Urban Observation and Social Sensing
1st Edition
Will be published approx. on 6. August 2026
Book
Hardback
172 pages
978-1-032-77653-8 (ISBN)
Description
Urban Observation and Social Sensing helps readers see cities in a way they have seldom imagined before. Advanced technologies such as satellites in space, near surface drones, or even smartphones, can be used to explain how a city functions, or why certain areas are more populated than others. It examines the science of capturing city images and information gathered from above the ground combined with the information from social media and mobile data on the ground, and how to make sense of it all. From planning better neighborhoods to understanding how city life affects health, this book is a guide to the future of urban living and the technologies that help navigate it.
Features
Covers a broad spectrum of urban observation methods in one resource to ensure a thorough understanding of diverse data collection methods.
Provides a unique emphasis on social sensing to enable a more holistic and human-centric view of urban landscapes.
Includes practical applications to showcase how the data and methodologies can be used in real-world scenarios.
Explains the current technologies and methodologies but also offers insights into the future trajectory of urban science.
Integrates technological advances with informed urban planning and real-time insights to elucidate a holistic understanding of urban spaces.
This is an excellent, insightful resource for researchers, academics, students, and professionals in remote sensing, Geographic Information Systems, urban planning and design, data science, geography, earth science, and those interested in the future of urban living and planning.
Features
Covers a broad spectrum of urban observation methods in one resource to ensure a thorough understanding of diverse data collection methods.
Provides a unique emphasis on social sensing to enable a more holistic and human-centric view of urban landscapes.
Includes practical applications to showcase how the data and methodologies can be used in real-world scenarios.
Explains the current technologies and methodologies but also offers insights into the future trajectory of urban science.
Integrates technological advances with informed urban planning and real-time insights to elucidate a holistic understanding of urban spaces.
This is an excellent, insightful resource for researchers, academics, students, and professionals in remote sensing, Geographic Information Systems, urban planning and design, data science, geography, earth science, and those interested in the future of urban living and planning.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Postgraduate, Professional Reference, and Undergraduate Advanced
Illustrations
17 s/w Tabellen, 10 farbige Zeichnungen, 8 s/w Zeichnungen, 20 Farbfotos bzw. farbige Rasterbilder, 5 s/w Photographien bzw. Rasterbilder, 30 farbige Abbildungen, 13 s/w Abbildungen
17 Tables, black and white; 10 Line drawings, color; 8 Line drawings, black and white; 20 Halftones, color; 5 Halftones, black and white; 30 Illustrations, color; 13 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Weight
453 gr
ISBN-13
978-1-032-77653-8 (9781032776538)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Bin Chen | Fan Zhang
Urban Observation and Social Sensing
E-Book
approx. 08/2026
CRC Press
€115.99
Not yet available
Bin Chen | Fan Zhang
Urban Observation and Social Sensing
E-Book
approx. 08/2026
CRC Press
€115.99
Not yet available
Persons
Dr. Bin Chen is an Associate Professor, Director of Future Urbanity & Sustainable Environment (FUSE) Lab at The University of Hong Kong. He obtained his BSc in Geographical Information Systems from Wuhan University, and his PhD in Global Environmental Change from Beijing Normal University. Before joining the University of Hong Kong in 2021, he worked as a postdoctoral researcher at the University of California, Davis.
Dr. Chen's research leverages geospatial big data, data-model fusion, and advanced interdisciplinary approaches to investigate the interaction loops between environmental change, human activities, and public health. Specifically, his major research includes the remote sensing of built and natural environmental changes; modelling of human-environment spatiotemporal interaction; and impact of environment and human activities on public health. He has published over 80 refereed publications in top academic journals. His achievements have received international recognition, including Geospatial World 50 Rising Stars (2024) and receiving the International Society of Digital Earth Young Scientist Award, American Association of Geographers Early Career Award in Remote Sensing, and HKU-100 Scholars Award and Outstanding Young Researcher Award.
Dr. Fan Zhang is an Assistant Professor at the Institute of Remote Sensing and GIS, Peking University. Prior to this, he was a Senior Research Fellow at MIT, where he led the Urban Visual AI group at the MIT Senseable City Lab. His research focuses on geographical artificial intelligence and data-driven urban studies, with particular emphasis on developing urban visual intelligence using street-level imagery. Dr. Zhang's work has been published in renowned academic journals, and he currently serves as an Associate Editor and Editorial Board Member for various journals. He currently serves as an Associate Editor, an Editorial Board Member. His notable honors include the CPGIS Young Scholar Award (2024), the Geospatial World 50 Rising Stars Award (2022), and the Global Young Scientist Award in Frontier Science and Technology from WGDC (2020).
Dr. Chen's research leverages geospatial big data, data-model fusion, and advanced interdisciplinary approaches to investigate the interaction loops between environmental change, human activities, and public health. Specifically, his major research includes the remote sensing of built and natural environmental changes; modelling of human-environment spatiotemporal interaction; and impact of environment and human activities on public health. He has published over 80 refereed publications in top academic journals. His achievements have received international recognition, including Geospatial World 50 Rising Stars (2024) and receiving the International Society of Digital Earth Young Scientist Award, American Association of Geographers Early Career Award in Remote Sensing, and HKU-100 Scholars Award and Outstanding Young Researcher Award.
Dr. Fan Zhang is an Assistant Professor at the Institute of Remote Sensing and GIS, Peking University. Prior to this, he was a Senior Research Fellow at MIT, where he led the Urban Visual AI group at the MIT Senseable City Lab. His research focuses on geographical artificial intelligence and data-driven urban studies, with particular emphasis on developing urban visual intelligence using street-level imagery. Dr. Zhang's work has been published in renowned academic journals, and he currently serves as an Associate Editor and Editorial Board Member for various journals. He currently serves as an Associate Editor, an Editorial Board Member. His notable honors include the CPGIS Young Scholar Award (2024), the Geospatial World 50 Rising Stars Award (2022), and the Global Young Scientist Award in Frontier Science and Technology from WGDC (2020).
Content
1. Multispectral Remote Sensing in Urban Environments. 2. Advances in Nighttime Light Remote Sensing for Urban Observation. 3. Complex Linear Attention Network for Urban Land Cover Mapping from PolSAR Data. 4. Towards 3D Forest Structure Analysis: LiDAR Techniques Advancing Urban Forest Ecosystems. 5. Advanced Applications of Nano-Satellite Constellation in Urban Environmental Monitoring. 6. The Transformative Role of Social Media Data in Urban Studies. 7. Geospatial Optimization Coupling Spatiotemporal Big Data and Deep Reinforcement Learning. 8. Understanding Cities through the Lens of Spatial Navigation. 9. Towards the Science of Living Structure: Making and Remaking Liveble Cities as part of Urban Informatics. 10. Localised Sensor-Enhanced Assessment of Indoor Heat Exposure in Low-Income Housing in Global South.