The dasymetric method for mapping population

Show simple item record Krahnen, Anne Siemer, Julia 2011-04-21T22:21:05Z 2011-04-21T22:21:05Z 2011-04-02
dc.description.abstract This poster introduces basic concepts, methods and ideas of the dasymetric method. Today’s society relies upon maps as a common and effective way of communication. Population distribution and density are frequently displayed phenomena. Currently, the choropleth method is most commonly applied to map population. This method displays statistical data as densities for enumeration units and is most appropriate for phenomena that occur equally throughout a region (e.g., tax rates). However, its application to phenomena whose real distribution is not reflected by the boundaries of administrative areas (e.g., population) is inadequate. A less established method avoiding these problems is the dasymetric method. This method is visualizing statistical surfaces displaying phenomena and variables varying continuously over space. Cartographers discovered a relationship between the occurrence of population and additional, so-called ancillary data. Dasymetric mapping is the method used to define this logical relationship between ancillary data and census population data. Irregularities such as peak values and local variations are shown on dasymetric maps. The dasymetric method has not been standardized yet. A generally accepted valid relationship between ancillary data and a statistical surface still is to be defined. Thus, research focuses on the definition of methods that precisely redistribute census data to exclusively populated areas and determine their population density. en_US
dc.language.iso en en_US
dc.publisher University of Regina Graduate Students' Association en_US
dc.relation.ispartofseries Posters and Exhibits en_US
dc.subject Cartography en_US
dc.subject Mapping population en_US
dc.subject Dasymetric mapping en_US
dc.title The dasymetric method for mapping population en_US
dc.type Presentation en_US
dc.description.authorstatus Student en_US
dc.description.peerreview yes en_US

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