Browse by author
Lookup NU author(s): Dr Rachel Carr
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2019 This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. 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.
Author(s): Leigh JR, Stokes CR, Carr RJ, Evans IS, Andreassen LM, Evans DJA
Publication type: Article
Publication status: Published
Journal: Journal of Glaciology
Print publication date: 01/12/2019
Online publication date: 27/09/2019
Acceptance date: 09/07/2019
Date deposited: 14/10/2019
ISSN (print): 0022-1430
ISSN (electronic): 1727-5652
Publisher: Cambridge University Press
Altmetrics provided by Altmetric