Spatial depopulation risk assessment through spatial principal component analysis and indicator kriging in Castilla-La Mancha (Spain) - Hidalgo-Arellano, Isidro; Fernández-Avilés, Gema (Journal of rural studies, 2025)
Rural depopulation, which refers to a chronic decrease in the inhabitants of a rural area that affects the spatial distribution of the population, is an emerging issue that has entered the public policy agenda in recent years. Recent studies of rural depopulation have attempted to measure rural depopulation risk using depopulation or development indexes, but without considering a crucial dimension in this field: spatial dependence. The main objective of this paper is to include spatial dependence in the analysis using two novel approaches. First, we propose a spatial depopulation risk index (sDRI) for a large set of demographic and socio-economic variables using spatial principal component analysis. For this purpose, we use a geostatistical tool, the semivariogram, to determine the range of spatial dependence. Second, we provide a depopulation risk probability map (DRPM), showing the risk across the region as a whole, produced using Indicator Kriging. We apply these methods to the case of Castilla-La Mancha, a region of Spain in which vast areas have population densities lower than those of Siberia or Lapland, and which has been a pioneer in the implementation of laws and economic measures to combat rural depopulation. The results show that (i) accounting for spatial dependence in the design of the compound index provides a consistent classification of municipalities according to depopulation risk, and (ii) depopulation risk probability maps are suitable instruments for the identification of zones in which countermeasures can be applied. [Display omitted] •Spatial dependence is the keystone in the characterization of rural depopulation risk.•A dataset of 80 variables is used to analyze the structure, dynamics and spatial distribution of population in rural areas.•A Spatial Depopulation Risk Index is proposed using spatial principal component analysis.•Geostatistics through Indicator kriging provides a detailed Depopulation Risk Probability Map.•We provide valuable insights for rural policy-making and strategies to combat depopulation.