Advances in Urban Environmental Research: Applications of Geospatial Technologies and Artificial Intelligence in Urban Studies (English)

Key Chapter Title List

1. Remote Sensing and Artificial Intelligence in Urban Environmental Research
2. Geospatial Technology and Artificial Intelligence in Urban Growth Modeling: A Systematic Review
3. Monitoring Using Machine Learning Algorithms and Cellular Automata Models on the Google Earth Engine Platform: A Case Study of Raiganj City, West Bengal, India
4. Land Use and Land Cover Change Modeling and Future Simulation of Mumbai City: Integration of Cellular Automata and Artificial Neural Networks
5. Monitoring Urban Sprawl Using Geospatial Technology: A Case Study of Kanpur City, India
6. Spatio-temporal Analysis of Urban Green and Blue Space Dynamics: A Case Study of Rajshahi City, Bangladesh
7. Quantifying the Impact of Urban Green Space Patterns on Land Surface Temperature: Evidence from Urban Agglomerations in Eastern India
8. A GIS and WUDAPT Tool-Based Approach for Mapping Urban Local Climate Zones: A Case Study of Kolkata
9. Identification of Urban Flood Hazard Zones: A Case Study of the Indian Capital
10. Assessment of Drinking Water Quality and Its Relationship with Land Use Using Remote Sensing and GIS: A Case Study of Azamgarh City, India
11. Urban Planning from the Perspective of UN Sustainable Development Goal 11: A Case Study of the Kolkata Metropolitan Area
12. An Introduction to Big Data and Its Applications in the Urban Context

Document Introduction

This book, "Advances in Urban Environmental Research 2023: Applications of Geospatial Technology and Artificial Intelligence in Urban Studies," as a volume in the "Geographic Information Science and Geo-environmental Modeling" series, systematically presents cutting-edge applications of remote sensing, geographic information systems, and artificial intelligence technologies in the field of urban environmental research. Comprising 28 peer-reviewed academic papers, the book revolves around four core themes: urban expansion, green and blue space dynamics, urban climate and disasters, and environmental planning and waste management. It aims to provide a scientific basis and methodological support for sustainable urban management through multi-scale and interdisciplinary perspectives.

The book is structured into four parts. Part One focuses on "Land Use, Land Cover, and Urban Expansion," systematically reviewing the application of geospatial technologies and artificial intelligence in urban growth modeling. Through multiple case studies (e.g., Mumbai, Raiganj, Kanpur in India; Khulna in Bangladesh, etc.), it demonstrates the practical application of machine learning algorithms, cellular automata models, and the Google Earth Engine platform in monitoring and simulating urban expansion. Part Two explores "Urban Green and Blue Spaces," analyzing the spatio-temporal dynamics of urban vegetation and water bodies and their ecosystem service functions. It covers topics such as landscape pattern metrics, land surface temperature effects, and wetland hydrological status assessment, emphasizing the critical role of urban ecological spaces in mitigating the heat island effect and maintaining biodiversity.

Part Three, "Urban Climate, Heat Islands, and Disasters," concentrates on the impacts of urbanization on local climate, thermal environment, and natural disaster risks. Case studies include mapping Local Climate Zones using the World Urban Database and Access Portal Tools (WUDAPT), analyzing the association between anthropogenic heat flux and urban heat islands, assessing the impact of urbanization on land surface temperature, and identifying urban flood risk zones using models like the Flood Hazard Index. These studies provide data support and decision-making tools for urban climate adaptation and resilience planning.

Part Four, "Urban Environmental Planning and Waste Management," addresses sustainable urban development strategies and practices. The content covers scenario analysis for solid waste management, integration of advanced technologies in waste management, geospatial assessment of walkability experience quality, the relationship between drinking water quality and land use, and case studies of urban planning based on UN Sustainable Development Goal 11. Furthermore, the book prospectively discusses the potential utility of big data in urban environmental research and offers systematic reflections on the research methods and technological advancements in this field.

This book compiles contributions from researchers in India, the United States, Bangladesh, Iran, and other countries. All chapters are based on multi-temporal remote sensing data, geospatial analysis, and machine learning algorithms, demonstrating the strong potential of interdisciplinary collaboration and technological integration in urban studies. It provides urban researchers, planners, policymakers, and environmental scientists with rich empirical analysis and methodological references, serving as a vital academic resource for understanding and addressing the environmental challenges posed by rapid urbanization.