Objectives Terrain relief is a crucial indicator for quantifying topographic features and describing regional landforms. The application of the mean change point method to determine the optimal analysis window is of significant importance for extracting terrain relief and conducting regional landform analysis.

Methods The study selected the Altai-Kanas potential area, which exhibited significant topographic relief and the Kalameili potential area, which featured relatively flat terrain and small relief as the research areas. The study employed widely DEM data with spatial resolutions of 30m and 90m were employed as the base data. The optimal analysis window was determined through the application of the mean change point method, with consideration given to the landform features and the classification results of terrain relief in the two study areas.

Results The results demonstrated that: (1) The optimal analysis window area exhibited a larger overall area when a 90m spatial resolution DEM was employed, as compared to a 30m spatial resolution, with an average area growth rate of 22.66%. Meanwhile, as the area range increased, the optimal analysis window also increased in accordance with this expansion. However, the discrepancy in the optimal analysis window between the two study areas was not significant under the same area range. (2) By integrating terrain relief classification data and layers, a 60×60 (3.2400 km²) window was identified as the optimal terrain relief analysis window for the Altai-Kanas potential area using 30m spatial resolution base data, while a 17×17 (2.3409 km²) window was determined as the optimal terrain relief analysis window for the Kalameili potential area using 90m spatial resolution base data.

Conclusion In the process of studying terrain relief, regions with different landform characteristics exhibit variations in the suitable spatial resolution of base DEM data and optimal windows. Areas with gentle terrain relief may use DEM data with lower spatial resolution and smaller analysis windows, while areas with significant relief should employ DEM data with higher spatial resolution and larger analysis windows.