An innovative data mining procedure, using clean algorithm and factor analysis, for irregularly sampled temporal environmental data sets

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Published: Jan 1, 2007
DOI: https://doi.org/10.12681/bgsg.17225
Keywords:
Missing data Fourier transform CLEAN algorithm Factor analysis Environmental data
E. Fakiris
Laboratory of Marine Geology and Physical Oceanography, Department of Geology, University of Patras
G. Papatheodorou
Laboratory of Marine Geology and Physical Oceanography, Department of Geology, University of Patras
P. Panagiotopoulos
Laboratory of Marine Geology and Physical Oceanography, Department of Geology, University of Patras
Abstract

Environmental data are often irregularly collected in the time domain due to various reasons which affect the field sampling schedule. As a result, data sets with uneven time step and time periods with no measurements are frequently built. Many problems occur in such data sets when processed owing to that neither statistical nor spectral analysis methods can easily be applied to them without any specific pre-treatment. In our study it is demonstrated a unified methodological scheme especially designed to deal with incomplete and unevenly sampled temporal data sets. This method consists of the CLEAN algorithm and the Factor analysis. The proposed methodology is successfully applied to data sets that belong to two sampling sites of the Greek river Strimonas

Article Details
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  • New Technologies in Geophysical and Geological Research
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