High-resolution monthly glacier surface velocity mapping in the Kangri Karpo region (2015–2024) using multi-source remote sensing data fusion

Abstract. To improve the accuracy and timeliness of glacier surface-velocity retrieval in complex mountain terrain, we develop a high-resolution fusion method combining Landsat, Sentinel-1/2, and UAV (Unmanned Aerial Vehicle) data, and produce monthly velocity products for the Kangri Karpo region for 2015–2024. Compared with existing large-area public datasets, the products offer markedly higher spatial resolution and better detection of small mountain glaciers; relative to single-sensor inputs prior to fusion, the valid-pixel ratio increases by ~50 %, the average number of valid months per pixel over the decade rises by ~50, and spatial smoothness improves—demonstrating the method’s suitability for rugged terrain. Spatially, velocities follow the canonical “fast center, slow margins” pattern, with multi-year maxima >700 m·yr⁻¹ and values in lower reaches and most tributaries generally