Yong Xu Yong Xu is an Associate Professor in the School of Geography and Remote Sensing, Guangzhou University, China. He specializes in remote sensing and spatial analysis applied in the urban environment. He is the author or a coauthor for over 20 referred journal articles and three patents. He was a winner for the International Data Fusion Contest Award sponsored by the IEEE Geoscience and Remote Sensing Society in 2017.
Jinxin Yang Jinxin Yang is a Lecturer in the School of Geography and Remote Sensing at the Guangzhou University, Guangzhou, China. She received her PhD from the Hong Kong Polytechnic University in 2017. Her research interest centers on thermal remote sensing, surface energy balance, and urban climate. She authored or coauthored over 10 articles.
Kai‐Ling Yang Kai‐Ling Yang is an undergraduate student in the Department of Geography at the National Taiwan University, Taiwan. Her research interests include spatial data analysis, environmental remote sensing, and geolocated data clustering. She achieved the College Student Research Scholarship, and her current research study is to establish a modeling framework to capture and analyze the spatial patterns of geotagged photos on Instagram.
Xiaojun Yang Xiaojun Yang, Editor of this volume, is a Professor of Geography in the College of Social Sciences and Public Policy at the Florida State University, USA. His research interests center on the development of remote sensing and geospatial information technologies with applications in the urban and environmental domains. He has authored or coauthored more than 100 publications including eight books with John Wiley & Sons, Taylor & Francis, and Springer.
Dameng Yin Dameng Yin is an Assistant Professor at Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, China. Her research focus is on remote sensing, more specifically on the remote sensing of forests and agriculture. She has authored 15 papers, including an award‐winning “highly cited paper” on individual mangrove delineation using UAV LiDAR.
Junjun Yin Junjun Yin is an Assistant Research Professor at the Social Science Research Institute and Population Research Institute, and an ICDS Associate at the Institute for Computational and Data Sciences, Pennsylvania State University, USA. His research interests center on GIScience with a specific focus on understanding population dynamics in the urban environment. His main research agenda employs computational geography approaches and geospatial Big Data to model human–urban environment interactions concerning urban mobility, accessibility, and sustainability.
Yihong Yuan Yihong Yuan received her PhD in Geography and M.A. in Statistics from the University of California, Santa Barbara, and her B.S. in Geographic Information Systems from Peking University, China. She is currently an Associate Professor of Geography at the Texas State University. Her research focuses on big geo‐data analytics and spatial‐temporal knowledge discovery. She has an extensive background in analyzing the roles of communication technologies in reshaping today’s connected society. Dr. Yuan has led and participated in several projects on human mobility modeling funded by national and international agencies, such as the U.S. Department of Transportation and the Swiss National Science Foundation.
Naizhuo Zhao Naizhuo Zhao is a Research Associate in the Department of Medicine at the McGill University, Canada. His research lies in understanding human–environment interactions using remote sensing and social sensing. He has published 50 peer‐reviewed journal papers. He received a PhD in Geography from the Texas State University, San Marcos. Before joining McGill University, he worked as a Postdoctoral Research Associate at the Texas Tech University.
Fan Zhang Fan Zhang is a Postdoctoral Researcher at the Massachusetts Institute of Technology, USA. He received his PhD and M.S. in Geo‐Information Science at the Chinese University of Hong Kong, and a B.S. in Electronic Information Science at Beijing Normal University, Zhuhai. His research interests include spatiotemporal urban data mining, computer vision, and social sensing. He is the author of over 30 peer‐reviewed journal and conference papers.
Preface
The first edition of Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment published in 2011was primarily an outcome of my decade‐long efforts promoting urban remote sensing research through organizing thematic paper sessions at the annual meetings of the American Association of Geographers (AAG). It is the first book written with a broad vision of urban remote sensing that draws upon multiple disciplines and the integration of remote sensing with relevant geospatial data and technologies. The book covered a variety of topics extending beyond urban feature extraction and into socioeconomic and environmental analyses and predictive modeling of urbanization. It contrasts considerably in such a treatment with other dedicated books on urban remote sensing, which are largely restricted on urban feature extraction and land use interpretation. In addition, the book has been translated into Chinese and was published by China’s Higher Education Press in 2014.
Over the past decade, we have witnessed evolving innovations in sensors, technologies, and theories in the broad arena of Earth Observation, which enable critical information to be developed through remote sensing in support of urban management activities and the scientific research on socio‐environmental dynamics and sustainability. Specifically, the availability of openly accessed satellite image archives since the late 2000s, coupled with the progression of high‐computing and cloud computing infrastructures, prompts the surge of multi‐temporal image analyses moving beyond fast‐paced change detection (such as land conversions) and into monitoring of continuous land use activities with slower change rates (such as land modifications). New or emergent platforms or systems, such as unmanned aerial systems and social sensing, provide spatial flexibility in urban mapping and new opportunities for understanding the changing urban environment. The advancement of artificial intelligence technology beyond shallow learning algorithms and into deep learning models helps discover the intricate structure in large remote sensor datasets, bringing about breakthroughs in image understanding over complex urban environments. Last, integrating remote sensing with relevant geospatial data and technologies supports innovative urban applications moving beyond observing spatiotemporal patterns and into analyzing socio‐environmental dynamics, and into pursuing toward urban sustainability.
The time is ripe for a new edition on urban remote sensing after one decade of publishing the first version. While continuing research on some critical issues identified in the earlier volume is also examined, this new edition focuses on a variety of essential and emerging research areas in urban remote sensing including sensors, techniques, and applications. The book is divided into five parts beginning with an introductory part discussing the rationale and motivation leading to the publication of the new volume. The second part examines advanced and emerging platforms or systems, such as unmanned aircraft systems and social sensing, which provide new opportunities for urban studies. The third part discusses some emerging remote sensing and machine learning techniques, such as deep learning and cloud computing infrastructures, for urban attribute extraction. The fourth part presents several innovative socioeconomic applications through remote sensing, such as urban slum mapping and urban conflict damage monitoring. The last part showcases some latest progress in the synergistic use of remote sensing and relevant geospatial techniques for urban environmental applications, which are related to such issues as man‐made carbon dioxide emissions, urban microclimate, air pollution, urban green infrastructure, and urban sustainability.
This book is the result of extensive research by interdisciplinary experts, and will appeal to students, researchers, and professionals dealing with not only remote sensing, geographic information systems, and geocomputation but also urban planning, geography, environmental science, global change science, and sustainability science. It is worth noting that the book project has spanned almost the entire period of the global coronavirus pandemic by now. The virus (COVID‐19) imposes tremendous impacts on our daily life challenging the project completion. I am very grateful