Manual of Digital Earth.

• Author: Guo, Huadong.
• TeilnehmendeR: Goodchild, Michael F.; Annoni, Alessandro.
• Place / Publishing House: Singapore : : Springer Singapore Pte. Limited,, 2019.; ©2020.
• Year of Publication: 2019
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (846 pages)

Table of Contents

Intro -- Preface -- Acknowledgements -- List of Editors -- Editors-in-Chief -- Managing Editors -- Contents -- About the Editors-in-Chief -- Digital Earth Technologies -- 2 Digital Earth Platforms -- 2.1 Introduction -- 2.2 Discrete Global Grid Systems -- 2.2.1 Initial Domain -- 2.2.2 Cell Type -- 2.2.3 Refinement -- 2.2.4 Projection -- 2.2.5 Indexing -- 2.3 Scientific Digital Earths -- 2.4 Public and Commercial Digital Earth Platforms -- 2.4.1 Latitude/Longitude Grids -- 2.4.2 Geodesic DGGSs -- 2.4.3 Installations: DESP -- 2.5 Discrete Global Grid System Standards -- 2.5.1 Standardization of Discrete Global Grid Systems -- 2.5.2 Core Requirements of the OGC DGGS Abstract Specification -- 2.5.3 The Future of the DGGS Standard -- 2.5.4 Linkages Between DGGS and Other Standards Activities -- References -- 3 Remote Sensing Satellites for Digital Earth -- 3.1 Development of Remote Sensing -- 3.1.1 Overview of Remote Sensing -- 3.1.2 Development of Remote Sensing Satellites -- 3.2 Land Observation Satellites -- 3.2.1 US Land Observation Satellites -- 3.2.2 European Land Observation Satellites -- 3.2.3 China's Land Observation Satellites -- 3.2.4 Other Land Observation Satellites -- 3.3 Ocean Observation Satellites -- 3.3.1 US Ocean Observation Satellites -- 3.3.2 European Ocean Observation Satellites -- 3.3.3 China's Ocean Observation Satellites -- 3.3.4 Other Ocean Observation Satellites -- 3.4 Meteorological Observation Satellites -- 3.4.1 US Meteorological Observation Satellites -- 3.4.2 European Meteorological Observation Satellites -- 3.4.3 China's Meteorological Observation Satellites -- 3.4.4 Other Meteorological Observation Satellites -- 3.5 Trends in Remote Sensing for Digital Earth -- References -- 4 Satellite Navigation for Digital Earth -- 4.1 Introduction -- 4.2 Global Navigation Satellite System -- 4.2.1 BDS -- 4.2.2 GPS -- 4.2.3 GLONASS.

4.2.4 Galileo -- 4.3 GNSS Augmentation Systems -- 4.3.1 Wide-Area Differential Augmentation System -- 4.3.2 Global Differential Precise Positioning System -- 4.3.3 Local Area Differential Augmentation System -- 4.3.4 Local Area Precise Positioning System -- 4.4 Applications in Digital Earth Case Studies -- 4.4.1 Terrestrial Reference System -- 4.4.2 Time System -- 4.4.3 High-Precision Positioning -- 4.4.4 Location-Based Service -- References -- 5 Geospatial Information Infrastructures -- 5.1 Introduction -- 5.2 A Brief History of Geospatial Information Infrastructures -- 5.2.1 Geospatial Information Infrastructure Milestones -- 5.2.2 Architectural Evolutions in Geospatial Information Infrastructure Development -- 5.3 Geospatial Information Infrastructures Today -- 5.3.1 The Evolution of Geospatial Information on the Web -- 5.3.2 Geospatial Information Infrastructures Champion Openness -- 5.3.3 Capacity Building and Learning for Geospatial Information Infrastructures -- 5.4 Recent Challenges and Potential for Improvement -- 5.4.1 Strengthened Role of Semantics -- 5.4.2 Is Spatial Still Special? -- 5.5 Conclusion and Outlook -- References -- 6 Geospatial Information Processing Technologies -- 6.1 Introduction -- 6.2 High-Performance Computing -- 6.2.1 The Concept of High-Performance Computing: What and Why -- 6.2.2 High-Performance Computing Platforms -- 6.2.3 Spatial Database Management Systems and Spatial Data Mining -- 6.2.4 Applications Supporting Digital Earth -- 6.2.5 Research Challenges and Future Directions -- 6.3 Online Geospatial Information Processing -- 6.3.1 Web Service-Based Online Geoprocessing -- 6.3.2 Web (Coverage) Processing Services -- 6.3.3 Online Geoprocessing Applications in the Context of Digital Earth -- 6.3.4 Research Challenges and Future Directions -- 6.4 Distributed Geospatial Information Processing.

6.4.1 The Concept of Distributed Geospatial Information Processing: What and Why -- 6.4.2 Fundamental Concepts and Techniques -- 6.4.3 Application Supporting Digital Earth -- 6.4.4 Research Challenges and Future Directions -- 6.5 Discussion and Conclusion -- References -- 7 Geospatial Information Visualization and Extended Reality Displays -- 7.1 Introduction -- 7.2 Visualizing Geospatial Information: An Overview -- 7.2.1 Representation -- 7.2.2 User Interaction and Interfaces -- 7.3 Understanding Users: Cognition, Perception, and User-Centered Design Approaches for Visualization -- 7.3.1 Making Visualizations Work for Digital Earth Users -- 7.4 Geovisual Analytics -- 7.4.1 Progress in Geovisual Analytics -- 7.4.2 Big Data, Digital Earth, and Geovisual Analytics -- 7.5 Visualizing Movement -- 7.5.1 Trajectory Maps: The Individual Journey -- 7.5.2 Flow Maps: Aggregated Flows Between Places -- 7.5.3 Origin-Destination (OD) Maps -- 7.5.4 In-Flow, Out-Flow and Density of Moving Objects -- 7.6 Immersive Technologies-From Augmented to Virtual Reality -- 7.6.1 Essential Concepts for Immersive Technologies -- 7.6.2 Augmented Reality -- 7.6.3 Mixed Reality -- 7.7 Virtual Reality -- 7.7.1 Virtual Geographic Environments -- 7.7.2 Foundational Structures of VGEs -- 7.8 Dashboards -- 7.9 Conclusions -- References -- 8 Transformation in Scale for Continuous Zooming -- 8.1 Continuous Zooming and Transformation in Scale: An Introduction -- 8.1.1 Continuous Zooming: Foundation of the Digital Earth -- 8.1.2 Transformation in Scale: Foundation of Continuous Zooming -- 8.1.3 Transformation in Scale: A Fundamental Issue in Disciplines Related to Digital Earth -- 8.2 Theories of Transformation in Scale -- 8.2.1 Transformation in Scale: Multiscale Versus Variable Scale -- 8.2.2 Transformations in Scale: Euclidean Versus Geographical Space.

8.2.3 Theoretical Foundation for Transformation in Scale: The Natural Principle -- 8.3 Models for Transformations in Scale -- 8.3.1 Data Models for Feature Representation: Space-Primary Versus Feature-Primary -- 8.3.2 Space-Primary Hierarchical Models for Transformation in Scale -- 8.3.3 Feature-Primary Hierarchical Models for Transformation in Scale -- 8.3.4 Models of Transformation in Scale for Irregular Triangulation Networks -- 8.3.5 Models for Geometric Transformation of Map Data in Scale -- 8.3.6 Models for Transformation in Scale of 3D City Representations -- 8.4 Mathematical Solutions for Transformations in Scale -- 8.4.1 Mathematical Solutions for Upscaling Raster Data: Numerical and Categorical -- 8.4.2 Mathematical Solutions for Downscaling Raster Data -- 8.4.3 Mathematical Solutions for Transformation (in Scale) of Point Set Data -- 8.4.4 Mathematical Solution for Transformation (in Scale) of Individual Lines -- 8.4.5 Mathematical Solutions for Transformation (in Scale) of Line Networks -- 8.4.6 Mathematical Solutions for Transformation of a Class of Area Features -- 8.4.7 Mathematical Solutions for Transformation (in Scale) of Spherical and 3D Features -- 8.5 Transformation in Scale: Final Remarks -- References -- 9 Big Data and Cloud Computing -- 9.1 Introduction -- 9.2 Big Data Sources -- 9.3 Big Data Analysis Methods -- 9.3.1 Data Preprocessing -- 9.3.2 Statistical Analysis -- 9.3.3 Nonstatistical Analysis -- 9.4 Architecture for Big Data Analysis -- 9.4.1 Data Storage Layer -- 9.4.2 Data Query Layer -- 9.4.3 Data Processing Layer -- 9.5 Cloud Computing for Big Data -- 9.5.1 Cloud Computing and Other Related Computing Paradigms -- 9.5.2 Introduction to Cloud Computing -- 9.5.3 Cloud Computing to Support Big Data -- 9.6 Case Study: EarthCube/DataCube -- 9.6.1 EarthCube -- 9.6.2 Data Cube -- 9.7 Conclusion -- References.

10 Artificial Intelligence -- 10.1 Introduction -- 10.2 Traditional and Statistical Machine Learning -- 10.2.1 Supervised Learning -- 10.2.2 Unsupervised Learning -- 10.2.3 Dimension Reduction -- 10.3 Deep Learning -- 10.3.1 Convolutional Networks -- 10.3.2 Recurrent Neural Networks -- 10.3.3 Variational Autoencoder -- 10.3.4 Generative Adversarial Networks (GANs) -- 10.3.5 Dictionary-Based Approaches -- 10.3.6 Reinforcement Learning -- 10.4 Discussion -- 10.4.1 Reproducibility -- 10.4.2 Ownership and Fairness -- 10.4.3 Accountability -- 10.5 Conclusion -- References -- 11 Internet of Things -- 11.1 Introduction -- 11.2 Definitions and status quo of the IoT -- 11.2.1 One Concept, Many Definitions -- 11.2.2 Our Definition -- 11.2.3 Early Works on the Interplay Between DE and the IoT -- 11.2.4 IoT Standards Initiatives from DE -- 11.3 Interplay Between the IoT and DE -- 11.3.1 Discoverability, Acquisition and Communication of Spatial Information -- 11.3.2 Spatial Understanding of Objects and Their Relationships -- 11.3.3 Taking Informed Actions and Acting Over the Environment (ACT) -- 11.4 Case Studies on Smart Scenarios -- 11.5 Frictions and Synergies Between the IoT and DE -- 11.5.1 Discoverability, Acquisition and Communication of Spatial Information -- 11.5.2 Spatial Understanding of Objects and Their Relationships -- 11.5.3 Taking Informed Actions and Acting Over the Environment -- 11.6 Conclusion and Outlook for the Future of the IoT in Support of DE -- References -- 12 Social Media and Social Awareness -- 12.1 Introduction: Electronic Footprints on Digital Earth -- 12.2 Multifaceted Implications of Social Media -- 12.3 Opportunities: Human Dynamics Prediction -- 12.3.1 Public Health -- 12.3.2 Emergency Response -- 12.3.3 Decision Making -- 12.3.4 Social Equity Promotion -- 12.4 Challenges: Fake Electronic Footprints -- 12.4.1 Rumors.

12.4.2 Location Spoofing.