The Landsat 8 satellite was launched in February 2013, carrying two key sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). These sensors maintain the same spatial resolution, coverage, and spectral range as their predecessor, Landsat 7, but feature optimized spectral bandwidths for certain bands, particularly Band 5 and Band 8 of the OLI sensor. This study utilizes Landsat 8 imagery from Band 8 (panchromatic band) covering the High Mountain Asia region during the period 2014–2021. With a spatial resolution of 15 meters, the Band 8 imagery enables precise measurement of surface displacements on mountain glaciers. To minimize the effects of cloud cover and snow reflectance, only cloud-free and low-snow imagery from the study area was selected. Glacier surface velocity data were extracted using an optical image cross-correlation algorithm. For this study, individual glaciers served as the unit of analysis, and cloud-free imagery was identified using an optical image albedo-based cloud removal algorithm. In total, 101,827 images were selected for glacier velocity extraction, covering all cloud-free imagery over glaciers larger than 10 km² in the High Mountain Asia region between 2014 and 2021.

(1) In this study, individual glaciers were used as units of analysis. A total of 101,827 cloud-free images suitable for extracting glacier velocity were selected using an albedo-based cloud removal algorithm on the Google Earth Engine (GEE) platform. These images covered all cloud-free scenes over glaciers larger than 10 km² in High Mountain Asia from 2014 to 2021.

(2) The east-west displacement, north-south displacement, and signal-to-noise ratio (SNR) of glaciers were calculated using the COSI-Corr plugin in ENVI.

(3) Cloud-free areas, snow-free areas, and bare ground pixels in non-glacier terrains were identified in each image. Feature matching was conducted for bare ground pixels between paired images, and the north-south and east-west displacements of bare ground pixels were calculated as the matching error between the two images. These errors were subsequently removed from the displacement results derived from each image pair.

(4) Based on the above steps, this study employed the GLAFT to assess the uncertainty in glacier velocity. This method estimates glacier surface velocity uncertainty by measuring the displacement of static ground, with the core assumption that adjacent non-glacier areas are static, with no horizontal or vertical displacement. This implies that any displacement observed in non-glacier areas represents measurement error. Glacier, snow-covered, and cloud-covered regions were excluded from the remote sensing imagery, leaving only exposed bare ground. Under the condition of retaining exposed bare ground, GLAFT distinguished between correct and incorrect feature matching points on the bare ground during the calculation of displacement errors. Subsequently, the uncertainty of glacier velocity was estimated from the correct feature matching points on bare ground. Ideally, the uncertainty calculated from the correct bare ground matches would be closer to the theoretical uncertainty.