Fig 1：White Paper on the Strategic Development of Spatial Data Intelligence in China officially released
On 27th April 2024, the White Paper on China's Spatial Data Intelligence Strategy, organised by ACM SIGSPATIAL in China Branch, was officially released at the 5th Spatial Data Intelligence Conference (SpatialDI 2024) held in Nanjing, Jiangsu Province. Under the guidance of many academicians and senior experts at home and abroad, a number of well-known experts and scholars in the fields of geographic information science, computer science and mathematics were invited to form a writing group, and Dr Wang Shaohua's team from the Institute of Space and Astronautical Information Innovation of the Chinese Academy of Sciences (ISIAS) wrote the report, which was finally formed after several rounds of review and modification. The White Paper on China's Spatial Data Intelligence Strategy is a joint effort of the expert group to promote the development of spatial data intelligence models in the AGI era and their applications in the fields of urban, airspace remote sensing, geography, and transportation, as well as to promote academic exchanges of theories, technologies, and applications in the fields of geo-information science and computer science in the cross-research of spatial data intelligence models, and to address the major challenges and challenges facing the development of the spatial data intelligence model industry. model industry development faces major challenges and bottlenecks pointed out the direction.
Fig 2：Editorial Board Director Professor Meng Xiaofeng released the "White Paper on China's Spatial Data Intelligence Strategy"
Fig 3：Dr. Wang Shaohua gave a conference report to interpret the overview of "White Paper on China's Spatial Data Intelligence Strategy"
The spatial data intelligence model is a comprehensive basic model for the systematic, comprehensive and in-depth analysis and processing of multimodal, massive and heterogeneous spatial data based on the cross-disciplinary and multifaceted technological means of geography, informatics, mathematics, physics, artificial intelligence and big data, and the integration of spatial, computational and systemic thinking into a single model. The spatial data intelligence model can not only efficiently integrate all kinds of spatial data resources, but also realises the fusion and cross-application of multi-source data, intelligently extract the potential value and laws of spatial data, and provide accurate spatial information services and decision-making support for various industries. The spatial data intelligence model covers the main development directions of data perception, data management, data analysis and data security, and realises all-round intelligent processing and application of spatial data through comprehensive perception, fine management, in-depth analysis and security of data. The spatial data intelligence grand model not only focuses on spatial data acquisition and perception, but also on spatial data storage, management and in-depth analysis, as well as data privacy and security.
Compared with traditional artificial intelligence models, the spatial data intelligence model has the following significant features: firstly, it realizes multi-source spatial data fusion, integrates spatial data from multiple sources such as GIS, remote sensing technology, sensor networks, etc., and achieves all-round, multi-dimensional spatial information acquisition and analysis; secondly, it has the ability of cross-field cross-application, which is not only confined to the field of computers, but also cross fused with Secondly, it has the ability of cross-field cross-application, which is not limited to the field of computer, but can also be cross-integrated with data and knowledge of other fields, such as mathematics, remote sensing, meteorology, geology, etc., to achieve cross-field comprehensive analysis and intelligent decision-making; furthermore, it has the ability of efficiently processing massive spatial data, and it can cope with large-scale, high-dimensional spatial data, and with the help of distributed computing and high-performance computing platforms, it can achieve rapid processing and analysis of massive data; lastly, it possesses the function of intelligent inference and prediction. By learning the laws and patterns of spatial data, it realises intelligent reasoning and prediction, providing users with accurate spatial information services and decision-making support.
The emergence and development of intelligence models of spatial data have filled the technical gaps in the field of spatial data analysis and provided new ideas and methods for solving various complex problems. However, the development and application of realising intelligence models for spatial data still face three challenges: how to build effective models at different scales so that they have good generalisation ability and adaptability, given that data distribution and features show different regularities and change trends at different spatial scales; how to improve the effectiveness of large models so that they can efficiently and accurately handle massive spatial data. At the same time, how to improve the stability and reliability of generative intelligent models so that they can generate high-quality spatial data is also an important core technical challenge for spatial data intelligence models.
Fig 4：China Spatial Data Intelligence Strategy White Paper Outline
China Spatial Data Intelligence Strategy White Paper provides in-depth elaboration on topics such as definition, development history, current status and trends, and challenges faced by spatial data intelligence models, systematically elaborates key technologies of spatial data intelligence models and application scenarios in cities, air and space remote sensing, geography, and traffic, and panoramically collates and summarises the current stage of spatial data intelligence models in cities, multimodality, remote sensing, intelligent transportation, resource and environment, etc., which points out the direction for the future development of spatial data intelligence models.
Highlight 1: Outline and clarify the current status of the development of spatial data intelligence models
The White Paper on Strategic Development of Spatial Data Intelligence in China follows the current wave of spatial data intelligence model technology, elaborates on the background and definition of the core concept of spatial data intelligence model, discusses in depth the three stages of development of spatial data intelligence model, and analyses the current research status and development trend of spatial data intelligence model. On this basis, the white paper combines the current development trajectory and problems of spatial data intelligence model, puts forward the three major challenges faced by spatial data intelligence model nowadays, and points out the future development prospect of spatial data intelligence model.
Highlight 2: A clear framework to sort out the thematic areas of spatial data intelligence models
Focusing on the research status of big models of spatial data intelligence at the present stage, the White Paper on Strategic Development of Spatial Data Intelligence in China, on the basis of summarising the results of the meeting of the 2nd China Spatial Data Intelligence Strategy Workshop held in Beijing in December 2023, has sorted out four major thematic areas of big models of spatial data intelligence. Firstly, the white paper starts from the basic issues of big models and introduces the purpose and significance of developing big models for spatial data intelligence nowadays; secondly, it summarises the progress of big model research in the four thematic areas of urban, air and space remote sensing, geography, and transportation; and lastly, the white paper puts forward the new viewpoints of big model research in four areas, which is a way to throw out bricks to draw in jade and to lead the future development of big models.
Highlight 3: In-depth analysis of the key technologies of spatial data intelligent models
The White Paper on the Strategic Development of Spatial Data Intelligence in China, co-authored by experts in the fields of geographic information science and computer science, provides an in-depth introduction to the key technologies, characteristics and advantages of spatial data intelligence models, the current status of research, the future development and other core information, which covers not only the basic performance of spatial-temporal big data platforms, distributed computing, 3D virtual reality, spatial analyses and visualisations, and the complex spatial and comprehensive performance of big models, but also covers the complex spatial integrated performance of big models such as geospatial intelligent computing, deep learning, big data high-performance processing, geographic knowledge atlas, geographic intelligent multi-scenario simulation, etc., and thoroughly analyses the positions and roles of the above key technologies in the spatial data intelligent big models.
Highlight 4: Based on the cutting edge, demonstrate spatial data intelligence big model application cases
The intelligent model of Spatial data will change various industries in the fields of geographic information science and computer science, etc. Based on the frontier of the development of the intelligent model of spatial data, "White Paper on the Strategic Development of Spatial Data Intelligence in China " panoramically displays the latest application cases of spatial data intelligent model, which spans the five fields of urban, multi-modal data processing, remote sensing intelligent computing, intelligent transportation, resource environment, etc., bringing innovative possibilities and infinite imagination for the industrial application of spatial data intelligent big model. It brings innovative possibilities and infinite imagination for the industrial application of spatial data intelligent big model, and depicts a magnificent blueprint for the development of spatial data intelligent model. The white paper focuses on the future development of spatial data processing and analysis scenarios, and looks forward to the three development trends of spatial data intelligent model, which provides a reference for the future development of spatial data intelligent model in industry, academia and research.