Spatial reallocation of areal data – another look at basic methods
Do Van Huyen,
Christine Thomas-Agnan and
Anne Vanhems ()
Revue d'économie régionale et urbaine, 2015, vol. mai, issue 1, 27-58
Abstract:
The analysis of socio-economic data often implies the combination of databases originating from different administrative sources so that data have been collected on several separate partitions of the zone of interest into administrative units. It is therefore necessary to reallocate the data from the source spatial units to the target spatial units. We propose a review of the literature on the simplest statistical methods of spatial reallocation rules (spatial interpolation). We concentrate here on the areal-to-areal change of support case when initial and final data have an areal support with a particular attention to disaggregation for numerical data. There are three main types of such techniques: proportional weighting schemes also called dasymetric methods, smoothing techniques and regression based interpolation. We propose a unified formalization of the basic techniques with a synoptic table and extensions of some of these methods to new cases.
Keywords: areal interpolation; change of support; polygon overlay problem; pycnophylactic property; spatial disaggregation (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.cairn.info/load_pdf.php?ID_ARTICLE=RERU_151_0027 (application/pdf)
http://www.cairn.info/revue-d-economie-regionale-et-urbaine-2015-1-page-27.htm (text/html)
free
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cai:rerarc:reru_151_0027
Access Statistics for this article
More articles in Revue d'économie régionale et urbaine from Armand Colin
Bibliographic data for series maintained by Jean-Baptiste de Vathaire ().