Guoqing Zhou - Urban High-Resolution Remote Sensing: Algorithms and Modeling

With increasing interest in and requests for applications of remote sensing in urban areas, the development of urban remote sensing algorithms and methodologies driven by applications from different fields has become imperative. In addition to the traditional fields of application such as land use and cover and environmental pollution monitoring, remote sensing has been widely applied in other fields such as micro-climate analysis, cell phone planning, and socioeconomic analysis.

The objective of this book is to provide readers with algorithms and methods with an emphasis on urban three-dimensional modeling, urban orthophotomap generation, and urban feature extraction from high-resolution urban remotely sensed imagery. On the other hand, it has been observed that none of the eight published books relevant to urban remote sensing has specially presented algorithms and methods relevant to urban 3D modeling, orthophotomap generation, and feature extractions. Therefore, another objective of this book is to compensate for the gap.

When we talk about urban remote sensing, we should NOT forget its roots. In the early nineteenth century, balloon-based aerial photography was applied in city monitoring and observations. Since that era, three major tasks in urban remote sensing are urban digital surface model (DSM) creation, including digital terrain models (DTM), orthophotomap generation, and feature extractions. The book therefore presents novel developments of methods and algorithms surrounding this root through dealing with various data resources, such as UAV-based aerial image video, LiDAR (light detection and ranging) data, high-resolution satellite imagery, and so on. Readers should be very interested in many novel algorithms and methods, such as high building orthorectification with self-constraints, deep learning neural networks for urban classification, co-location decision trees for urban classification. The arrangement of the book is below:

• is an introduction to urban remote sensing fundamentals.

• emphasizes the algorithms and methods of urban feature extractions, including DSM extraction, power line extraction, tree extraction, and car/vehicle extraction on the freeway using advanced methods such as co-location decision trees, and deep learning neural networks.

• focuses on the algorithms and methods for urban orthophotomap generation, especially urban true orthorectification.

• presents novel algorithms and methods for case applications, including soil surface moisture (SSM) retrieval and asphalt road aging monitoring.

I believe several features of the book will enhance its value as a textbook or reference book. First, the algorithms and methods described in this book are almost all for high-resolution imagery, that is, the ground sampling distance (GSD) is less than 1.0 meter. Second, the algorithms and methods presented in this book focus on the three traditional urban remote sensing products, namely, the 3D urban model, orthophotomap, and feature extraction. Third, both linear and sporadic reading are appropriate, in that sporadic readers can completely understand the essence of any chapter without needing to read all the previous chapters. Readers may therefore read the chapters relevant to his/her background. However, the chapters have a logical order, which is given above especially for various interested readers.