Application of the factorial analysis to specially Discriminate geographic variables

Authors

  • Arnobio Germán Poblete Instituto de Geografía aplicada de la UNSJ
  • Juan L Minetti Universidad Nacional de Tucumán- CONICET- S.M. de Tucumán
  • María José Vera Universidad Nacional de San Juan

Keywords:

Factorial analysis, precipitation, spatial-temporal discrimination

Abstract

This work aims to show the effectiveness of Factor Analysis in geographic research, explaining how to discriminate spatially to any geographic variable, which in this case; Is the precipitation in the Argentine Republic and Chile, taking into account its interannual variability, This task was carried out applying this multivariate methodology, given its recognized validity to find the underlying
structures in a high number of variables.
The spatial discrimination of a variable is important to analyze the processes involved, taking into account homogeneous areas from the point of view of its geographical distribution and its genesis, Understanding the behavior of such uniform areas, the geographer can perform an adequate planning of that scenario.
The additional purpose of this investigation is to provide a contribution to the understanding of the regime of the interannual variability of rainfall in the Argentinean and Chilean territory analyzed from a sandy point of view. With the application of this methodology, eight domains with spatial uniformity were identified in the variability of the mean annual precipitation, from the same number of factors, which explain 61% of the variance. The criterion adopted in the definitive retention of these eight factors is that they follow a pattern of territorial homogeneity, since they condense with enough spatial discrimination the information contained in the ninety-five original variables.

Downloads

Download data is not yet available.

References

Almeira, G., Ciappesoni, H. y Goniadzki D. (2009) Algunos aspectos de la precipitación regionalizada en el centro-norte de Argentina. Preprint Congremet, Buenos Aires, Argentina.

Barros, V., Moyra. (1996). Precipitation trends in Southern America to the East of the Andes, Centre of Ocean Land Atmospheric Studies, COLA, MD, Report No26. Proceeding of the Workshops of Dynamics on Statistical of Secular Climate

Variations, 76-80.

Bruniard, E. (1989) NA ́ ALHUA, Instituto de Geografía, UNNE- Chaco.

Chan, S., Behera, S., & Yamagata, T. (2008). Indian Ocean Dipole influence on South American rainfall. Geophysical Research Letters, 35(14). Retomado de:

http://dx.doi.org/10.1029/2008gl034204

Grupo Chadule: " Métodos estadísticos en Geografía", Ed, El Cano, 1000, Madrid

Hoffman, José A. (1989). Las variaciones climáticas ocurridas en la Argentina desde fines del siglo pasado hasta el presente. El Deterioro del Ambiente en la Argentina. Divulgación No 15 del Servicio Meteorológico Nacional. FECIC, Bs.As. http://dx.doi.org/10.1175/1520-0442(2000)013<1000:amitec>2.0.co;2

Jennrich, R., & Robinson, S. (1969). A Newton-Raphson algorithm formaximum likelihood factoanalysis. Psychometrika, 34(1), 111-123. http://dx.doi.org/10.1007/bf02290176

Joereskog K,G. (1976) Factor analysis by least-squares and maximum-likelihood methods. Statistical Methods for Digital Computers. p125-153. Eds. In Enslein, K,, Ralston, A, and Wilf, H,S. Wiley.

Johnson, R., & Wichern, D. (1988). Applied multivariate statistical analysis. Englewood Cliffs, New Jersey: Prentice-Hall.

Minetti, J,L, y W. Vargas. (1998). Trends and jumps in the annual precipitation in South America, south of the 15oS. Atmósfera 11, No4, 205-223, México.

Morrison, D. (1982). Multivariate statistical methods. New York, (etc): Mac Graw-Hill.

Poblete, A. G. y Bertol E. (2001). Variabilidad internanual del derrame anual del río San Juan, IGA Revista de Geografía, No: 5. Instituto y Departamento de Geografía, FFHA-UNSJ. San Juan, Argentina.

Poblete, A. G., Minetti, J, L. (2003). Asociación entre cuantificadores del ENSO e índices de circulación atmosférica regional con el derrame del río San Juan. IGA Revista de Geografía, Vol,:7 año 6, Páginas 26-33. Instituto y Departamento de Geografía, FFHA-UNSJ. San Juan, Argentina.

Poblete, A. G., Minetti, J.L, Sánchez, G. DEL V. (2001). Análisis de la variabilidad interanual de los ríos andinos de Cuyo y del Comahue con métodos multivariantes. Libro electrónico del IX Congreso Latinoamericano e Ibérico de

Meteorología y VIII Congreso Argentino de Meteorólogos. Buenos Aires, Reboita, M., Ambrizzi, T., & Rocha, R. (2009). Relationship between the southern annular mode and southern hemisphere atmospheric systems. Revista Brasileira De Meteorologia, 24(1), 48-55.

Saji, N., Goswami, B., Vinayachandran, P., & Yamagata, T. (1999). A dipole mode in the tropical Indian Ocean. Nature, 401(6751), 360-363: http://dx.doi.org/10.1038/43854

Silvestri, G. (2003). Antarctic Oscillation signal on precipitation anomalies over southeastern South America. Geophysical Research Letters, 30(21).: http://dx.doi.org/10.1029/2003gl018277

Tatsouda M.N. (1971). Multivariate Analysis, Wiley, New York. Thompson, D., & Wallace, J. (2000). Annular Modes in the Extratropical Circulation. Part I: Month-to-Month Variability*. Journal Of Climate, 13(5), 1000-1016.

Published

2017-12-21

How to Cite

Poblete, A. G., Minetti, J. L., & Vera, M. J. (2017). Application of the factorial analysis to specially Discriminate geographic variables. Boletín Geográfico, (39), 35–52. Retrieved from https://revele.uncoma.edu.ar/index.php/geografia/article/view/1753

Issue

Section

Geography and Climatology

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.