Spatial patterns and environmental suitability of traditional Tibetan villages in Ganzi Tibetan Autonomous Prefecture, China

The acceleration of global urbanization and industrialization since the 20th century has drawn increasing attention to the quality of human settlements. Ganzi Tibetan Autonomous Prefecture, located on the southeastern Tibetan Plateau, is characterized by rugged terrain, fragile ecosystems, and cultural diversity. Its traditional villages exhibit strong adaptation to local environmental conditions in site selection, spatial configuration, and construction practices; however, rapid modernization and environmental change have increasingly affected their spatial distribution and living conditions. In this study, 274 traditional villages listed by the Ministry of Housing and Urban-Rural Development and the Sichuan Provincial Government were selected as research samples. An integrated framework combining spatial pattern analysis, environmental suitability assessment, and factor detection analysis was applied. ArcGIS spatial analysis, multi-index evaluation, and the GeoDetector model were employed to examine spatial distribution patterns, environmental suitability, and associated factors. The results indicate that traditional villages in Ganzi are significantly clustered, forming a “two cores–multiple scattered points” pattern, primarily concentrated in Danba and Litang. Clear inter-county disparities are observed, showing a general “south-dense and north-sparse” tendency. Most villages are located in unsuitable, critical, or low-suitability zones, accounting for 63.60% of the total sample. GeoDetector results indicate that the Temperature–Humidity Index shows the strongest individual association with village clustering intensity, while the interaction between the Temperature–Humidity Index and Water Resources Index exhibits the highest explanatory power (q = 0.518). The Land Cover Index shows no statistically significant association (q = 0.035, p = 0.214). These findings are robust under different weighting scenarios with ± 20% parameter perturbation. This study provides empirical evidence on the spatial patterns of traditional Tibetan villages and their relationships with environmental conditions in a high-altitude region.