Acta Geographica Sinica ›› 2018, Vol. 73 ›› Issue (8): 1397-1406.doi: 10.11821/dlxb201808001

Special Issue: 地理大数据

• Theoretical Frontiers •     Next Articles

Geographic big-data: A new opportunity for geography complexity study

CHENG Changxiu1,2,3(),SHI Peijun1,2,3,SONG Changqing1,3,GAO Jianbo1,3   

  1. 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    2. Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China
    3. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2018-06-02 Online:2018-08-15 Published:2018-07-31
  • Supported by:
    National Natural Science Foundation of China, No.41771537;Talent Start Project of Beijing Normal University


Since 2010, big data has played a significant role in various fields of science, engineering and society. The paper introduces the concepts of geographic big-data, the fourth paradigm and nonlinear complex geographic system, and discusses interactive relationships of these concepts. It is proposed that geographic big-data and the fourth paradigm would become a new opportunity to research on geography complexity. Then the paper discusses how to use the methods of geographic big-data and complexity science to examine geography complexity. For example, based on big-data, a series of indicators of statistical physics fields could be constructed to describe the complex nonlinear characteristics of the real geographic world. Deep learning, complex network and multi-agent methods can be used to model and simulate the complex nonlinear geographic systems. These methods are important for a better understanding of the complexity of geographic phenomena and processes, as well as the analysis, simulation, inversion and prediction of complex geographic systems. Finally, the paper highlights that the combination of geographic big-data and complexity science would be the mainstream scientific method of geography in the 21st century.

Key words: geographic big-data, the fourth paradigm, nonlinearity, geography complexity