APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Arnobio Germán Poblete, Juan Leonidas Minetti, María José Vera
Format: Article
Language:English
Published: Universidad Nacional del Comahue;Facultad de Humanidades; Departamento de Geografía, 2017-12-01
Series:Boletín Geográfico
Subjects:
Online Access:http://revele.uncoma.edu.ar/htdoc/revele/index.php/geografia/article/view/1753/1787
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832569357355450368
author Arnobio Germán Poblete
Juan Leonidas Minetti
María José Vera
author_facet Arnobio Germán Poblete
Juan Leonidas Minetti
María José Vera
author_sort Arnobio Germán Poblete
collection DOAJ
description 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.
format Article
id doaj-art-cb0d355edd3343269a48e6dd38a46cbc
institution Kabale University
issn 0326-1735
2313-903X
language English
publishDate 2017-12-01
publisher Universidad Nacional del Comahue;Facultad de Humanidades; Departamento de Geografía,
record_format Article
series Boletín Geográfico
spelling doaj-art-cb0d355edd3343269a48e6dd38a46cbc2025-02-02T22:19:27ZengUniversidad Nacional del Comahue;Facultad de Humanidades; Departamento de Geografía,Boletín Geográfico0326-17352313-903X2017-12-01393552APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICASArnobio Germán Poblete0Juan Leonidas Minetti1María José Vera2Instituto de Geografía aplicada de la UNSJ. - San Juan. Argentina. e-mail: agpoblete@gmail.com Universidad Nacional de Tucumán- CONICET- S.M. de Tucumán e-mail: minettil@arnet.com.arUniversidad Nacional de San Juan. San Juan. Argentina. e-mail: mariajosevera@gmail.comThis 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.http://revele.uncoma.edu.ar/htdoc/revele/index.php/geografia/article/view/1753/1787Factorial analysisprecipitationspatial- temporal discrimination
spellingShingle Arnobio Germán Poblete
Juan Leonidas Minetti
María José Vera
APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS
Boletín Geográfico
Factorial analysis
precipitation
spatial- temporal discrimination
title APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS
title_full APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS
title_fullStr APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS
title_full_unstemmed APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS
title_short APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS
title_sort aplicacion del analisis factorial para discriminar espacialmente variables geograficas
topic Factorial analysis
precipitation
spatial- temporal discrimination
url http://revele.uncoma.edu.ar/htdoc/revele/index.php/geografia/article/view/1753/1787
work_keys_str_mv AT arnobiogermanpoblete aplicaciondelanalisisfactorialparadiscriminarespacialmentevariablesgeograficas
AT juanleonidasminetti aplicaciondelanalisisfactorialparadiscriminarespacialmentevariablesgeograficas
AT mariajosevera aplicaciondelanalisisfactorialparadiscriminarespacialmentevariablesgeograficas