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Urban Remote Sensing


作者:
Zhenfeng Shao
定价:
129.00元
ISBN:
978-7-04-058585-8
版面字数:
290.000千字
开本:
16开
全书页数:
暂无
装帧形式:
平装
重点项目:
暂无
出版时间:
2022-07-06
读者对象:
学术著作
一级分类:
自然科学
二级分类:
地球科学
三级分类:
测绘科学技术

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
    • 1.1 Urban Remote Sensing Observation Demand
      • 1.1.1 The Observation Objects of Urban Remote Sensing
      • 1.1.2 The Demand for Urban Application Services for Remote Sensing Platform
      • 1.1.3 The Demand for Sensor Diversity in Urban Remote Sensing
      • 1.1.4 Remote Sensing Platform for Various Urban Applications
    • 1.2 Multi-platform Multi-sensor Collaborative Network Observation Mode of Space-Air-Ground for Urban Service Demand
    • 1.3 Theoretical Model of Urban Spatio-Temporal-Spectral-Angular Observation
    • 1.4 Urban Remote Sensing Observation Services
    • Questions
    • References
  • 2 Big Data Characteristics of Urban Remote Sensing
    • 2.1 Multi-source Heterogeneous Remote Sensing Big Data with Long Time Series
      • 2.1.1 Urban Satellite Imagery
      • 2.1.2 Urban Aerial Imagery
      • 2.1.3 Urban UAV Imagery
      • 2.1.4 Urban Mobile Mapping System
      • 2.1.5 Urban Crowdsourcing Images
    • 2.2 Data Characteristics of Urban Visible Panchromatic Remote Sensing Imagery
      • 2.2.1 Image Characteristics of Urban Houses
      • 2.2.2 Image Characteristics of Urban Roads
      • 2.2.3 Image Characteristics of Urban Green Space
      • 2.2.4 Image Characteristics of Urban Water Bodies
    • 2.3 Data Characteristics of Urban Multi-spectral Remote Sensing Images
      • 2.3.1 Data Characteristics of Urban Green Space
      • 2.3.2 Data Characteristics of Urban Water Bodies
    • 2.4 Data Characteristics of Urban Hyperspectral Imagery
    • 2.5 Data Characteristics of Urban Thermal Infrared Images
    • 2.6 Data Characteristics of Urban Microwave Remote Sensing Images
    • 2.7 Data Characteristics of Urban LiDAR Data
    • 2.8 Data Characteristics of Urban Nighttime Light Remote Sensing Imagery
    • 2.9 Data Characteristics of Urban Crowdsourcing Images
    • Questions
    • References
  • 3 Principles and Methods of Urban Remote Sensing Image Interpretation
    • 3.1 The Task of Urban Remote Sensing Imagery Interpretation
    • 3.2 The Objects of Urban Remote Sensing Imagery Interpretation
      • 3.2.1 Image Spatial Interpretation
      • 3.2.2 Interpretation of Spectrum Space
      • 3.2.3 Interpretation of Feature Space
    • 3.3 The Mechanism of Urban Remote Sensing Imagery Interpretation
      • 3.3.1 Direct Interpretation Signs
      • 3.3.2 Indirect Interpretation Signs
    • 3.4 Methods of Urban Remote Sensing Imagery Interpretation
      • 3.4.1 Visual Interpretation
      • 3.4.2 Semi-automatic Interpretation
      • 3.4.3 Automatic Interpretation Based on Machine Learning
      • 3.4.4 Automatic Interpretation Based on Deep Learning
      • 3.4.5 Interpretation of Remote Sensing Big Data
    • Questions
    • References
  • 4 Preprocessing Methods of Urban Remote Sensing Imagery
    • 4.1 Cloud Detection Methods for Urban Remote Sensing Imagery
    • 4.2 Shadow Detection Methods for Urban Remote Sensing Imagery
    • 4.3 Image Enhancement Methods for Urban Remote Sensing Imagery
    • 4.4 Super-resolution Reconstruction Methods for Urban Remote Sensing Imagery
    • 4.5 Fusion Demands of Urban Remote Sensing Imagery
      • 4.5.1 Spatial-Spectral Fusion Methods
      • 4.5.2 Spatio-Temporal Fusion Methods
    • Questions
    • References
  • 5 Classification and Information Extraction Methods for Urban Remote Sensing Imagery
    • 5.1 Classification and Information Extraction Demands for Urban Remote Sensing Imagery
    • 5.2 Unsupervised Classification Methods for Urban Remote Sensing Imagery
    • 5.3 Supervised Classification Methods for Urban Remote Sensing Imagery
    • 5.4 New Classification Methods for Urban Remote Sensing Imagery
    • 5.5 Urban Road Extraction Methods Based on Remote Sensing Imagery
      • 5.5.1 Automatic Extraction Method of Urban Roads
      • 5.5.2 Road Rxtraction Method Based on Deep Learning Models
    • 5.6 Urban Building Extraction Methods Based on Remote Sensing Imagery
    • 5.7 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
    • 6.1 Urban 3D Reconstruction Demands
    • 6.2 Urban 3D Reconstruction Based on Stereo Image Pair
    • 6.3 3D Reconstruction Based on Onboard LiDAR
    • 6.4 3D Reconstruction Based on Mobile Mapping Systems
    • 6.5 3D Reconstruction of Urban Ancient Buildings Based on Ground LiDAR
    • 6.6 Texture Reconstruction of Urban 3D Model
    • 6.7 Urban 3D Reconstruction Based on Street View Data
    • 6.8 3D Modeling Technology Based on Integrated Aerial-Ground Panoramic Imagery from Indoor and Outdoor
    • 6.9 Quality Control Strategy for 3D Reconstruction of the Urban Scene
    • 6.10 3D Reconstruction Management Platform of the Urban Scene
    • 6.11 The Planning and Construction Practice of Real Scene 3D in China
    • Questions
    • References
  • 7 Change Detection Methods and Applications of Urban Remote Sensing
    • 7.1 Change Detection Demands of Urban Remote Sensing
      • 7.1.1 Urban Construction Monitoring Demands
      • 7.1.2 Urban Management Monitoring Needs
    • 7.2 Change Detection Process of Urban Remote Sensing
    • 7.3 Change Detection Methods of Urban Remote Sensing
      • 7.3.1 2D Change Detection Methods
      • 7.3.2 3D Change Detection Methods
    • 7.4 Change Detection Practice of Urban Remote Sensing
      • 7.4.1 Urban Land Cover/Use Change Detection Methods
      • 7.4.2 Urban Impervious Surface Change Detection Methods
      • 7.4.3 Urban Cultivated Land Change Detection Methods
    • Questions
    • References
  • 8 Dynamic Monitoring Methods and Applications through Urban Remote Sensing
    • 8.1 Demands of Dynamic Urban Monitoring
    • 8.2 Urban Dynamic Monitoring Process
    • 8.3 Urban Dynamic Monitoring Methods
      • 8.3.1 Urban Dynamic Monitoring Based on Time-Series Remote Sensing Imagery
      • 8.3.2 Urban Dynamic Monitoring Based on the Integration of Earth Observation Sensor Network
    • 8.4 Remote Sensing Monitoring Applications of Urban Natural Resources
      • 8.4.1 Remote Sensing Monitoring of Urban Lake Changes
      • 8.4.2 Remote Sensing Monitoring of Urban Impervious Surface
      • 8.4.3 Remote Sensing Monitoring of Urban Cultivated Land
    • 8.5 Remote Sensing Monitoring of Urban Planning
    • 8.6 Remote Sensing Monitoring of Urban Conditions
      • 8.6.1 Difficulties of Remote Sensing Monitoring of Urban Situations
      • 8.6.2 Urban Area Extraction Method Based on Progressive Learning Models
    • 8.7 Remote Sensing Monitoring of Urban Geological Hazards
    • Questions
    • References
  • 9 Remote Sensing Monitoring Technology and Practice of Urban Ecological Environment
    • 9.1 Remote Sensing Monitoring Demands of Urban Ecological Environment
      • 9.1.1 The Concept of Urban Heat Island and the Remote Sensing Monitoring Demands of the Urban Thermal Environment
      • 9.1.2 Application Demands for Remote Sensing Inversion of Urban Aboveground Biomass
    • 9.2 Remote Sensing Monitoring Methods and Practice of Urban Heat Island Effect
    • 9.3 Remote Sensing Inversion and Application of Urban Aboveground Biomass
    • 9.4 Innovative Models and Methods in Remote Sensing Quantitative Monitoring of Cyanobacteria from Urban Lakes with Eutrophication
    • Questions
    • References
  • 10 Prospects of Urban Remote Sensing Technologies and Applications
    • 10.1 The Developing Directions of Urban Remote Sensing Sensors
    • 10.2 New Application Fields of Urban Remote Sensing
    • 10.3 The Future Directions of Urban Remote Sensing
    • Questions
    • References
  • Index

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