Geography - Research Publications

Permanent URI for this collectionhttps://kr.cup.edu.in/handle/32116/93

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Author: search.filters.author.Singh, Kiran Kumari

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    Assessment of groundwater potential modeling using support vector machine optimization based on Bayesian multi-objective hyperparameter algorithm
    (Elsevier Ltd, 2022-11-25T00:00:00) Anh, Duong Tran; Pandey, Manish; Mishra, Varun Narayan; Singh, Kiran Kumari; Ahmadi, Kourosh; Janizadeh, Saeid; Tran, Thanh Thai; Linh, Nguyen Thi Thuy; Dang, Nguyen Mai
    Today, water supply in order to achieve sustainable development goals is one of the most important concerns and challenges in most countries. For this reason, accurate identification of areas with groundwater potential is one of the important tools in the protection, management and exploitation of water resources. Accordingly, the present study was conducted with the aim of modeling and predicting groundwater potential in Markazi province, Iran using Multivariate adaptive regression spline (MARS) and Support vector machine (SVM) machine learning models and using two random search (RS) and Bayesian optimization hyperparameter algorithms to optimize the parameters of the SVM model. For this purpose, 18 variables affecting the groundwater potential and 3482 spring locations were used to model the groundwater potential. Data for modeling were divided into two categories of training (70%) and validation (30%). The receiver operating characteristics (ROC) were used to evaluate the performance of the models. The results of evaluation models showed that using hyperparameters random search and Bayesian optimization were improved SVM accuracy in training and validation stages. Bayesian optimization methods are very efficient because they are consciously choosing the parameters of the model that this strategy improves the performance of the model. Evaluating accuracy in the validation stage showed that the AUC value is for MARS, SVM, RS-SVM and B-SVM models 87.40%, 88.25%, 90.73% and 91.73%, respectively. The results of assessment variables importance showed elevation, precipitation in the coldest month, soil and slope variables have the most importance in modeling groundwater potential, while aspect, profile curvature and TWI variables, have the least importance in predicting groundwater potential in Markazi province. � 2022 Elsevier B.V.
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    Spatiotemporal dynamics of urban green and blue spaces using geospatial techniques in Chandannagar city, India
    (Springer Science and Business Media Deutschland GmbH, 2021-10-12T00:00:00) Ghosh, Pritha; Singh, Kiran Kumari
    Green and blue spaces are important landscape elements in a city and there is strong literary evidence available regarding the ecological, social, cultural and recreational benefits of these spaces to people and urban sustainability. Comprehensive quantitative assessment of these spaces is gaining scientific recognition for their utility in sustainable urban planning and drafting greening policies. This study analyzed the spatiotemporal change in urban green and blue spaces in Chandannagar city, India through quantitative assessment for the years 1991, 2001, 2011, and 2020 using Landsat data of 30�m spatial resolution. Normalized Difference Vegetation Index and Normalised Difference Water Index was applied to extract information on urban green and blue spaces. The classified maps were validated through field observations and Google earth images. Spatio-temporal analysis was carried out at ward level to analyze the distribution of urban green spaces (UGS) at the micro level. The result indicated that there was a reduction in green and blue spaces in the central and eastern parts of the city while there was a good amount of UGS in the western part of the city. The findings of this study shed light on important policy implications for the UGS planning in the city. � 2021, The Author(s), under exclusive licence to Springer Nature B.V.
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    Green, open spaces and transport for healthy and sustainable cities in asian developing countries
    (Universiti Putra Malaysia Press, 2021-07-31T00:00:00) Singh, Kiran Kumari; Katewongsa, Piyawat; Wijaya, Nurrohman; Kwan, Soo Chen
    Introduction: This paper presents the case studies of the green, open spaces and transport issues in three cities of the Asian region based on the work of participants from the Workshop of Health in Urban Planning. Methods: Three case studies were collected from the participants of Thailand, India, and Indonesia, and compiled under the theme. Results: The first case study presents findings from the Thailand's Survey on Physical Activity (SPA), and various strategies taken by the Thai government to improve physical activity levels among the Thai population and children, including improved accessibility, walkability; and reconstruction of school curricula. The second case study is an empirical study of the geographical extent and type of green spaces accessible to the urban population, and their usage in the city of Varanasi, India, in the wake of Yoga practice popularity. The third case study discusses the insufficient transport infrastructures, along with the influx of visitors from outside the city as the cause of severe traffic congestions and emissions in Bandung city, Indonesia. The governments' action plans and recommendations for improvements of the city environment are discussed. Conclusion: Integrating health into urban and transport planning needs co-operations from multiple stakeholders including the government, private sectors, and the communities, especially from the early phase of development. � 2021 UPM Press. All rights reserved.
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    Geospatial analysis of the distribution of urban green spaces: a study of four Indian cities
    (Routledge, 2021-07-27T00:00:00) Kaur, Navjotpreet; Kaur, Mandeep; Padhi, Saumya Sibani; Singh, Kiran Kumari
    The urban green spaces are immensely significant to ensure quality of life in a city. However, their spatial distribution is found to be inequitable. The study investigates spatial distribution of green space through remote sensing data at different times in four Indian cities. It further examines the distribution of urban parks with respect to the location of slums. The results demonstrate that green spaces in the study areas changed considerably in the last two decades. The public urban parks are far from slum areas, and their spatial distribution is inequitable. Urban green spaces should be considered a matter of environment justice. � 2021 Informa UK Limited, trading as Taylor & Francis Group.