在全球城市化背景下，城市遥感技术在城市观测、监测、规划、建设和管理等方面发挥了重要作用。本书介绍了城市多源遥感大数据获取原理、城市遥感图像处理方法和城市遥感在相关行业的具体应用。具体内容涵盖城市遥感现状和发展趋势、城市遥感空天地多平台传感器的数据特性，重点包括城市遥感“时空谱角”观测模型、城市遥感图像解译原理和方法、城市遥感图像预处理和信息提取方法、基于深度学习模型的城市遥感图像处理方法、城市遥感变化检测和动态监测，以及城市生态环境遥感监测技术与实践。
本书内容包括遥感基础知识和城市遥感当前研究方向，可以作为高等院校遥感、测绘、地理信息及相关专业本科生和研究生教材，也可供城市遥感领域的科学工作者参考。

1 Urban Spatio-Temporal-Spectral-Angular
Observation Model
Urban Remote Sensing Observation Demand
The Observation Objects of Urban Remote Sensing
The Demand for Urban Application Services for Remote
Sensing Platform
The Demand for Sensor Diversity in Urban
Remote Sensing
Remote Sensing Platform for Various Urban Applications
Multi-platform Multi-sensor Collaborative Network Observation
Mode of Space-Air-Ground for Urban Service Demand
Theoretical Model of Urban Spatio-Temporal-Spectral-Angular
Observation
Urban Remote Sensing Observation Services
Questions
References
2 Big Data Characteristics of Urban Remote Sensing
Multi-source Heterogeneous Remote Sensing Big Data with
Long Time Series
Urban Satellite Imagery
Urban Aerial Imagery
Urban UAV Imagery
Urban Mobile Mapping System
Urban Crowdsourcing Images
Data Characteristics of Urban Visible Panchromatic Remote
Sensing Imagery
Image Characteristics of Urban Houses
Image Characteristics of Urban Roads
Image Characteristics of Urban Green Space
Image Characteristics of Urban Water Bodies
Data Characteristics of Urban Multi-spectral Remote
Sensing Images
Data Characteristics of Urban Green Space
Data Characteristics of Urban Water Bodies
Data Characteristics of Urban Hyperspectral Imagery
Data Characteristics of Urban Thermal Infrared Images
Data Characteristics of Urban Microwave Remote
Sensing Images
Data Characteristics of Urban LiDAR Data
Data Characteristics of Urban Nighttime Light Remote
Sensing Imagery
Data Characteristics of Urban Crowdsourcing Images
Questions
References
3 Principles and Methods of Urban Remote Sensing
Image Interpretation
The Task of Urban Remote Sensing Imagery Interpretation
The Objects of Urban Remote Sensing Imagery
Interpretation
Image Spatial Interpretation
Interpretation of Spectrum Space
Interpretation of Feature Space
The Mechanism of Urban Remote Sensing Imagery
Interpretation
Direct Interpretation Signs
Indirect Interpretation Signs
Methods of Urban Remote Sensing Imagery Interpretation
Visual Interpretation
Semi-automatic Interpretation
Automatic Interpretation Based on Machine Learning
Automatic Interpretation Based on Deep Learning
Interpretation of Remote Sensing Big Data
Questions
References
4 Preprocessing Methods of Urban Remote
Sensing Imagery
Cloud Detection Methods for Urban Remote
Sensing Imagery
Shadow Detection Methods for Urban Remote
Sensing Imagery
Image Enhancement Methods for Urban Remote
Sensing Imagery
Super-resolution Reconstruction Methods for
Urban Remote Sensing Imagery
Fusion Demands of Urban Remote Sensing Imagery
Spatial-Spectral Fusion Methods
Spatio-Temporal Fusion Methods
Questions
References
5 Classification and Information Extraction Methods for
Urban Remote Sensing Imagery
Classification and Information Extraction Demands for
Urban Remote Sensing Imagery
Unsupervised Classification Methods for Urban Remote
Sensing Imagery
Supervised Classification Methods for Urban Remote
Sensing Imagery
New Classification Methods for Urban Remote
Sensing Imagery
Urban Road Extraction Methods Based on Remote
Sensing Imagery
Automatic Extraction Method of Urban Roads
Road Rxtraction Method Based on Deep Learning Models
Urban Building Extraction Methods Based on
Remote Sensing Imagery
Urban Lakes Extraction Methods Based on
Remote Sensing Imagery
Questions
References
6 Urban 3D Reconstruction Methods Based on
Multi-source High-resolution Remote Sensing Imagery
Urban 3D Reconstruction Demands
Urban 3D Reconstruction Based on Stereo Image Pair
3D Reconstruction Based on Onboard LiDAR
3D Reconstruction Based on Mobile Mapping Systems
3D Reconstruction of Urban Ancient Buildings Based on
Ground LiDAR
Texture Reconstru