The formation and development of glaciers depend on a combination of topographic conditions and climatic factors, such as precipitation and temperature. However, the mechanisms underlying glacier distribution and variation remain uncertain. Our study aims to explore the relationship between glacier distribution patterns and topographical factors and uncover the driving forces behind them. To accomplish this, we utilized the Randolph Glacier Inventory version 6 and NASADEM for our analysis. Initially, we derived four key topographical factors based on NASADEM: relief degree of land surface (RDLS), altitude, slope, and aspect. Because the calculation of RDLS has scale dependence, the key is to determine the optimal analysis window using the average change-point analysis approach. The identified optimal analysis window size for RDLS evaluation in the study area was a rectangular neighborhood of 36 × 36 pixels, corresponding to an area of approximately 1.17 km². Subsequently, we examined glacier distribution patterns across various terrains in the Tibetan Plateau using the distribution index. This index elucidates the disparities between actual and standard glacier distributions across various mountain chains, excluding area disturbances. Finally, we employed the geodetector method to quantitatively assess the spatial interplay between glacier distribution patterns and topographical elements. This innovative statistical approach identifies spatially stratified heterogeneity, pinpoints explanatory factors, and evaluates interactive relationships between variables. The results show that: (1) Glacier distribution in the Tibetan Plateau shows strong selectivity for RDLS and altitude, with wide suitability for aspect and slope. The predominant distribution involves large RDLS and high altitudes. (2) Topography significantly influences glacier development, with varied effects of topographic factors on the spatial distribution of glaciers. Altitude and RDLS emerged as dominant factors controlling the distribution of glaciers, followed by slope and aspect. The interactive detection revealed that the combined effect of altitude and RDLS had a dominant impact on spatially stratified glacier heterogeneity. (3) Among altitude and RDLS gradients, the Himalayas Mountains had the most extensive glacier distribution, followed by the Karakoram Mountains. The other ten mountain ranges demonstrated diverse glacier distributions, though they mostly adhered to a normal pattern. This study will serve as a theoretical reference and provide data support for regional hydrology research. It offers vital guidance for appropriate water resource management in arid lands.