Combining multivariate statistical analysis with geographic information systems mapping: a tool for delineating groundwater contamination

El trabajo presenta una metodología que permite la identificación de zonas de vulnerabilidad agrícola por sequía meteorológica en el Estado México; la propuesta utiliza de técnicas de evaluación multivariada, sistemas de información geográfica, estandarización y análisis estadístico. El proceso de validación metodológica se desarrolló en el territorio que comprende al Estado de México en donde se seleccionaron y aplicaron indicadores sugeridos por la guía metodológica del INECC y PNUD; asimismo se llevó a cabo el análisis por superposición temática de variables para procesar la información. Como resultado, se construyó cartografía del escenario correspondiente a exposición, sensibilidad, resiliencia y vulnerabilidad agrícola para el Estado de México y sus municipios. Palabras clave: vulnerabilidad; evaluación multivariada; sistemas de información geográfica; resiliencia; sequía. This paper presents a methodology that allows the identification of agricultural zones vulnerability due to meteorological drought in Mexico. The proposal uses multivariate evaluation techniques, Geographic Information Systems (GIS), standardization and statistical analysis. The methodological validation process was developed and approved in the State of Mexico territory, where indicators suggested by methodological guide of the INECC and UNPN were select and applied. Also the analysis by thematic overload of variables to process the information was carried out. As result, exposure mapping, sensitivity, resilience and agricultural vulnerability were developed. Index words: vulnerability; multivariate evaluation; GIS; resilience; drought.

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The modifiable areal unit problem (MAUP) in physical geography

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133307083294 ◽

2007 ◽

Vol 31 (5) ◽

pp. 471-479 ◽

Cited By ~ 146

Author(s):

Shawna J. Dark ◽

Danielle Bram

Keyword(s):

Remote Sensing ◽

Information Systems ◽

Statistical Analysis ◽

Geographic Information Systems ◽

Large Scale ◽

Geographic Information ◽

Physical Geography ◽

Modifiable Areal Unit Problem ◽

Areal Unit ◽

Quantitative Studies

Of particular importance to the study of large-scale phenomena in physical geography is the modifiable areal unit problem ( MAUP). While often viewed as only a problem in human geography (particularly demographic studies), the MAUP is an issue for all quantitative studies in geography of spatial phenomena (Openshaw and Taylor, 1979). Increasingly, remote sensing and Geographic Information Systems ( GIS) are being used to assess the distribution of phenomena from a large scale. These phenomena are modelled using areal units that can take any shape or size resulting in complications with statistical analysis related to both the scale and method used to create the areal units. In this paper, we define the modifiable areal unit problem, present examples of when it is a problem in physical geography studies, and review some potential solutions to the problem. Our aim is to increase awareness of this complicated issue and to promote further discussion and interest in this topic.

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