Spatio-Temporal Data Mining for Typhoon Image Collection

Our research aims at discovering useful knowledge from the large collection of satellite images of typhoons using data mining approaches. We first introduce the creation of the typhoon image collection that consists of around 34,000 typhoon images for the northern and southern hemisphere, providing the medium-sized, richly-variational and quality-controlled data collection suitable for spatio-temporal data mining research. Next we apply several data mining approaches for this image collection. We start with spatial data mining, where principal component analysis is used for extracting basic components and reducing dimensionality, and it revealed that the major principal components describe latitudinal structures and spiral bands. Moreover, clustering procedures give the "birds-eye-view" visualization of typhoon cloud patterns. We then turn to temporal data mining, including state transition rules, but we demonstrate that it involves intrinsic difficulty associated with the no...

• Type: Journal
• Year: 2002
• Where: JIIS
• Authors: Asanobu Kitamoto
• Keywords: Image, JIIS 2002, Typhoon, Typhoon Image