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.
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
. Paleogeographic Reconstruction Driven by Big Data: Challenges and Prospects[J]. Geological Journal of China Universities, 2020
, 26(1)
: 73
.
DOI: 10.16108/j.issn1006-7493.2019091
