Object-oriented spatial-temporal association rules mining on ocean remote sensing imagery

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Xue, C.J.^1 ; Dong, Q.^1 ; Ma, W.X.^1

Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China^1

关键词: Apriori algorithms;    Association rules mining;    Direct association pattern;    Marine remote sensing;    Mutual information theory;    Object oriented method;    Ocean remote sensing;    Spatiotemporal analysis;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012109/pdf
DOI  :  10.1088/1755-1315/17/1/012109

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Using the long term marine remote sensing imagery, we develop an object-oriented spatial-temporal association rules mining framework to explore the association rules mining among marine environmental elements. Within the framework, two key issues are addressed. They are how to effectively deal with the related lattices and how to reduce the related dimensions? To deal with the first key issues, this paper develops an object-oriented method for abstracting marine sensitive objects from raster pixels and for representing them with a quadruple. To deal with the second key issues, by embedding the mutual information theory, we construct the direct association pattern tree to reduce the related elements at the first step, and then the Apriori algorithm is used to discover the spatio-temporal associated rules. Finally, Pacific Ocean is taken as a research area and multi- marine remote sensing imagery in recent three decades is used as a case study. The results show that the object-oriented spatio-temporal association rules mining can acquire the associated relationships not only among marine environmental elements in same region, also among the different regions. In addition, the information from association rules mining is much more expressive and informative in space and time than traditional spatio-temporal analysis.