Abstract
The issue of population dataset reliability is of particular importance when it comes to broadening the understanding of spatial structure, pattern and configuration of humans’ geographical location. The aim of the paper was to estimate the reliability of LandScan based on the official Polish Population Grid. The adopted methodology was based on the change detection approach, spatial pattern and continuity analysis, as well as statistical analysis at the grid-cell level. Our results show that the LandScan data can estimate the Polish population very well. The number of grid cells with equal people counts in both datasets amounts to 10.5%. The most and highly reliable data cover 72% of the country territory, while less reliable ones cover only 4.3%. The LandScan algorithm tends to underestimate people counts, with a total value of 79,735 people (0.21%). The highest underestimation was noticed in densely populated areas as well as in the transition areas between urban and rural, while overestimation was observed in moderately populated regions, along main roads and in city centres. The underestimation results mainly from the spatial pattern and size of Polish rural settlements, namely a big number of shadowed single households dispersed over agricultural areas and in the vicinity of forests. An excessive assessment of the number of people may be a consequence of the well-known blooming effect.
Highlights
A better understanding of many phenomena and processes related to the Earth’s surface requires information on the locations and characteristics of humans
The official providers of population data are national census agencies. They give the most reliable and the most complete information on population distribution related to pre-defined units, the size of which depends on the country and population density
The objective of this paper was to estimate the comprehensive, cell-based reliability of LandScan data using the set of metrics, setting up the criteria of reliable data, and to portray spatial distribution of reliability classes in a user-friendly and efficient way
Summary
A better understanding of many phenomena and processes related to the Earth’s surface requires information on the locations and characteristics of humans. The official providers of population data are national census agencies. They give the most reliable and the most complete information on population distribution related to pre-defined units, the size of which depends on the country and population density. In many geographical regions, those of irregular and dispersed population distribution, statistical data aggregated to administrative units’ gives an unrealistic view of the location of humans. This problem has been noticed by scientists as early as the beginning of the 20th century. The Russian cartographer Tian-Shansky coined the term ‘dasymetric mapping’ and elaborated the first dasymetric population density map of European Russia, scale 1:420,000, published in the 1920s [3]
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