TITLE:
A Bivariate Dasymetric Population Map of Saudi Arabia
AUTHORS:
Mohsen Dhieb
KEYWORDS:
Dasymetric Map, Bivariate Method, GIS, Saudi Arabia, Population Distribution, Land Use Classification
JOURNAL NAME:
Current Urban Studies,
Vol.10 No.4,
December
23,
2022
ABSTRACT: The dasymetric method is used
to portray accurately phenomena such as densities of population over one space.
In general, this method is preferred to the classical choropleth one since it
yields more accurate results, especially when the mapped space is characterized
by its inner heterogeneity and therefore reflects what Langford called “spatial
specialization”. Now, many topics dealing with space such as planning, site
selection, or spatial risk and hazard studies require accurate and real
population location since most issued spatial choices or decisions may impact
the population, and the dasymetric method may help. Since KSA is a huge country
characterized by a high percentage of a few inhabited population entities
crowded in small areas as opposed to wide empty or almost empty deserts or
rural spaces, and to embrace its overall territory in a glance, we used the
bivariate method on the scale of 1 to 2 million. Scarce highly populated urban
poles appear opposed to very large portions of the remaining territory
characterized by scarce or null densities. Besides a classical choropleth map,
a dasymetric map was drawn to portray the highly contrasted distribution of
population in the Kingdom of Saudi Arabia (KSA). It distinguishes two highly
contrasted classes of densities. The
overall objective is to achieve small-scale vector population maps (1 to
2 million) departing from the smallest administrative count unities, i.e.,
the governorates (locally called mouhafadhat). Besides population data,
the Saudi Topographic map, Open Street map and Saudi Basemap were utilized to
delimitate the land use classes, according to the scale. Population data was
integrated in a dedicated GIS which allows calculations of areas and densities
of the issued spatial units. The resulting bivariate dasymetric maps may
constitute useful tools to help geographers and planners in understanding the
population distributions forms and factors. This way, decision-makers may
implement further spatial measures and various projects particularly when
taking into consideration their effects on population.