Spatial–Temporal Big Data Enables Social Governance

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Abstract

The application of GIS technologies has extended from natural sciences to social sciences. The emerging spatial–temporal big data supported by GIS has broad applications in social governance. Through a unified time–space reference, multi-source big data from different departments can be linked and organized, forming a block data. A cloud platform based on the block data is developed for data processing, data fusion, data analysis, and data mining. This cloud platform can support the management of specific public affairs, such as natural resources management, urban and rural planning, and urban construction. In the future, we need to further explore and use spatial–temporal big data to constantly improve our spatial governance capabilities.

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References

  • Anselin, L., Li, X., & Koschinsky, J. (2021). GeoDa, From the Desktop to an Ecosystem for Exploring Spatial Data. Geographical Analysis, 1–28.

    Google Scholar 

  • Ding, X., Fan, H., & Gong, J. (2021). Towards generating network of bikeways from Mapillary data. Computers, Environment and Urban Systems, 88, 101632.

    Article  Google Scholar 

  • Gong, J., & Wu, H. (2012). The geospatial service web: Ubiquitous connectivity with geospatial services. Transactions in GIS, 16(6), 741–743.

    Article  Google Scholar 

  • Gong, J., Liu, C., & Huang, X. (2020). Advances in urban information extraction from high-resolution remote sensing imagery. Science China Earth Sciences, 63(4), 463–475.

    Article  Google Scholar 

  • Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Computational social science. Science, 323(5915), 721–723.

    Article  Google Scholar 

  • Lazer, D. M. J., Pentland, A., Watts, D. J., Aral, S., Athey, S., Contractor, N., Freelon, D., Gonzalez-Bailon, S., King, G., Margetts, H., Nelson, A., Salganik, M. J., Strohmaier, M., Vespignani, A., & Wagner, C. (2020). Computational social science: Obstacles and opportunities. Science, 369(6507), 1060–1062.

    Article  Google Scholar 

  • Li, D., Yao, Y., Shao, Z., & Wang, L. (2014). From digital Earth to smart Earth. Chinese Science Bulletin, 59(8), 722–733.

    Article  Google Scholar 

  • Li, F., Gui, Z., Wu, H., Gong, J., Wang, Y., Tian, S., & Zhang, J. (2018). Big enterprise registration data imputation: Supporting spatiotemporal analysis of industries in China. Computers, Environment and Urban Systems, 70, 9–23.

    Article  Google Scholar 

  • Lin, W. (2013). Digitizing the Dragon Head, geo-coding the urban Landscape: GIS and the transformation of China’s Urban Governance. Urban Geography, 34(7), 901–922.

    Article  Google Scholar 

  • Lin, W. (2008). GIS development in China’s urban governance: A case study of Shenzhen. Transactions in GIS, 12(4), 493–514.

    Article  Google Scholar 

  • Liu, Y. (2021). Core or edge? Revisiting GIScience from the geography-discipline perspective. Science China-Earth Sciences, 64, 1–4.

    Article  Google Scholar 

  • Lv, Z., Li, X., Wang, W., Zhang, B., Hu, J., & Feng, S. (2018). Government affairs service platform for smart city. Future Generation Computer Systems, 81, 443–451.

    Article  Google Scholar 

  • Mukherjee, F. (2018). GIS use by an urban local body as part of e-governance in India. Cartography and Geographic Information Science, 45(6), 556–569.

    Article  Google Scholar 

  • Mukherjee, F. (2020). Institutional networks of association for GIS use: The case of an urban local body in India. Annals of the American Association of Geographers, 110(5), 1445–1463.

    Article  Google Scholar 

  • Pei, T., Xu, J., Liu, Y., Huang, X., Zhang, L., Dong, W., Qin, C., Song, C., Gong, J., & Zhou, C. (2021). GIScience and remote sensing in natural resource and environmental research: Status quo and future perspectives. Geography and Sustainability, 2(3), 207–215.

    Article  Google Scholar 

  • Shi, Y., Deng, M., Yang, X., & Gong, J. (2018). Detecting anomalies in spatio-temporal flow data by constructing dynamic neighbourhoods. Computers, Environment and Urban Systems, 67, 80–96.

    Article  Google Scholar 

  • Trencher, G. (2019). Towards the smart city 2.0: Empirical evidence of using smartness as a tool for tackling social challenges. Technological Forecasting and Social Change, 142, 117–128.

    Article  Google Scholar 

  • United Nations, Department of Economic and Social Affairs, Population Division. (2015). World Urbanization Prospects: The 2014 Revision, (ST/ESA/SER.A/366).

    Google Scholar 

  • Wright, D. J., Duncan, S. L., & Lach, D. (2009). Social power and GIS technology: A review and assessment of approaches for natural resource management. Annals of the Association of American Geographers, 99(2), 254–272.

    Article  Google Scholar 

  • Zhou, C., Su, F., Pei, T., Zhang, A., Du, Y., Luo, B., Cao, Z., Wang, J., Yuan, W., Zhu, Y., Song, C., Chen, J., Xu, J., Li, F., Ma, T., Jiang, L., Yan, F., Yi, J., & **ao, H. (2020). COVID-19: Challenges to GIS with big data. Geography and Sustainability, 1(1), 77–87.

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (92038301).

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Correspondence to Jianya Gong .

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Gong, J., Xu, G. (2022). Spatial–Temporal Big Data Enables Social Governance. In: Li, B., Shi, X., Zhu, AX., Wang, C., Lin, H. (eds) New Thinking in GIScience. Springer, Singapore. https://doi.org/10.1007/978-981-19-3816-0_27

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