Acta Geodaetica et Cartographica Sinica ›› 2022, Vol. 51 ›› Issue (6): 1062-1069.doi: 10.11947/j.AGCS.2022.20220125

• Cartography and Geoinformation • Previous Articles     Next Articles

A note on GeoAI from the perspective of geographical laws

LIU Yu1,2, GUO Hao1, LI Haifeng3, DONG Weihua4, PEI Tao5   

  1. 1. Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China;
    2. Institute for Artificial Intelligence, Peking University, Beijing 100871, China;
    3. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;
    4. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;
    5. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2022-02-24 Revised:2022-04-11 Published:2022-07-02
  • Supported by:
    The National Natural Science Foundation of China(Nos. 41830645;41971331)

Abstract: Recently, the rapid development of artificial intelligence has reshaped the research paradigm of many disciplines. Regarding geography, this trend is no exception. From the perspective of knowledge discovery, geographical research has two major tasks: revealing big unknowns and discovering laws. Artificial intelligence helps geographers discover knowledge or even automatically extract knowledge from these two aspects. Compared with other geoscience disciplines, geography focuses more on discovering "universal" laws. However, in the process of seeking geographical laws, we need to deal with the trade-off between universality and geographical heterogeneity, the core in which can be expressed as the theoretical foundation in artificial intelligence learning: generalization and interpretability. Therefore, there is an inherent logical consistency between the two disciplines. Introducing artificial intelligence to geographical studies will help to strengthen the disciplinary basis. This paper gives an example framework for artificial intelligence to discover geographical laws, and points out the future directions of geospatial artificial intelligence and geographic information science.

Key words: geographical heterogeneity, geographical law, geospatial artificial intelligence, geographic information science

CLC Number: