A Bivariate Dasymetric Population Map of Saudi Arabia

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.