Chennai Metropolitan Area Research Articles

Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology.

Flood disasters are frequent natural disasters that occur annually during the monsoon season and significantly impact urban areas. This area is characterized by impermeable concrete surfaces, which increase runoff and are particularly susceptible to flooding. Therefore, this study aims to adopt Bi-variate statistical methods such as frequency ratio (FR) and weight of evidence (WOE) to map flood susceptibility in an urbanized watershed. The study area encompasses an urbanized watershed surrounding the Chennai Metropolitan area in southern India. The essential parameters considered for flood susceptibility zonation include geomorphology, soil, land use/land cover (LU/LC), rainfall, drainage, slope, aspect, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The flood susceptibility map was derived using 70% of randomly selected flood areas from the flood inventory database, and the other 30% was used for validation using the area under curve (AUC) method. The AUC method produced a frequency ratio of 0.806 and a weight of evidence value of 0.865 contributing to the zonation of the three classes. The study further investigates the impact of urbanization on flood susceptibility and is further classified into high, moderate, and low flood risk zones. With the abrupt change in climatic scenarios, there is an increase in the risk of flash floods. The results of this study can be used by policymakers and planners in developing a preparedness system to mitigate economic, human, and property losses due to floods in any urbanized watershed.

GIS-based Social Vulnerability Integration for Robust Flood Response, Disease Prevention and Community Resilience in Chennai Metropolitan Area post-Cyclone Michaung

The present study outlines a comprehensive strategy for flood response, disease prevention and long-term community resilience in the aftermath of a recent Cyclone Michaung, with the proximity of landfall near Chennai and the increased likelihood of flooding in the CMA. Drawing insights from an existing social vulnerability map, the study addresses the unique challenges posed by flooding and aims to mitigate the heightened risk of waterborne and vector-borne diseases. Objectives encompass assessing social vulnerability, formulating a targeted flood response strategy, implementing healthcare interventions for disease prevention, strengthening information dissemination and advocating for long-term resilience planning. The methodology involves reviewing the existing vulnerability map, identifying vulnerable communities, integrating flood impact data and developing a comprehensive response plan. The study utilizes GIS and Remote Sensing technologies for monitoring and assessing the results. Key findings from the social vulnerability assessment inform prioritized intervention areas for both flood response and disease prevention. The discussion interprets results in the context of strategy effectiveness, emphasizing the significance of a nuanced and inclusive approach. This manuscript serves as a guide for stakeholders in implementing a holistic strategy that addresses immediate concerns, prevents disease outbreaks and fosters long-term community resilience.

Impact of Urban Vegetation Loss on Urban Heat Islands: A Case Study of Chennai Metropolitan Area

Impact of Urban Vegetation Loss on Urban Heat Islands: A Case Study of Chennai Metropolitan Area

Modelling urban freight generation using linear regression and proportional odds logit models

Receivers and intermediary establishments typical to urban areas have unique freight behaviour and are understudied, particularly in developing countries. This paper uses establishment-based freight survey data to examine their freight generation patterns in the Chennai metropolitan area, India. Three sets of Simple Linear Regression (SLR) models, three single predictor proportional odds logit models, one multiple linear regression model, and one multiple predictor proportional odds logit model with business size (employment, area, and operational age) and indicators of establishment category as regressors are developed each for both freight production and freight attraction. Partial proportional odds logit models are developed in a few cases to overcome the limitations of proportional odds logit models. The best SLR model varied with the establishment category for freight production and attraction. The establishment area model is the best among single predictor proportional odds logit models. The multiple predictor proportional odds logit models marginally improved the fit over single predictor models. The proportional odds logit model results show that the establishment category has a greater impact on freight generation levels than business size variables. Since earlier studies rarely focused on receivers and intermediary establishments, policymakers may benefit from the developed models and study insights while estimating freight demand and developing freight policies.

Assessing the future groundwater vulnerability of an urban region under variable climatic and land use conditions

Climate change and urbanization threaten groundwater resources due to over-abstraction and contamination. Groundwater vulnerability assessment aids in protecting groundwater resources; DRASTIC is the widely used groundwater vulnerability model (GVM) to assess vulnerability. This study uses an optimized DRASTIC framework to assess the impact of climate and land use change on the future groundwater vulnerability of Chennai Metropolitan Area (CMA). The frequency ratio (FR) and metaheuristic (MH) algorithms are coupled to optimize the rates and weights of GVM to reduce subjectivity. The climatic variables and land use projected for the future period 2030 and 2050 under RCP4.5 and RCP8.5 scenarios. The projected net recharge for the study region varies from 349.95 mm/yr to 458.95 mm/yr, and depth to groundwater level ranges between 4.92 and 6.42 mbgl for scenarios 1 to 4. The RCP4.5 scenario for the far future period (scenario-2) shows an increase in the vulnerability class by 41.64%, and RCP8.5 scenario for the far future period (scenario-4) exhibits a decrease in the vulnerability class by 20.67% of the total area. The integrated groundwater vulnerability analysis found that the CMA groundwater system is in critical condition of high vulnerability for near and far future periods.

Understanding the relationship between Urban Heat Island and Urban Vegetation by reviewing three decades of satellite images for the Chennai Metropolitan Area

Urbanization has led to one of the most important climatic issues i.e., the Urban Heat Island (UHI) phenomenon. In Chennai Metropolitan Area (CMA), the overall distribution of the green cover has gradually succumbed to urbanization whereas the temperatures have soared by 1.3 deg C in the past six decades. Urban vegetation provides shade and protects the buildings from direct solar exposure, thus reduces the UHI. Further, it also sequester large quantities of carbon, reduce storm water runoff and function as noise filters and pollutant traps. In comparison with the international UHI studies, the studies concerning Indian UHI are limited. Hence, the aim of the current research work is to understand the seasonal relationship between Land Surface Temperature (LST) and the Normalised Difference Vegetation Index (NDVI) of CMA using LANDSAT 4, 5, 7 and 8 images captured during the years 1988, 1991, 1996, 2000, 2008, 2013 and 2016. The results are discussed under three parts namely, Part-A, Part-B, and Part-C. Part-A results infer that the CMA is covered predominantly by minimum LST values (9 deg C to 25 deg C) and maximum LST values (25 deg C to 50 deg C) during Monsoon and Summer/Post-Monsoon seasons, respectively. The mean LST of the CMA is between 18 deg C to 31 deg C throughout the year. In Part B analysis results, the study establishes a moderate seasonal correlation between LST and the NDVI values (r-values between -0.2648 and 0.3604). According to Part C results, ‘High Vegetation’ (NDVI values 0.5 to 1) has a significant role in maintaining the average LST during all four seasons. Further, it also has the potential to reduce the LST values during the summer season in CMA. However, due to a moderate correlation, the urban vegetation may reduce the LST value only as an outcome of reducing the rest of the UHI contributors.

PCA-based approach for mapping social vulnerability to hazards in the Chennai metropolitan area, east coast of India

ABSTRACT Social vulnerability shows the lack of capacities of a person or groups across space and time to prepare for, respond to, and recover from the impact of natural hazards. It involves a combination of socioeconomic and demographic factors that determine the degree to which a (human) system is susceptible to, or unable to cope with, the adverse effects of a disastrous event. Social Vulnerability Index (SoVI) is an effective tool to measure the social vulnerability of an area. Though SoVI has successfully applied in many different contexts and places for socioeconomic development and disaster risk reduction, most societies still lack awareness of how social differences within their population play a role during disastrous events. To address this gap, the present study aims to map the social vulnerability and identify the locations of a socially vulnerable community in the Chennai Metropolitan Area (CMA) through an inductive approach (e.g. factor analysis) using demographic and built-environment data in ArcGIS and SPSS environment. We analysed twenty-three individual variables from five different vulnerability components, such as population, housing, economics, healthcare service, and exposed elements using Principal Component Analysis, that reduced to a smaller set of multidimensional components that explained 71.2% of the total variance and calculated the final SoVI score by adding all five-factor scores. The resultant SoVI map identifies the most vulnerable areas in the highly populated and tightly packed residential areas of Chennai city and the least vulnerable areas on the outskirts of Chennai city. The constructed SoVI could assist planners and policymakers at the national, state, and local government level in making appropriate decisions at all phases of the disaster management cycle and help prioritize the implementation of Government welfare schemes.

Dynamics of urban sprawl on the peri-urban landscape and its relationship with urban heat island in Chennai Metropolitan Area, India

Dynamics of urban sprawl on the peri-urban landscape and its relationship with urban heat island in Chennai Metropolitan Area, India

Estimation of natural groundwater recharge in Chennai River basin using multiple approaches

ABSTRACT Groundwater is vital in Chennai Metropolitan Area, and thus its sustainable management is essential. This study aims to estimate groundwater recharge in the Chennai River basin (CRB) using an empirical method, a rainfall infiltration factor (RIF) method, a geographical information system (GIS)-distributed model, and the water table fluctuation (WTF) method. The average recharge estimates were 196 mm/year (empirical), 127 mm/year (WTF), and 122 mm/year (RIF). These results agree with the estimate of the GIS-distribution model, where 59% of the area has high recharge (>100 mm/year). The effective recharge from rainfall was around 10% with the RIF and WTF methods and 16% using the empirical method. All the estimates were statistically significant with confidence levels of over 98%, using a 95% confidence interval. The WTF method (with a 99.9% confidence level) was the most reliable of the four approaches. However, we suggest using multiple methods to cross-check the results and that measuring rainfall and water level is necessary for accurate recharge estimates in the future.

Spatial Seemingly Unrelated Regression Models for Freight Trip Generation by Vehicle Type: Application to the Chennai Metropolitan Area in India

During the last two decades, there has been substantial interest in developing freight trip generation (FTG) models. Most studies consider only truck trips or convert all freight trips into equivalent truck trips. Freight in several large cities is increasingly being moved by smaller vehicles. This calls for modeling FTG by vehicle type. The present research identifies and compares establishment characteristics affecting FTG by different vehicle types. In this context, spatial correlations among nearby establishments and the error-term correlations between independent models by vehicle type become relevant. Based on the Lagrange-Multiplier (LM) tests, we develop non-spatial seemingly unrelated regression (SUR) models for freight trip production (FTP) and spatial SUR models with a spatial lag in the dependent variable to account for both spatial and error-term correlations for freight trip attraction (FTA). The results show that establishment type and size affect FTG by different vehicle types.

Clinical Profile and Types of Youth-Onset Diabetes in Chennai

Background: The first national-level multicentric clinic-based registry of youth-onset diabetes from India was started in the year 2006 by the Indian Council of Medical Research (ICMR). Objective: In this study, we present the data collected from one of the Regional Collaborating Centre, Chennai (RCC03) of the ICMR Young Diabetes Registry (YDR). Materials and Methods: YDR recruited young diabetes participants reporting on/after January 1, 2000, with age onset ≤25 years at the time of diagnosis of diabetes, and residing within the Chennai Metropolitan Area. The reporting centers (RCs) that were willing to participate in the registry were included, and their staff was trained to fill-in the baseline and follow-up proforma. Results: Overall, 29 RCs participated, which includes six government hospitals, and remaining are private speciality hospitals or single-physician clinics. So far, RCC03 had contributed 4194 young diabetes participants to ICMR-YDR from the Chennai region. Among the registered 48.1% (n = 2020) were type 1 diabetes mellitus (T1DM), 43.4% (n = 1821) were type 2 diabetes mellitus (T2DM), 6.4% (n = 269) were gestational diabetes mellitus, and remaining 2.0% (n = 84) had secondary diabetes. Among T1DM, 58% of them had age onset of <15 years, whereas in T2DM, 95% of them had age onset <15 years. Differences in their clinical profiles were seen among these participants. All T1DMs were on insulin treatment at the time of registration or they had been prescribed insulin at their first visit to the RCs, and 12% of the T2DMs were on insulin. Conclusions: The observations from RCC03 of the registry reveal that 48.1% were T1DM and 43.4% were T2DM. These results suggest that there is equal contribution of T1DM and T2DM cases in the Chennai region, which needs to be studied in detail.

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Tick borne diseases and their complications in dogs are increasing over the years. Periodical assessments helps in planning to handle such health care burdens. Medical records of the clinical cases presented to the Small Animal Medicine Referral Clinics and Emergency Critical Care Medicine Referral Clinic of Madras Veterinary College, Chennai, were analyzed. Among the TBD cases of 268 identified in this study, 120 cases were ehrlichiosis affected dogs (44.77%) and remained one among the highly prevalent disease in Chennai Metropolitan Area. 66 cases (24.62%) were found to be affected by Babesia canis and 59 cases (22.01%) were found to be affected by Babesia gibsoni. Together babesiois affected dogs were 46.63%, which is little higher than the E.canis affections. 23 dogs (8.58%) were found to be affected with H.canis. Incidence of TBD, status of anemia, thrombocytopenia and pancytopenia due to E.canis were evaluated in this study.

Investigation of Role of Retention Storage in Tanks (Small Water Bodies) on Future Urban Flooding: A Case Study of Chennai City, India

The Adyar River flowing through Chennai Metropolitan Area (CMA) in Southern India functions as a surplus course of upstream water bodies that are locally known as tanks. During northeast monsoons, the river frequently floods the adjoining city areas. In this study, the impact of dredging and disappearance of tanks on flooding in CMA is analyzed under historical, urbanization, and extreme rainfall scenarios utilizing an urbanization-hydrologic-hydraulic modelling framework. The simulated scenarios highlight the importance of the tanks as a flood control measure for CMA. The major conclusions are (a) dredging the tanks uniformly by 2 m can compensate the increase in flooding due to urbanization by 2050 for 1 in 50-year rainfalls and, (b) for disappearance of tanks, 1 in 50-year rainfall can inundate the city akin to 1 in 100-year rainfalls. The study can be useful for making informed decisions on dredging the tanks, land use planning, and flood control measures for the CMA.

Metropolitan and Peri-Urban Governance in India: Case Study of Chennai Metropolitan Area

The rapid growth and economic importance of metropolitan cities is a known fact world over. These cities have increased in number over a period of time and have immense economic importance for their countries. They account for more than half of the world’s wealth. Moreover, some of the larger metropolitan cities in South Asia account for one-third and even more of the national GDP. The fast pace of growth of metropolitan cities and their peri-urban areas and the resulting spatial transformation is one of the most striking features of India’s urban scenario. In this context, planning and basic service provisions are the two components that warrant special attention in metropolitan regions for organised spatial, economic and social development. The present paper emphasises on the need for better service provision in peri-urban areas. It recommends a strategy to govern metropolitan regions so that the peri-urban areas can also get equitable treatment in the development process.

Association of Tuberculosis With Household Catastrophic Expenditure in South India

The high household costs associated with tuberculosis (TB) diagnosis and treatment can create barriers to access and adherence, highlighting the urgency of achieving the World Health Organization's End TB Strategy target that no TB-affected households should face catastrophic costs by 2020. To estimate the occurrence of catastrophic costs associated with TB diagnosis and treatment and to identify socioeconomic indicators associated with catastrophic costs in a setting where TB control strategies have been implemented effectively. In this cross-sectional study, 455 patients with TB in the Chennai metropolitan area of South India who were treated under the TB control program between February 2017 and March 2018 were interviewed. Patients were interviewed by trained field investigators at 3 time points: at the initiation of treatment, at the end of the intensive phase of treatment, and at the end of the continuation phase of treatment. A precoded interview schedule was used to collect information on demographic, socioeconomic, and clinical characteristics and direct medical, direct nonmedical, and indirect costs. Data analysis was performed from August 2018 to November 2019. Direct, indirect, and total costs to patients with TB. Catastrophic costs associated with TB were defined as costs exceeding 20% of the household's annual income. A binary response model was used to determine the factors that were significantly associated with catastrophic costs. Of 455 patients with TB interviewed, 205 (53%) were aged 19 to 45 years (mean [SD] age, 38.4 [16.0] years), 128 (33%) were female, 72 (19%) were illiterate, 126 (33%) were employed, and 186 (48%) had a single earning member in the family (percentages are based on the 384 patients who were interviewed through the end of the continuation phase of treatment). Sixty-one percent of patients (234 patients) had pulmonary smear positive TB. The proportion of patients with catastrophic costs was 31%. Indirect costs contributed more toward catastrophic cost than did direct costs. Multivariate logistic regression analysis found that unemployment (adjusted odds ratio, 0.2; 95% CI, 0.1-0.5; P < .001) and higher annual household income (Rs 1-200 000, adjusted odds ratio, 0.4; 95% CI, 0.2-0.7; P = .004; Rs >200 000, adjusted odds ratio, 0.2; 95% CI, 0.1-0.5; P < .001) were associated with a decreased likelihood of experiencing catastrophic costs. Despite the implementation of free diagnostic and treatment services under a national TB control program, TB-affected households had a high risk of catastrophic costs and further impoverishment. There is an urgent demand to provide additional financial protection for patients with TB.

Marketing of Women Self Help Groups Products (with Special Reference to Chennai City)

Empowerment implies equal conditions to girls. It supplies more significant access to know-how as well as sources, greater liberty in decision making, higher potential to consider their lifestyles and flexibility from the irons troubled all of them through personalized, view and also technique becoming conscious of their own condition and setting, setting their personal schedules, developing area on their own, obtaining skill-sets, developing positive self-image, addressing problems, and developing self-reliance. It is actually certainly not merely a social as well as a political method, yet a personal one too - as well as it is not simply a procedure however a result too. Empowerment of girls creates them much more powerful to encounter the challenges of lifestyle, to beat the disabilities, handicaps, and inequalities. It makes it possible for ladies to discover their total identification and powers in all realms of life. The study is actually generally concentrated on the efficiency of SWOT aspects on the total assessment of Women Self Help Groups product in Chennai Metropolitan area

Monitoring spatio-temporal dynamics of urban and peri-urban land transitions using ensemble of remote sensing spectral indices-a case study of Chennai Metropolitan Area, India.

Land-use/land-cover change is the most vulnerable factor in any developing urban environment. Increased infrastructure and population density tend to alter the land features which in turn will have an impact on climate change and will increase the impervious layer. Study of trends in land-use/land-cover change is required for analyzing the possible ways of managing the natural system. In this study, the spatial and temporal changes of the urban and peri-urban landscape of the Chennai Metropolitan Area (CMA), Tamil Nadu, India, were analyzed using satellite images. Imageries from Landsat 5 (TM) and Landsat 8 (OLI/TIRS) sensors were taken for the years 1988, 1997, 2006, and 2017. Ensembles of remote sensing spectral indices (NDVI, MNDWI, NDBI, and NDBaI) were calculated for the land-use/land-cover classification. The confusion matrix was used for assessing the accuracy for the year 2017. The overall accuracy of the LULC classification obtained was 91.76% with the kappa coefficient of 0.84. The results show that during the period of February 1988 to February 2017, the agriculture/fallow land, barren/semi-barren, vegetation, and water bodies/wetlands have decreased by 53.62%, 1.45%, 58.99%, and 30.59%, respectively. This decrease has contributed to an increase of 173.83% in built-up area. About 26,881ha of agriculture/fallow land, 10,482ha of vegetation land, and 2454ha of water bodies/wetlands were converted to built-up and other land-use over the period. This essentially meant that CMA has changed from predominantly an agricultural area (42.21%) in 1988 to built-up area (48.72%) in 2017.

Analysis and Prediction of Urban Growth Using Neural-Network-Coupled Agent-Based Cellular Automata Model for Chennai Metropolitan Area, Tamil Nadu, India

Chennai is one of the most densely populated cities in India facing challenges in shifting the city to metropolitan or mega city in the last two decades with continuing agglomeration. To model the growth of Chennai city, we have used cellular automata-based urban growth models based on the historical datasets. In the present study, urban growth of Chennai Metropolitan Area (CMA) was predicted for the year 2017 based on 2010 and 2013 dataset and Chennai city master plan using neural-network-coupled agent-based cellular automata (NNACA) model. Eight different agents of urbanization including transportation, hotspots, and industries were used in the prediction modeling. On validating the 2017 predicted outputs, NNACA model with hotspots proved to be better (hits: 498.52 km2) than that of without hotspots (hits: 488.31 km2). Out of the total eight agents of urbanization, the most influencing agent of urbanization of 2017 was identified to be the neighborhood of ‘Existing built-up of 2013’ using ‘sensitivity analysis’. Further, the urban sprawl of CMA for 2010, 2013 and 2017 was measured through Shannon’s entropy. The study area was divided into five directional and distance-based zones with the State Secretariat as the center. Entropy values suggest the need for more careful planning for further development in the southern region of CMA which has undergone congested urban growth while urbanization is dispersed in the northern part of the study region which can be thought for future urban developments.

Comparison of Urban Growth Modeling Using Deep Belief and Neural Network Based Cellular Automata Model—A Case Study of Chennai Metropolitan Area, Tamil Nadu, India

Urban Growth Models (UGMs) are very essential for a sustainable development of a city as they predict the future urbanization based on the present scenario. Neural Network based Cellular Automata models have proved to predict the urban growth more close to reality. Recently, deep learning based techniques are being used for the prediction of urban growth. In this current study, urban growth of Chennai Metropolitan Area (CMA) of 2017 was predicted using Neural Network based Cellular Automata (NN-CA) model and Deep belief based Cellular Automata (DB-CA) model using 2010 and 2013 urban maps. Since the study area experienced congested type of urban growth, “Existing Built-Up” of 2013 alone was used as the agent of urbanization to predict urban growth in 2017. Upon validating, DB-CA model proved to be the better model, as it predicted 524.14 km2 of the study area as urban with higher accuracy (kappa co-efficient: 0.73) when compared to NN-CA model which predicted only 502.42 km2 as urban (kappa co-efficient: 0.71), while the observed urban cover of CMA in 2017 was 572.11 km2. This study also aimed at analyzing the effects of different types of neighbourhood configurations (Rectangular: 3 × 3, 5 × 5, 7 × 7 and Circular: 3 × 3) on the prediction output based on DB-CA model. To understand the direction and type of the urban growth, the study area was divided into five distance based zones with the State Secretariat as the center and entropy values were calculated for the zones. Results reveal that Chennai Corporation and its periphery experience congested urbanization whereas areas away from the Corporation boundary follow dispersed type of urban growth in 2017.

Sub-Surface Investigation Using Vertical Electrical Sounding: Chennai Metropolitan Area

The data or information on the sub-stratum, nature of aquifers, their spatial disposition, their hydrogeological characteristics and other information, are limited particularly in urban context. The study was performed in the Chennai metropolitan area. The objective of the study was to get the sub-surface information of the study area. The vertical electrical sounding was performed at ninety locations to identify the sub surface lithology. The Archaeans consisting of Charnockites, gneisses and dolerite occupy the southern part of the Metropolitan area. The lower portion of gondwanas belonging to the Talchir beds consist of light brown and green colored Shales occurring below the alluvium in the area between Nandanam on the east to Nandambakkam on the west. These Shales are overlying the older crystalline rocks. The lower portion of gondwanas belonging to the Talchir beds consist of light brown and green coloured Shales occurring below the alluvium in the area between Nandanam on the east to Nandambakkam on the west The Tertiary bed comprising friable white and reddish brown Sandstone occurs on the western side near Chembarambakkam and on the northwestern side between Thirunindravur and Villiwakkam. The thickness of the alluvium ranges between 5m on the southern side to a little more than 20m on the east central part of the Metropolitan area.