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        Chapter GeoAI for High-Resolution Urban Air Temperature Estimation and Urban Heat Island Monitoring

        IN Book: Handbook of Geospatial Approaches to Sustainable Cities

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        Author(s)
        orcid
        Contributor(s)
        (editor) orcid
        Language
        English
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        Abstract
        This comprehensive handbook presents the current state of knowledge on geospatial technologies, techniques, and methods that are imperative for providing solutions to sustainable cities. It addresses the role of geospatial big data and AI techniques and how they are applied when analyzing the sustainability of urban development, land use, urban planning, and resource management, as well as monitoring the impact urbanization has on the environment and the ecosystem. Taking an interdisciplinary approach to sustainable cities, and with contributions from renowned experts around the world, this holistic handbook is a toolbox for geospatial, urban, and sustainability professionals, the artificial intelligence community, and those who work in related fields. Features: Explores cutting-edge geospatial and AI techniques in support of efficient, resilient, digital, and smart cities Bridges urban science and sustainability science via geospatial methods Contributes to the efforts of GEO by addressing and exemplifying pertinent societal benefit areas and engagement priorities Includes 16 case studies with a broad geographic scope that integrate societal needs with technological advances Draws expertise in geospatial technology, big data, and artificial intelligence from leading experts in the world This book is intended for researchers and scientists interested in learning techniques in GeoAI, including the technologies for collecting, analyzing, managing, processing, and visualizing geospatial datasets. Chapters 3, 6, 7, 8, and 15 of this book are freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.
        URI
        https://oapen-dev.siscern.org/handle/20.500.12657/108901
        Keywords
        Urban climate modelling; Nature-based solutions; Land use change analysis; Agent-based simulation; Environmental monitoring techniques; Urban air pollution control; Machine learning for urban sustainability
        DOI
        10.1201/9781003244561-11
        ISBN
        9781003244561, 9781003244561, 9781032154817, 9781032155340
        Publisher
        Taylor & Francis
        Publisher website
        https://taylorandfrancis.com/
        Publication date and place
        Boca Raton, 2024
        Imprint
        CRC Press
        Series
        Imaging Science,
        Classification
        City and town planning: architectural aspects
        Environmental science, engineering and technology
        Geographical information systems, geodata and remote sensing
        Pages
        139 - 158
        Rights
        https://creativecommons.org/licenses/by-nc-nd/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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