Artificial Intelligence Methods Applied To Urban Remote Sensing And Gis
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Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS
This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.
AI and Language in the Urban Context
In a world influenced increasingly by artificial intelligence (AI), the city emerges as a dynamic hub of digital conversations. AI and Language in the Urban Context offers a novel exploration of how AI, particularly large language models (LLMs), is transforming urban environments. Moving beyond the typical technological narratives, this book draws on the author’s unique expertise in design, semiotics and hermeneutics to present a critical cultural perspective on AI’s role in the city. Focusing on the intersection of urban theory and AI, the book reveals how conversational AI is reshaping social interactions, decision-making processes, and media in urban spaces. By merging practical knowledge of AI algorithms with an understanding of urban practices, the author highlights the opportunities and challenges AI presents for modern cities. This book is essential for anyone interested in the future of urban living. It provides a deep dive into the technical, social and cultural implications of AI in cities, offering practical examples and philosophical insights. Readers will gain a comprehensive understanding of how AI is influencing the design, governance and dynamics of urban life in the digital age. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
Urban High-Resolution Remote Sensing
With urbanization as a global phenomenon, there is a need for data and information about these terrains. Urban remote sensing techniques provide critical physical input and intelligence for preparing base maps, formulating planning proposals, and monitoring implementations. Likewise these methodologies help with understanding the biophysical properties, patterns, and process of urban landscapes, as well as mapping and monitoring urban land cover and spatial extent. Advanced sensor technologies and image processing methodologies such as deep learning, data mining, etc., facilitate the wide applications of remote sensing technology in urban areas. This book presents advanced image processing methods and algorithms focused on three very important roots of urban remote sensing: 3D urban modelling using different remotely sensed data, urban orthophotomap generation, and urban feature extraction, which are also today’s real challenges in high resolution remote sensing. Data generated by remote sensing, with its repetitive and synoptic viewing and multispectral capabilities, constitutes a powerful tool for mapping and monitoring emerging changes in the city's urban core, as well as in peripheral areas. Features: Provides advances in emerging methods and algorithms in image processing and technology Uses algorithms and methodologies for handling high-resolution imagery from a ground sampling distance (GSD) less than 1.0 meter Focuses on 3D urban modelling, orthorectification methodologies, and urban feature extraction algorithms from high-resolution remotely sensed imagery Demonstrates how to apply up-to-date techniques to the problems identified and how to analyze research results Presents methods and algorithms for monitoring, analyzing, and modeling urban growth, urban planning, and socio-economic developments In this book, readers are provided with valuable research studies and applications-oriented chapters in areas such as urban trees, soil moisture mapping, city transportation, urban remote sensing big data, etc.