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Glacier centerlines are crucial input for many glaciological applications. From the morphological perspective, we proposed a new automatic method to derive glacier centerlines, which is based on the Euclidean allocation and the terrain characteristics of glacier surface. In the algorithm, all glaciers are logically classified as three types including simple glacier, simple compound glacier, and complex glacier, with corresponding process ranges from simple to complex. The process for extracting centerlines of glaciers introduces auxiliary reference lines and follows the setting of not passing through bare rock. The program of automatic extraction of glacier centerlines was implemented in Python and only required the glacier boundary and digital elevation model (DEM) as input. Application of this method to 48 571 glaciers in the second Chinese glacier inventory automatically yielded the corresponding glacier centerlines with an average computing time of 20.96 s, a success rate of 100 % and a comprehensive accuracy of 94.34 %. A comparison of the longest length of glaciers to the corresponding glaciers in the Randolph Glacier Inventory v6.0 revealed that our results were superior. Meanwhile, our final product provides more information about glacier length, such as the average length, and the longest length, the lengths in the accumulation and ablation regions of each glacier. [ABSTRACT FROM AUTHOR]

Due to the influence of the Indian monsoon, the Kangri Karpo Mountains in the south-east of the Tibetan Plateau is in the most humid and one of the most important and concentrated regions containing maritime (temperate) glaciers. Glacier mass loss in the Kangri Karpo is an important contributor to global mean sea level rise, and changes run-off distribution, increasing the risk of glaciallake outburst floods (GLOFs). Because of its inaccessibility and high labour costs, information about the Kangri Karpo glaciers is still limited. Using geodetic methods based on digital elevation models (DEMs) derived from 1980 topographic maps from the Shuttle Radar Topography Mission (SRTM) (2000) and from TerraSAR-X/TanDEM-X (2014), this study has determined glacier elevation changes. Glacier area and length changes between 1980 and 2015 were derived from topographical maps and Landsat TM/ETMC/OLI images. Results show that the Kangri Karpo contained 1166 glaciers with an area of 2048:50±48:65 km2 in 2015. Ice cover diminished by 679:51±59:49 km2 (24:9±2:2%) or 0:71±0:06%a-1 from 1980 to 2015, although nine glaciers advanced. A glacierized area of 788.28 km2, derived from DEM differencing, experienced a mean mass loss of 0:46±0:08mw:e: a-1 from 1980 to 2014. Shrinkage and mass loss accelerated significantly from 2000 to 2015 compared to 1980-2000, consistent with a warming climate. [ABSTRACT FROM AUTHOR]