Abstract ID: 3.12238 | Accepted as Poster | Poster | TBA | TBA

Socioeconomic variables are essential for assessing and monitoring the interactions between human populations and the unique environmental conditions of mountain regions. Understanding socioeconomic changes in these areas requires a comprehensive set of essential socioeconomic variables (ESVs), and visualizing these variables is crucial for identifying future trends and developing targeted policies. Nonetheless, mapping these variables in mountain regions presents distinct challenges, particularly in data sourcing, processing, and visualization, leading to inconsistencies in availability and comparability, especially in transboundary regions where socioeconomic variables may be measured differently. To overcome the frequent unavailability, outdated nature, or incompleteness of census data, particularly in mountain regions of the Global South, we identified Gridded Population Datasets (GPDs) such as WorldPop as valuable alternatives for mapping population distribution and related indicators (e.g. access to essential services). We tested our methodology in the EUREGIO regions of Tirol, South Tyrol, and Trentino, a data-rich region, combining GPDs with GIS techniques to map ESVs. Specifically, our study integrates GPDs with road network data, facilitating spatial analyses that identify disparities in service access. We applied this methodology to develop a healthcare access matrix by combining spatial population data with road network distances to determine travel distances from residences to healthcare facilities. This approach identified high-population areas with limited healthcare access, highlighting regions most in need of intervention. An advantage of this methodology is its replicability for other ESVs, like education, employment opportunities, and infrastructure access. This approach provides valuable insights into socioeconomic dynamics, particularly in data-poor regions. This research highlights the need for standardized methodologies to ensure meaningful cross-regional comparisons of ESVs while enabling better visualization of indicators to identify vulnerable populations and support evidence-based decision-making. In mountain areas, where remoteness and topography influence service accessibility, GIS-based visualization offer a powerful tool for assessing socioeconomic vulnerability. By applying GPDs and spatial analysis, this research demonstrates an approach for visualizing and addressing socioeconomic challenges in mountain areas worldwide.