Comparison of multiple glacier inventories with a new inventory derived from high-resolution ALOS imagery in the Bhutan Himalaya

• Published in: The Cryosphere
• Main Authors: Nagai, H., Fujita, K., Sakai, A., Nuimura, T., Tadono, T.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2016
• Subjects: article; Verlagsveröffentlichung; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-10-65-2016; https://noa.gwlb.de/receive/cop_mods_00014272; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00014228/tc-10-65-2016.pdf; https://tc.copernicus.org/articles/10/65/2016/tc-10-65-2016.pdf

Digital glacier inventories are invaluable data sets for revealing the characteristics of glacier distribution and for upscaling measurements from selected locations to entire mountain ranges. Here, we present a new inventory of Advanced Land Observing Satellite (ALOS) imagery and compare it with existing inventories for the Bhutan Himalaya. The new inventory contains 1583 glaciers (1487 ± 235 km2), thereof 219 debris-covered glaciers (951 ± 193 km2) and 1364 debris-free glaciers (536 ± 42 km2). Moreover, we propose an index for quantifying consistency between two glacier outlines. Comparison of the overlap ratio demonstrates that the ALOS-derived glacier inventory contains delineation uncertainties of 10–20 % which depend on glacier size, that the shapes and geographical locations of glacier outlines derived from the fourth version of the Randolph Glacier Inventory have been improved in the fifth version, and that the latter is consistent with other inventories. In terms of whole glacier distribution, each data set is dominated by glaciers of 1.0–5.0 km2 area (31–34 % of the total area), situated at approximately 5400 m elevation (nearly 10 % in 100 m bin) with either north or south aspects (22 and 15 %). However, individual glacier outlines and their area exhibit clear differences among inventories. Furthermore, consistent separation of glaciers with inconspicuous termini remains difficult, which, in some cases, results in different values for glacier number. High-resolution imagery from Google Earth can be used to improve the interpretation of glacier outlines, particularly for debris-covered areas and steep adjacent slopes.