APPLICATION OF GEOGRAPHICAL INFORMATION SYSTEM AND PRINCIPAL COMPONENTS ANALYSIS IN ANALYSIS OF LONG TERM CLIMATE MONITORING DATA
Received date: 1999-10-26
Revised date: 2000-02-21
Online published: 2000-10-01
The objective of this study is to develop a new approach for long term climate monitoring data mining by using geo-information system (GIS), digital image processing, principal components analysis (PCA) and spatial iterative self-organizing unsupervised classification technologies. Monthly mean air-tempurature and precipitation data collected from 160 cities in China from 1987 to 1996 were interpolated spatially into digital images, then principal components analysis and spatial iterative self-organizing unsupervised classification were performed. In comparison with the previous classification results by using traditional schemes, climate zoning result from this method is similar to traditional climate zoning schemes.But in some districts zoning result is bad due to sparsity or scarsity of monitoring data. But GIS and SPCA
showed advantage in analyzing long term climate monitoring data.
LI Ben-gang,TAO Shu，LAM Kin-che,CHENG Shou-quan . APPLICATION OF GEOGRAPHICAL INFORMATION SYSTEM AND PRINCIPAL COMPONENTS ANALYSIS IN ANALYSIS OF LONG TERM CLIMATE MONITORING DATA[J]. Advances in Earth Science, 2000 , 15(5) : 509 -515 . DOI: 10.11867/j.issn.1001-8166.2000.05.0509
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