Urban High-Resolution Remote Sensing : Algorithms and Modeling

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.

Guoqing Zhou received his first Ph.D. from Wuhan University, Wuhan, China, in 1994 and his second Ph.D. from Virginia Tech at Blacksburg, Virginia, USA in 2001. He was a Visiting Scholar at the Department of Computer Science and Technology, Tsinghua University, Beijing, China, and a Postdoctoral Researcher at the Institute of Information Science, Beijing Jiaotong University, Beijing, China from 1994-1996. He continued his research as an Alexander von Humboldt Fellow at Technical University of Berlin, Berlin, Germany from 1997-1998, and afterward became a Postdoctoral Researcher at the Ohio State University, Columbus, OH, USA from 1998 to 2000. Later he worked at Old Dominion University, Norfolk, VA, USA, as an Assistant Professor, Associate Professor, and Full Professor in 2000, 2005, and 2010, respectively. He is currently professor at the Guilin University of Technology, Guilin, China. He is author of 4 books and has published more than 300 papers in peer-reviewed journals and conference proceedings.