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Geological Journal of China Universities ›› 2020, Vol. 26 ›› Issue (1): 73-.DOI: 10.16108/j.issn1006-7493.2019091

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Paleogeographic Reconstruction Driven by Big Data: Challenges and Prospects

ZHANG Lei,ZHONG Hanting,CHEN Anqing,ZHAO Yingquan,HUANG Keke,LI Fengjie,HUANG Hu,LIU Yu,CAO Haiyang,ZHU Shengxian,MU Caineng,HOU Mingcai,JAMES G. Ogg   

  1. 1. Institute of Sedimentary Geology, Chengdu University of Technology, Chengdu 610059, China;
    2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of Technology) ,
    Chengdu 610059, China;
    3. Department of Earth, Atmospheric and Planetary Sciences, Purdue University, West Lafayette 47907, USA
  • Online:2020-02-20 Published:2020-03-05

Abstract: Paleogeography is a typical data-reliable subject. Paleogeographic reconstruction focuses on the characteristics of geographic, life, and climate changes on the Earth's surface through geological history. In the new era of big data, the continuous accumulation of massive paleogeographic data and the rapid development of computer science technology make it possible to reconstruct the paleogeographic history using more standard and intelligent tools and software. The current paper reviews the major databases and research groups related to paleogeography, and proposes the following key components of big data-driven paleogeographic reconstruction: (1) A standard paleogeographic knowledge system; (2) An open and interactive paleogeographic data platform with new technologies such as natural-language understanding to expand data sources; (3) Paleogeographic data quality control mechanisms; (4) Various types of paleogeographic reconstruction models contructed with artificial intelligence technology; (5) Visual outputs as time-sliced maps or animations.

Key words: paleogeographic reconstruction, big data, database, machine learning

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