Journal of Geo-information Science, Volume. 22, Issue 1, 41(2020)
Fig. 3. Spurious spatial co-location patterns caused by the random interactions
Fig. 5. Relationship between spatio-temporal clusters and data scale
Fig. 6. Meteorological division identified by the statistical method for spatio-temporal clustering
Fig. 9. Induced spatial auto-correlations between different features
Fig. 10. Pattern reconstruction based on multi-modal summary characteristics
Fig. 11. Spatio-temporal co-location patterns determined by the statistical method
Fig. 12. Space-time support vector regression model considering both auto-correlation and heterogeneity
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Min DENG, Jiannan CAI, Wentao YANG, Jianbo TANG, Xuexi YANG, Qiliang LIU, Yan SHI.
Received: Sep. 4, 2019
Accepted: --
Published Online: Sep. 16, 2020
The Author Email: CAI Jiannan (jiannan.cai@csu.edu.cn)