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Identifying and mapping very small (<0.5 km²) mountain glaciers on coarse to high-resolution imagery.

Leigh, J.R. and Stokes, C.R. and Carr, J.R. and Evans, I.S. and Andreassen, L.M. and Evans, D.J.A. (2019) 'Identifying and mapping very small (<0.5 km²) mountain glaciers on coarse to high-resolution imagery.', Journal of glaciology., 65 . pp. 878-888.


Small mountain glaciers are an important part of the cryosphere and tend to respond rapidly to climate warming. Historically, mapping very small glaciers (generally considered to be <0.5 km2) using satellite imagery has often been subjective due to the difficulty in differentiating them from perennial snowpatches. For this reason, most scientists implement minimum size-thresholds (typically 0.01–0.05 km2). Here, we compare the ability of different remote-sensing approaches to identify and map very small glaciers on imagery of varying spatial resolutions (30–0.25 m) and investigate how operator subjectivity influences the results. Based on this analysis, we support the use of a minimum size-threshold of 0.01 km2 for imagery with coarse to medium spatial resolution (30–10 m). However, when mapping on high-resolution imagery (<1 m) with minimal seasonal snow cover, glaciers <0.05 km2 and even <0.01 km2 are readily identifiable and using a minimum threshold may be inappropriate. For these cases, we develop a set of criteria to enable the identification of very small glaciers and classify them as certain, probable or possible. This should facilitate a more consistent approach to identifying and mapping very small glaciers on high-resolution imagery, helping to produce more comprehensive and accurate glacier inventories.

Item Type:Article
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Publisher statement:COPYRIGHT: © The Author(s) 2019. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Date accepted:04 July 2019
Date deposited:23 July 2019
Date of first online publication:27 September 2019
Date first made open access:25 November 2019

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