Abstract
Population density varies sharply from place to place on the whole territory of
Poland. The largest number of people per 1 km2 is 21,531, while uninhabited areas account
for about 48% of the country. Such uneven, non-Gaussian distribution of the data causes
some difficulty in choosing the classification method in geometric choropleth maps. A thorough
evaluation of a geometric choropleth map of population data is not possible using
only traditional indicators such as the Tabular Accuracy Index (TAI). That is why the aim
of the article is to develop an innovative index based on distance analysis and neighbour
analysis of grid cells. Two indexes have been suggested in this paper: the Spatial Distance
Index (SDI) and the Spatial Contiguity Index (SCI). The paper discusses the use of five
classification methods to evaluate choropleth maps of population data, like head-tail breaks,
natural breaks, equal intervals, quantile, and geometrical intervals. A comprehensive assessment
of such geometric choropleth maps is also done. The research was conducted for
the whole territory of Poland, using data from the 2011 National Census of Population and
Housing. Population data are presented in the 1km grid. The results of the analysis are
shown on thematic maps. A compatibility of the choropleth maps with urban-rural typology
of the OECD (Organisation for Economic Co-operation and Development) was also
checked.
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