IJG  Vol.6 No.10 , October 2015
Correspondence Analysis on a Space-Time Data Set for Multiple Environmental Variables
Author(s) Palma Monica
Applications of the multivariate technique called correspondence analysis for environmental studies are relatively new and are limited to spatial multivariate data set. In this paper, a procedure of applying correspondence analysis to a large space-time data set for multiple environmental variables is shown. In particular, nitrogen dioxide and carbon monoxide hourly concentrations measured during January 1999 at several monitored stations in a district of Northern Italy are analyzed. The procedure consists in transforming the continuous variables into categorical ones by the means of appropriate indicator variables, generating special contingency tables and applying correspondence analysis. The use of this classical multivariate technique allows the identification of important relationships among pollution levels and monitoring stations and/or relationships among pollution levels and observation times.

Cite this paper
Monica, P. (2015) Correspondence Analysis on a Space-Time Data Set for Multiple Environmental Variables. International Journal of Geosciences, 6, 1154-1165. doi: 10.4236/ijg.2015.610090.
[1]   De Iaco, S., Myers, D.E. and Posa, D. (2000) Total Air Pollution and Space-Time Modeling. In: Monestiez P., Allard D. and Froidevaux R., Eds., GeoEnv III, Geostatistics for Environmental Applications, Kluwer Academic Publishers, Norwell, 45-56.

[2]   De Iaco, S. (2011) A New Space-Time Multivariate Approach for Environmental Data Analysis. Journal of Applied Statistics, 38, 2471-2483. http://dx.doi.org/10.1080/02664763.2011.559206

[3]   Blasius, J., Greenacre, M., Groenen, P.J.F. and van de Velden, M. (2009) Special Issue on Correspondence Analysis and Related Methods. Computational Statistics and Data Analysis, 53, 3103-3106. http://dx.doi.org/10.1016/j.csda.2008.11.010

[4]   Lebart, L., Morineau, A. and Warwick, K.M. (1984) Multivariate Descriptive Statistical Analysis. John Wiley & Sons, New York.

[5]   Benzécri, J.P. (1983) Histoire et préhistoire de l’analyse des données. Dunod, Paris.

[6]   Greenacre, M.J. (1989) Theory and Applications of Correspondence Analysis. Academic Press, London.

[7]   SAS/Stat (1990) SAS Institute Inc., Cary.

[8]   (1999) SPSS 8.0, SPSS Inc., Chicago.

[9]   Avila, F. and Myers, D.E. (1991) Correspondence Analysis Applied to Environmental Data Sets: A Study of Chautauqua Lake sediments. Chemometrics and Intelligent Laboratory Systems, 11, 229-249. http://dx.doi.org/10.1016/0169-7439(91)85002-7

[10]   Avila, F., Myers, D.E. and Palmer, C. (1991) Correspondence Analysis and Adsorbate Selection for Chemical Sensor Arrays. Journal of Chemometrics, 5, 455-465.

[11]   Dutot, A.L., Bergametti, G. and Buat-Menard, P. (1988) Application of Correspondence Analysis to Apportion Sources of Ambient Particles. Athmospheric Environment, 22, 1737-1743.

[12]   Jiménez-Espinosa, R., Sousa, A.J. and Chica-Olmo, M. (1992) Application of Correspondence Analysis and Factorial Kriging Analysis: A Case Study on Geochemical Exploration in Geostatistics. 2, Soares, A. Ed., Troia, 853-864.

[13]   Greenacre, M.J. and Primicerio, R. (2013) Multivariate Analysis for Ecological Data. Fundación BBVA, Bilbao.

[14]   De Iaco, S., Palma, M. and Posa, D. (2013) Prediction of Particle Pollution through Spatio-Temporal Multivariate Geostatistical Analysis: Spatial Special Issue. AStA Advanced Statistical Analysis, 97, 133-150. http://dx.doi.org/10.1007/s10182-012-0199-0

[15]   De Iaco, S., Maggio, S., Palma, M. and Posa, D. (2012) Advances in Spatio-Temporal Modeling and Prediction for Environmental Risk Assessment. In: Haryanto, B., Ed., Air Pollution—A Comprehensive Perspective, InTech, Croazia, 365-390. http://dx.doi.org/10.5772/51227

[16]   (1999) SPAD 4.0, Cisia, Montreuil Cedex, France.

[17]   Morineau, A. and Lebart, L. (1986) Specific Clustering Algorithms for Large Data Sets and Implementation in SPAD Software, in Classification as a Tool of Research. In: Gaul, W. and Schader, M., Eds., Classification as a Tool of Research: Proceedings of the 9th Annual Meeting of the Classification Society (F.R.G.), University of Karlsrube, F.R.G., North Holland, 321-329.