Page 37 - IJPS-11-2

International Journal of
Population Studies Satellite data analysis of South Africa population grid

Hachadoorian et al. (2011) argue that population Areas with sparse populations, marked by few inhabitants,
data are inherently spatial due to human habitation of are typically challenging to inhabit and are usually places
geographic areas. Population distribution refers to the with hostile environments, whereas densely populated
spatial arrangement of population dispersal, clustering, areas are more habitable. The particular scattering of the
and linear spread. Across most countries, significant population, agglomeration organization, and linear spread
regional variations exist in population distribution, leading determine the spatial structure and pattern (Chandna,
to differing population densities worldwide. 2009).

Getis & Ord (1996) and Getis & Paelinck (2004) assert Doignon et al. (2023) suggest that analyzing the spatial
that conventional statistical theory relies on general distribution of a population is an interdisciplinary exercise
models assuming independent observations. Hence, involving geography and demography. This analysis
spatial independence remains a relevant reference point occurs on various scales, encompassing both global
for detecting statistically significant non-independent and local perspectives, given the pronouncedly uneven
phenomena. Spatial statistics, as a field, is founded on distribution of populations nationally and worldwide.
the premise of observation non-independence, assuming These spatial disparities in population distribution
that neighboring units are somehow linked (Coetzee & constitute a crucial element in the functioning of societies,
Kleynhans, 2018). influencing their organization and future trajectory.
While the spatial distribution of a population offers a
Calka & Bielecka (2019) suggest that a comprehensive snapshot of societies at a particular moment, it also reflects
understanding of many earth surface phenomena and phenomena that characterize human temporal dynamics:
processes hinges on specific details regarding human the short-term lifespan of individuals and generations,
activity locations and characteristics. Consequently, there population dynamics, and the long-term endurance
is a growing emphasis on the challenge of obtaining reliable of societies. Furthermore, population distribution is a
population distribution data. Dong et al. (2017) highlight consequence of populations adapting, to varying degrees,
the increasing use of gridded population distribution to environmental constraints such as accessibility of
datasets, primarily due to their compatibility and ease of locations, available resources, and environmental quality,
integration with other spatial datasets. Leyk et al. (2019) thereby demonstrating their ability to exploit these factors
further observed that recent endeavors have resulted in the for settlement and habitation.
development of global and continental gridded population
datasets, which are gaining popularity across various Physical factors, attraction, constraints, and cultural
research communities. factors, in the main, account for the Earth’s population
characteristics and dynamics (Hornby & Jones, 1980).
This paper seeks to add to the discourse regarding the During economic development, social and political factors
reliability and precision of utilizing gridded population also play a role. Physical, social, demographic, economic,
images and datasets to estimate and illustrate the spatial political, and historical factors do not operate in isolation;
attributes and changes in the population, focusing on South instead, they affect each other. Thus, pinpointing the
Africa. Regarding the structure of the study, the next section influence of a single factor and deciphering the interplay
introduces the theoretical departure of population distribution between these factors is a complicated task (Clarke, 1972).
and spatial analysis. This is followed by a brief introduction
to gridded population statistics images and dataset, followed Several factors influence population characteristics and
by the testing for spatial concentration, autocorrelation, dynamics. These include the topography of the region—
and randomness, that is, spatial heterogeneity. Section 4.2 its soil, rivers, natural recourses, climate—whether it is
focuses on the trend surface analysis that uses the gridded landlocked or close to the sea, airports and harbors, and
population images and datasets. That indicates that higher- borders, as well as economic activity, culture, and religion.
order trend surfaces are indeed better than lower-order trend Related demographic factors include changes in natural
surfaces, that is, the population distribution in South Africa population growth and migration (Brush, 1968, Hugo,
is not linear. Based on the results obtained in the previous 2002, Small, 2003; and Liu et al., 2018). Adverse physical
two sections, spatial interpolation was performed and the conditions and a lack of enough opportunities to earn a
results are presented in section 4.3. The article culminates living also discourage people to live at particular locations.
with a summary and conclusions. Nevertheless, climatic conditions are probably the most
significant factor.
1.1. Literature review Duncan (1957) suggests several methods for analyzing
Population characteristics and dynamics encompass the and presenting the spatial characteristics and dynamics of
patterns and trends of human distribution across the earth. the population. A very simplified method is the percentage

Volume 11 Issue 2 (2025) 31 https://doi.org/10.36922/ijps.3297