Application of the factorial analysis to specially Discriminate geographic variables
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 carrie...
Guardado en:
| Autores principales: | , , |
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| Formato: | Artículo revista |
| Lenguaje: | Español |
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Facultad de Humanidades Universidad Nacional del Comahue
2017
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| Acceso en línea: | http://revele.uncoma.edu.ar/index.php/geografia/article/view/1753 |
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| Sumario: | 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 underlyingstructures 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. |
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