GIS-based Dasymetric mapping method to increase the accuracy of estimating population density

Abstract EN

Precise population information is critical for the purposes of planning and decision-making.

There are different techniques for estimating the spatial distribution of populations such as dot maps, choropleth maps and dasymetric mapping.

This study compared the choropleth versus dasymetric mapping techniques to improve the accuracy of mapping estimated population density.

While the choropleth approach uses the linear distribution of population density over an area based on census tract units, dasymetric maps account for geographic properties by incorporating ancillary data sets, such as land-use data, and extensively partitioning space into zones to increase the spatial resolution of the mapped population data.

Land-use/ land cover data derived from remotely sensed satellite imagery were used to determine the areal extent of populated areas, which in turn served as the denominator for dasymetric population density computations at the census tract level.

Dasymetric mapping provided a more accurate approach to estimate and characterize population densities in urban areas and the spatial distribution of population within administrative areas, yielding more precise population density estimates than the choropleth method, while graphically representing the geographic distribution of populations.

The study recommends that more studies are conducted to estimate the population density in different regions, especially in informal settlements.