A Multi-source Spatio-temporal Data Fusion Framework Based on Urban Information Units


This work is supported by National Key Research and Development Program of China (2019YFB2102503), Basic Research Funds of the Chinese Academy of Surveying and Mapping (AR2111), and Excellent Platform of Lanzhou Jiaotong University (201806)

Ethical statement:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials

    The construction of smart cities can effectively improve urban governance and operation capacity and break the urban development dilemma. To explore how to provide intelligent services for urban management through spatio-temporal big data in the physical-digital space intersection, this paper proposes a transparent fusion framework for multi-source spatio-temporal big data based on the analysis of the semantic relationships of multi-source, multi-dimensional, and heterogeneous spatio-temporal big data.To achieve this goal, a concept of “city information unit” is further proposed as the basis for building the data organization of physical-digital spatial integration. In particular, the multi-source, multi-dimensional,and heterogeneous spatio-temporal big data are first actively aggregated, semantically resolved, and then the geographic knowledge is constructed spatiotemporally; based on the unique data code, the data information is mapped to the city information unit; Next, in this paper, data matching model and association model are found, and a transparent data fusion framework is constructed. Combined with multi-source heterogeneous data element matching technology, a transparent spatio-temporal data fusion rule base is constructed. Finally, with the support of various fusion methods, the transparent fusion of urban entity and spatio-temporal multi-source spatio-temporal data is realized. With the help of urban information unit and data coding, we realize the dynamic integration system of urban entity and spatio-temporal big data, so as to provide users with intelligent information services.

    Cited by
Get Citation

LIU Shangqin, ZHANG Fuhao, QIU Agen, et al. A Multi-source Spatio-temporal Data Fusion Framework Based on Urban Information Units[J]. Journal of Integration Technology,2023,12(3):34-47

Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Received:
  • Revised:
  • Adopted:
  • Online: May 11,2023
  • Published: