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Historical patterns of land-use development across many countries in the Global North have generally been characterised by land-use segregation, low-density settlements, and limited transport accessibility. This can lead to inefficient regional developmental patterns and can increase the environmental degradation attributable to regional expansion. Numerous metrics and datasets have been employed to infer the sustainability and efficiency of these developments. Here, we quantify and visualise the relative entropy of land-use configurations across the Republic of Ireland using a novel dataset. Specifically, we combine the discipline-standard CORINE Land Cover 2018 dataset and OpenStreetMap data, which provides more thorough land-use classifications in urban areas. Spatial differences in relative entropy are visualised using a spatial typology distinguishing between areas exhibiting low and high levels of relative entropy. Our Main Map visualises the coverage of both CORINE and OpenStreetMap datasets, compares relative entropy estimates for both datasets, and illustrates the disparities in cross-dataset estimates. [ABSTRACT FROM AUTHOR]

Population shrinkage has gained attention from academics and policymakers in recent years, due to the long-term implications the phenomenon has for public service delivery and the viability of urban and rural communities. We visualise the socio-temporal evolution of population shrinkage and growth, utilising a spatially rectified dataset containing population data from seven Census of Population covering the 1986–2016 period in the Republic of Ireland. Spatial changes in population distribution are visualised in a map that classifies small administrative units using a spatial typology distinguishing between those experiencing population growth or shrinkage, across the 30-year period. The temporal dimensions of these developments are considered in a sequence of inset maps that apply the same typology to identify the intercensal changes. Overall, the map facilitates the visual communication of long-run population trends, the identification of areas experiencing limited or no growth, and indicates the relative consistency of these trends over time. [ABSTRACT FROM AUTHOR]