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Dasymetric Mapping for Estimating Population in Small Areas
Author(s) -
Mennis Jeremy
Publication year - 2009
Publication title -
geography compass
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 65
ISSN - 1749-8198
DOI - 10.1111/j.1749-8198.2009.00220.x
Subject(s) - thematic map , cartography , geography , ancillary data , population , interpolation (computer graphics) , data set , set (abstract data type) , computer science , remote sensing , artificial intelligence , image (mathematics) , demography , sociology , programming language
A dasymetric map depicts a statistical surface, most commonly population density, as a set of simply connected regions, such that variation within each region is minimized and the region boundaries approximate the steepest escarpments of the surface. Dasymetric mapping has its roots in early thematic mapping of population, but has recently been taken up by researchers focusing on areal interpolation and population estimation using remote sensing. The process of dasymetric mapping typically involves the disaggregation of population data encoded in choropleth map form using an ancillary spatial data set, most commonly either an area‐class map or satellite image. The functional relationship between the ancillary data and the statistical surface being mapped may be specified a priori by the researcher or estimated using a variety of statistical techniques. Challenges facing dasymetric mapping research include handling spatio‐temporal data and the development of standardized and accessible methods.