Journal of Geographical Sciences ›› 2020, Vol. 30 ›› Issue (2): 233-250.doi: 10.1007/s11442-020-1725-8

• Research Articles • Previous Articles     Next Articles

From earth observation to human observation: Geocomputation for social science

LI Deren1,2, GUO Wei1,2,*(), CHANG Xiaomeng3, LI Xi1,2   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    2. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
    3. Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China
  • Received:2018-12-16 Accepted:2019-04-15 Online:2020-02-25 Published:2020-04-21
  • Contact: GUO Wei
  • About author:Li Deren (1939-), Professor and Academician of Chinese Academy of Sciences, Academician of Chinese Academy of Engineering, Academician of Euro-Asia International Academy of Sciences, specialized in the research and education on spatial information science and technology represented by RS, GPS and GIS, and promoting the construction of geographic national monitoring, digital city, digital China, smart city and smart China. E-mail:
  • Supported by:
    LIESMARS Special Research Funding


It is possible to obtain vast amounts of spatiotemporal data related to human activities to support the study of human behavior and social evolution. In this context, geography, with the human-nature relationship as its core, is undergoing a transition from strictly earth observations to the observation of human activities. Geocomputation for social science is one manifestation thereof. Geocomputation for social science is an interdisciplinary approach combining remote sensing techniques, social science, and big data computation. Driven by the availability of spatially and temporally expansive big data, geocomputation for social science uses spatiotemporal statistical analyses to detect and analyze the interactions between human behavior, the natural environment, and social activities; Remote sensing (RS) observations are used as primary data. Geocomputation for social science can be used to investigate major social issues and to assess the impact of major natural and societal events, and will surely be an area of focused development in geography in the near future. We briefly review the background of geocomputation in the social sciences, discuss its definition and disciplinary characteristics, and highlight the main research foci. Several key technologies and applications are also illustrated with relevant case studies of the Syrian Civil War, typhoon transits, and traffic patterns.

Key words: geocomputation for social science, nighttime light remote sensing, social network, traffic patterns