A novel method for discovering spatio-temporal clusters of different sizes, shapes, and densities in the presence of noise

International Journal of Digital Earth

Volumn 7, Issue 2, 2014, Pages 138-157

  Liu, Qiliang ^a,b   Deng, Min ^a   Bi, Jiantao ^c   Yang, Wentao ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c CENTER FOR EARTH OBSERVATION AND DIGITAL EARTH   (China)

Author keywords

data mining; Digital Earth; foreshocks and aftershocks; geo spatial science; geospatial data integration; shared nearest neighbor; spatio temporal clustering; spatio temporal density; windowed distance

Indexed keywords

CLUSTER ANALYSIS; DATA INTEGRATION; DATA MINING; EARTHQUAKES;

DIGITAL EARTH; FORESHOCKS AND AFTERSHOCKS; GEO-SPATIAL; GEOSPATIAL DATA INTEGRATION; SHARED NEAREST NEIGHBORS; SPATIO TEMPORAL; SPATIO-TEMPORAL CLUSTERING; WINDOWED DISTANCE;

CLUSTERING ALGORITHMS;

ALGORITHM; COMPUTER SIMULATION; DATA MINING; NOISE; NUMERICAL MODEL; SHAPE ANALYSIS; SIZE DISTRIBUTION; SPATIOTEMPORAL ANALYSIS; AFTERSHOCK; DENSITY; EXPERIMENTAL STUDY; FORESHOCK; SEISMIC DATA; SEISMIC NOISE; SHAPE; SIZE;

EID: 84893264629     PISSN: 17538947     EISSN: 17538955     Source Type: Journal    
DOI: 10.1080/17538947.2012.655256     Document Type: Article

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