LIN Hui, YOU Lan, HU Chuanbo, CHEN Min. Prospect of Geo-Knowledge Engineering in the Era of Spatio-Temporal Big Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2205-2211. DOI: 10.13203/j.whugis20180318
Citation: LIN Hui, YOU Lan, HU Chuanbo, CHEN Min. Prospect of Geo-Knowledge Engineering in the Era of Spatio-Temporal Big Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2205-2211. DOI: 10.13203/j.whugis20180318

Prospect of Geo-Knowledge Engineering in the Era of Spatio-Temporal Big Data

  • With the construction of the smart city, the maturing sensor technology makes the spatio-temporal available. Every year, the amount of various kinds of spatio-temporal data from remote sensors, map servers, video monitoring, crawler and social platform reach up to PBs. Human society has entered the era of spatio-temporal big data. However, the sharp contrast between the sudden increase of mass data and the lack of information appreciation mechanism appears. The geo-knowledge produced by only IT are blacked seriously. How to use the emerging technology, combined with geographic information and accordingly analysis means, to produce, mine and use the spatio-temporal data has become the key problem to be solved urgently. Geo-knowledge is centered on human spatial cognition and complex knowledge discovery technology, which is of great significance for intelligent applications and government decision-making in the age of big data. In the era background of spatio-temporal big data, this paper discusses the connotation, time features, structure and research directions of geo-knowledge engineering in the future. Strongly driven by the virtual geographical environment, digital earth, smart city, geo-know-ledge engineering will promote the traditional GIS transforming to the directions of human cognition and exploration procedure. Through the rapid transformation from massive spatio-temporal data to the geo-knowledge, geo-knowledge engineering promises to solve the challenge problem of "geo-know-ledge explosion but knowledge poor" which will increase the efficiency of data use.
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