Digital twins (DTs) is also known as digital mirroring. The fundamental idea is to employ information technology to model real-world entities with properties and actions so that they can interact with other entities in digital models. Digital models themselves can be adjusted by changing their parameters and input information to perform predictive diagnosis and optimization on the entities. With the rapid technological development of earth observation, Internet of Things, and big data, our ability of monitoring, modeling, and simulation of the real world is rapidly improving. The application potential of DTs in complex geospatial systems such as the environment, energy sector, smart cities, and smart coasts is gradually emerging, which also raises new requirements on applications of geospatial modeling and analysis in DTs.
The Earth is a multi-sphere complex system, and the construction of its digital twins calls for representation and analysis of various geographical objects and geographical phenomena. Firstly, in terms of data modeling, it is necessary to develop a comprehensive data acquisition infrastructure including vehicle-mounted or airborne LIDAR, unmanned vehicle, and the Internet of Things, and to develop data models that can support the representation and modeling of data of different sources, dimensions, and types. Secondly, regarding analysis, more emphasis should be placed on the connections and interactions between virtual space and the real world, and on the capability of dynamically updating DT models, real-time control of physical entities, and online optimization for improved decision-making schemes. Thirdly, in the application and practice of DTs, it is essential to take advantage of the virtual space to inform designs in the real world. At the same time, attention shall be paid to data security, visual representation, and multi-agent distributed computing in the twin environment.
This Research Topic welcomes high-quality Original Research and Review Articles underscoring the collection, processing, modeling, analysis, visualization, and application of geospatial data and information for digital twins. Particular focus will be given to the following topics, but not be limited to:
• Data acquisition for DTs (e.g., remote sensing, LIDAR, Internet of Things)
• Spatiotemporal data models for DTs
• Data integration of different sources, dimensions, and types
• Data management and mining
• Multi-agent systems
• Augment reality visualization of geographic information
• Artificial intelligence and big data
• Decision support systems
• Digital twin applications (e.g., smart cities, smart communities, and smart coasts)
Digital twins (DTs) is also known as digital mirroring. The fundamental idea is to employ information technology to model real-world entities with properties and actions so that they can interact with other entities in digital models. Digital models themselves can be adjusted by changing their parameters and input information to perform predictive diagnosis and optimization on the entities. With the rapid technological development of earth observation, Internet of Things, and big data, our ability of monitoring, modeling, and simulation of the real world is rapidly improving. The application potential of DTs in complex geospatial systems such as the environment, energy sector, smart cities, and smart coasts is gradually emerging, which also raises new requirements on applications of geospatial modeling and analysis in DTs.
The Earth is a multi-sphere complex system, and the construction of its digital twins calls for representation and analysis of various geographical objects and geographical phenomena. Firstly, in terms of data modeling, it is necessary to develop a comprehensive data acquisition infrastructure including vehicle-mounted or airborne LIDAR, unmanned vehicle, and the Internet of Things, and to develop data models that can support the representation and modeling of data of different sources, dimensions, and types. Secondly, regarding analysis, more emphasis should be placed on the connections and interactions between virtual space and the real world, and on the capability of dynamically updating DT models, real-time control of physical entities, and online optimization for improved decision-making schemes. Thirdly, in the application and practice of DTs, it is essential to take advantage of the virtual space to inform designs in the real world. At the same time, attention shall be paid to data security, visual representation, and multi-agent distributed computing in the twin environment.
This Research Topic welcomes high-quality Original Research and Review Articles underscoring the collection, processing, modeling, analysis, visualization, and application of geospatial data and information for digital twins. Particular focus will be given to the following topics, but not be limited to:
• Data acquisition for DTs (e.g., remote sensing, LIDAR, Internet of Things)
• Spatiotemporal data models for DTs
• Data integration of different sources, dimensions, and types
• Data management and mining
• Multi-agent systems
• Augment reality visualization of geographic information
• Artificial intelligence and big data
• Decision support systems
• Digital twin applications (e.g., smart cities, smart communities, and smart coasts)
