Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework
AbstractThis paper presents an integrated framework for exploratory multi-scale spatio-temporal feature extraction and clustering of spatio-temporal data. The framework combines the multi-scale spatio-temporal decomposition, feature identification, feature enhancing and clustering in a unified process. The original data are firstly reorganized as multi-signal time series, and then decomposed by the multi-signal wavelet. Exploratory data analysis methods, such as histograms, are used for feature identification and enhancing. The spatio-temporal evolution process of the multi-scale features can then be tracked by the feature clusters based on the data adaptive Fuzzy C-Means Cluster. The approach was tested with the global 0.25° satellite altimeter data over a period of 21 years from 1993 to 2013. The tracking of the multi-scale spatio-temporal evolution characteristics of the 1997–98 strong El Niño were used as validation. The results show that our method can clearly reveal and track the spatio-temporal distribution and evolution of complex geographical phenomena. Our approach is efficient for global scale data analysis, and can be used to explore the multi-scale pattern of spatio-temporal processes. View Full-Text
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Luo, W.; Yu, Z.-Y.; Xiao, S.-J.; Zhu, A.-X.; Yuan, L.-W. Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework. ISPRS Int. J. Geo-Inf. 2015, 4, 1870-1893.
Luo W, Yu Z-Y, Xiao S-J, Zhu A-X, Yuan L-W. Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework. ISPRS International Journal of Geo-Information. 2015; 4(4):1870-1893.Chicago/Turabian Style
Luo, Wen; Yu, Zhao-Yuan; Xiao, Sheng-Jun; Zhu, A-Xing; Yuan, Lin-Wang. 2015. "Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework." ISPRS Int. J. Geo-Inf. 4, no. 4: 1870-1893.