A general method of spatio-temporal clustering analysis

作者：Deng Min^*; Liu QiLiang; Wang JiaQiu; Shi Yan

来源：Science China Information Sciences, 2013, 56(10): 102315.

DOI：10.1007/s11432-011-4391-8

• spatio-temporal clustering
• spatio-temporal autocorrelation
• spatio-temporal heterogeneity
• spatio-temporal data mining

Spatio-temporal clustering has been a hot topic in the field of spatio-temporal data mining and knowledge discovery. It can be employed to uncover and interpret developmental trends of geographic phenomenon in the real world. However, existing spatio-temporal clustering methods seldom consider both spatiotemporal autocorrelations and heterogeneities among spatio-temporal entities, and the coupling in space and time has not been well highlighted. In this paper, a unified framework for the clustering analysis of spatio-temporal data is proposed, and a novel spatio-temporal clustering algorithm is developed by means of a spatio-temporal statistics methodology and intelligence computation technology. Our method is applied successfully to finding spatio-temporal cluster in China's annual temperature database for the period 1951-1992.

• 出版日期2013-10
• 单位中南大学