Abstract Geospatial analysis often treats data distributed over spherical surfaces, necessitating specialized statistical methods. Traditional planar Euclidean statistical tools, however, fail to accurately capture directional patterns inherent in such data, resulting in distortions or an oversimplification of directional patterns when applied to curved contexts. This paper introduces QSphericalStats, a QGIS plugin designed to perform robust spherical statistical analyses through the use of an accessible, user-friendly interface. By extending QGIS’s native geospatial capabilities, QSphericalStats enables the analysis of three-dimensional directional data, such as orientations derived from digital elevation models (DEMs). Two case studies were conducted to assess the plugin’s effectiveness in practical scenarios. The first compares LiDAR DEMs and ASTER GDEM datasets, demonstrating the tool’s accuracy in analyzing curved surface data; the second examines cartographic maps with associated 3D information, highlighting its ability to extract and interpret directional trends from complex geospatial datasets. Results from both studies show stable mean direction estimates and moderate concentration parameters, underscoring the plugin’s robustness and the added interpretative value of spherical statistics in geospatial research.
Cuartero et al. (Sun,) studied this question.