamics during COVID‐19 Lockdown in Diverse Climatic and Physiographic Zones—A Study of Indian Mega Cities

Linkages between ambient PM2.5 and cardiovascular mortality in a large urban cohort in two Indian cities

Linkages between ambient PM2.5 and cardiovascular mortality in a large urban cohort in two Indian cities

A bivariate simultaneous pollutant forecasting approach by Unified Spectro-Spatial Graph Neural Network (USSGNN) and its application in prediction of O3 and NO2 for New Delhi, India

Declining urban air quality affects socioeconomic stability, public health, and ecosystems and is demanding attention of the administration to address environmental sustainability goals. Given the effects of ozone, a greenhouse gas, on local climate and health, this study introduces a Unified Spectro-Spatial Graph Neural Network (USS-GNN) designed for simultaneous 24-hour forecasting of ozone and its precursor, nitrogen-dioxide, while addressing their chemical interactions and spatiotemporal dynamics. This model exploits the graph structure of atmospheric dynamics and mines high-level spatial, spectral, and physical features from atmospheric data through a Dot Product Edge Attention mechanism and a location-aware graph feature rewiring technique. The proposed model is developed for Indian capital city New Delhi, utilizes hourly observations for the years 2021 and 2022 and achieved R2 values of 0.650 and 0.618, RMSE of 13.950 and 16.120 μg/m3, MAE of 10.730 and 12.930 μg/m3 for ozone and nitrogen-dioxide respectively, outperforming state-of-the-art models. The model’s forecast analysis identified error-prone areas, effects of local meteorology, and pollutant interdependencies. An ablation study further detailed the impacts of graph operations on forecasts. Moreover, this study promotes the utility of bivariate modeling frameworks in improving urban pollution monitoring and supporting sustainable city management through data-driven policy implementations.

ANALISIS FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA DI INDONESIA MENGGUNAKAN MODEL REGRESI LOGISTIK BINER

The primary tool for assessing the extent of human development progress in a country is the Human Development Index (HDI). There are three components of Indonesia's Human Development Index (HDI). The method used to characterize the quality of human existence is based on these foundational aspects of HDI. The three elements include the role of economic advancement in human progress, as well as health, knowledge, and a decent standard of living. The objective of this research is to conduct binary logistic regression modeling to identify the key aspects that influence the Human Development Index of Regencies and Cities in Indonesia. If the response variable is binary and the predictor factors consist of one or more continuous or categorical variables, binary logistic regression is the statistical technique used to model the categorical response variable. The research results indicate that the percentage of Life Expectancy (X1), Average Length of Schooling (X2), Expected Years of Schooling (X3), and Per Capita Expenditure (X4), both partially and simultaneously, are independent variables that have the most significant impact on HDI at a real level of α = 5%. A balanced accuracy rating of 91.83% was achieved from the model evaluation, indicating that the model is useful

Experimental investigation on wireless integrated smart system for energy and water resource management in Indian smart cities

In the realm of India's smart cities, precise meter readings are essential for effectively managing domestic energy and water systems. Nevertheless, meter reading employing conventional techniques prove to be both costly and time-consuming, especially considering the vast user base and deficit of everyday consumption analysis. To cope with this challenge, the proposed solution introduces a novel unified wireless smart metering system for measuring energy and water usage. This prototype harnesses the smart, advanced metering technology to manage energy and water resources. The presence of data and remote control capabilities in smart distribution transformers offers distribution operators the chance to optimize system operation and control. The innovative system proposed utilizes smart metering technology and incorporates a distribution system self-healing mechanism against power outages, revolutionizing the way utilities manage water and energy consumption. The system not only offers real-time consumption statistics to the utility provider but also provides the flexibility to remotely control the system's turn-on and turn-off functions. The system effectively captures real-time data, transmits it via LoRa to Telegram application. The system automatically re-establishes remote connections in the event of disconnections caused by emergency conditions or non-payment of the bill, once the relevant issue has been resolved. Additionally, the system promptly notifies authorities on overload, over-temperature, and instances of electricity theft. The system proficiently generates bills based on the consumed data and seamlessly transmits the consumed units to the authorities. The innovative system proposed has proven its ability to communicate effectively, yielding results that align with the given circumstances.

Consideration of water policies in the urban development plans of Delhi: A collaborative planning perspective

AbstractThis paper discusses collaborative planning principles as a means to improve water supply systems in the case of Delhi, India, through primary and secondary data analysis. The theory of collaborative planning is a well‐established concept applied to obtain effective policies in planning through the collaboration of actors in a shared space. We use this framework to discuss strengths, weaknesses, and scope for collaboration in the current urban development plan formulation process of the city. Some of the principles of collaborative planning we use include communication, collective decision‐making processes, and network power in a shared institutional environment. Our findings indicate a lack of consideration of water policies in the urban development plans. This underlines a major gap in the current process of plan formulation and provides evidence that the absence of collaboration between institutions in both sectors contributes to poor water supply for the population in Delhi. At the same time, it emphasizes the importance of collaborative practices between urban development and water institutions for better planning of water service provision in Indian cities.

Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis

India is home to 11 % of the global urban population and is ranks as the second-largest urban system in the world. This study introduces a Heat Health Risk Index (HHRI) rankings for 37 major Indian cities with more than one million residents, using geospatial and socio-ecological data to identify potential heat health risk areas. In this study, the Otsu method was employed to determine the critical parameters in the heat health index, considering factors such as Land Surface Temperature (LST), solar radiation, population density, mean temperature, urban green cover, rainfall, specific humidity, and wind speed. All data values were standardized to a uniform scale (0–1) for comparability. The standardized values, integrated with the assigned weights, formed the HHRI. Results indicate that cities such as Chennai, Mumbai, Kolkata, and Ahmedabad, each with populations exceeding 10 million, are deemed less livable due to their high HHRI (>0.50). Both Chennai and Mumbai stand out with highest hazard index as 0.66, followed by Kolkata (0.62) and Ahmedabad (0.56). Cities that lack sufficient green spaces are often more vulnerable, display elevated risk levels, and have decreased adaptability. In contrast, cities such as Ludhiana, Theni, Amritsar, and Nabarangpur are perceived as the most livable, with a mean HHRI of 0.21, owing to their higher adaptive capacity and lower exposure. Overall, this study serves as a foundation for conceiving future perspective plans for existing urban and peri‑urban areas, compared to living standards within the realms of sustainability.