Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru
Descripción del Articulo
The Peruvian provinces were tipified by factorial methods with incorporating geo-referenced data with information from the 2012 National Agricultural Census. Were determined three indicators : Intensity of agricultural activity, commercialization of agricultural production, and use of water sources...
| Autores: | , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2016 |
| Institución: | Universidad Nacional Mayor de San Marcos |
| Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
| Lenguaje: | español |
| OAI Identifier: | oai:ojs.csi.unmsm:article/12672 |
| Enlace del recurso: | https://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/12672 |
| Nivel de acceso: | acceso abierto |
| Materia: | Exploratory spatial data analysis Moran index factorial methods spatial analysis agricultural census. Análisis exploratorio de datos espaciales índice de Moran métodos factoriales análisis espacial censo agropecuario. |
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Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of PeruMétodos Factoriales en el Análisis de Datos Espaciales. Una Aplicación a los Datos del Censo Agropecuario 2012 para la Caracterización de las Provincias del PerúCambillo Moyano, Emma NormaAgüero Palacios, Ysela DomingaAlvarez Rivas, María del PilarRiojas Cañari, Alicia CirilaExploratory spatial data analysisMoran indexfactorial methodsspatial analysisagricultural census.Análisis exploratorio de datos espacialesíndice de Moranmétodos factorialesanálisis espacialcenso agropecuario.The Peruvian provinces were tipified by factorial methods with incorporating geo-referenced data with information from the 2012 National Agricultural Census. Were determined three indicators : Intensity of agricultural activity, commercialization of agricultural production, and use of water sources for irrigation; The use of the Moran Index helped identify provinces with similar agricultural characteristics. The results could be used to route some objectives of the strategic plan of the agricultural sector, and monitor policies of institutional development in the sector. The informatión also could be useful for designing development plans that meet the needs of the agricultural sector and to have a clear idea of the agricultural characteristics of all the provinces of Peru, with the object to orient the investment in the country.Las provincias peruanas fueron tipificadas por métodos factoriales con la incorporación de datos georreferenciados con información del Censo Nacional Agropecuario de 2012. Se determinaron tres indicadores: La intensidad de la actividad agrícola, la comercialización de la producción agrícola, y el uso de fuentes de agua para el riego; El uso del Índice de Moran ayudó a identificar las provincias con características agrícolas similares. Los resultados podrían ser utilizados para encaminar algunos objetivos del plan estratégico del sector agrícola, y supervisar las políticas de desarrollo institucional en el sector. La información también podría ser útil para el diseño de planes de desarrollo que respondan a las necesidades del sector agrícola y para tener una idea clara de las características agrícolas de todas las provincias del Perú, con el objeto de orientar la inversión en el paísUniversidad Nacional Mayor de San Marcos, Facultad de Ciencias Matemáticas2016-11-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/1267210.15381/pes.v19i2.12672Pesquimat; Vol. 19 No. 2 (2016)Pesquimat; Vol. 19 Núm. 2 (2016)1609-84391560-912X10.15381/pes.v19i2reponame:Revistas - Universidad Nacional Mayor de San Marcosinstname:Universidad Nacional Mayor de San Marcosinstacron:UNMSMspahttps://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/12672/11324Derechos de autor 2016 Emma Norma Cambillo Moyano, Ysela Dominga Agüero Palacios, María del Pilar Alvarez Rivas, Alicia Cirila Riojas Cañarihttps://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessoai:ojs.csi.unmsm:article/126722016-11-23T13:48:02Z |
| dc.title.none.fl_str_mv |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru Métodos Factoriales en el Análisis de Datos Espaciales. Una Aplicación a los Datos del Censo Agropecuario 2012 para la Caracterización de las Provincias del Perú |
| title |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru |
| spellingShingle |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru Cambillo Moyano, Emma Norma Exploratory spatial data analysis Moran index factorial methods spatial analysis agricultural census. Análisis exploratorio de datos espaciales índice de Moran métodos factoriales análisis espacial censo agropecuario. |
| title_short |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru |
| title_full |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru |
| title_fullStr |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru |
| title_full_unstemmed |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru |
| title_sort |
Factorial methods in the analysis of spatial data. An application to the 2012 agricultural census data for the characterization of the provinces of Peru |
| dc.creator.none.fl_str_mv |
Cambillo Moyano, Emma Norma Agüero Palacios, Ysela Dominga Alvarez Rivas, María del Pilar Riojas Cañari, Alicia Cirila |
| author |
Cambillo Moyano, Emma Norma |
| author_facet |
Cambillo Moyano, Emma Norma Agüero Palacios, Ysela Dominga Alvarez Rivas, María del Pilar Riojas Cañari, Alicia Cirila |
| author_role |
author |
| author2 |
Agüero Palacios, Ysela Dominga Alvarez Rivas, María del Pilar Riojas Cañari, Alicia Cirila |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
Exploratory spatial data analysis Moran index factorial methods spatial analysis agricultural census. Análisis exploratorio de datos espaciales índice de Moran métodos factoriales análisis espacial censo agropecuario. |
| topic |
Exploratory spatial data analysis Moran index factorial methods spatial analysis agricultural census. Análisis exploratorio de datos espaciales índice de Moran métodos factoriales análisis espacial censo agropecuario. |
| description |
The Peruvian provinces were tipified by factorial methods with incorporating geo-referenced data with information from the 2012 National Agricultural Census. Were determined three indicators : Intensity of agricultural activity, commercialization of agricultural production, and use of water sources for irrigation; The use of the Moran Index helped identify provinces with similar agricultural characteristics. The results could be used to route some objectives of the strategic plan of the agricultural sector, and monitor policies of institutional development in the sector. The informatión also could be useful for designing development plans that meet the needs of the agricultural sector and to have a clear idea of the agricultural characteristics of all the provinces of Peru, with the object to orient the investment in the country. |
| publishDate |
2016 |
| dc.date.none.fl_str_mv |
2016-11-18 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/12672 10.15381/pes.v19i2.12672 |
| url |
https://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/12672 |
| identifier_str_mv |
10.15381/pes.v19i2.12672 |
| dc.language.none.fl_str_mv |
spa |
| language |
spa |
| dc.relation.none.fl_str_mv |
https://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/12672/11324 |
| dc.rights.none.fl_str_mv |
https://creativecommons.org/licenses/by-nc-sa/4.0 info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by-nc-sa/4.0 |
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openAccess |
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application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Matemáticas |
| publisher.none.fl_str_mv |
Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Matemáticas |
| dc.source.none.fl_str_mv |
Pesquimat; Vol. 19 No. 2 (2016) Pesquimat; Vol. 19 Núm. 2 (2016) 1609-8439 1560-912X 10.15381/pes.v19i2 reponame:Revistas - Universidad Nacional Mayor de San Marcos instname:Universidad Nacional Mayor de San Marcos instacron:UNMSM |
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Universidad Nacional Mayor de San Marcos |
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UNMSM |
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Revistas - Universidad Nacional Mayor de San Marcos |
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Revistas - Universidad Nacional Mayor de San Marcos |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
