The glaciers climate change initiative: Methods for creating glacier area, elevation change and velocity products

TitleThe glaciers climate change initiative: Methods for creating glacier area, elevation change and velocity products
Publication TypeJournal Article
Year of Publication2015
AuthorsPaul F, Bolch T, Kaab A., Nagler T., Nuth C., Scharrer K., Shepherd A., Strozzi T., Ticconi F., Bhambri R., Berthier E, Bevan S., Gourmelen N., Heid T., Jeong S., Kunz M., Lauknes T.R, Luckman A., Boncori J.PM, Moholdt G, Muir A., Neelmeijer J., Rankl M., VanLooy J., Van Niel T.
JournalRemote Sensing of Environment
Volume162
Pagination408-426
Date Published2015/06
Type of ArticleArticle
ISBN Number0034-4257
Accession NumberWOS:000355052000028
Keywordsaccuracy; Algorithm selection; british-columbia; determination; feature tracking; Glacier area; Glacier elevation change; Glacier velocity; himalayan glaciers; inventory data; land ice measurements; laser altimetry; mass-balance; microwave remote sensing; Optical and; Round robin experiment; satellite radar interferometry; southern patagonia; thematic mapper
Abstract

Glaciers and their changes through time are increasingly obtained from a wide range of satellite sensors. Due to the often remote location of glaciers in inaccessible and high-mountain terrain, satellite observations frequently provide the only available measurements. Furthermore, satellite data provide observations of glacier characteristics that are difficult to monitor using ground-based measurements, thus complementing the latter. In the Glaciers_cci project of the European Space Agency (ESA), three of these characteristics are investigated in detail: glacier area, elevation change and surface velocity. We use (a) data from optical sensors to derive glacier outlines, (b) digital elevation models from at least two points in time, (c) repeat altimetry for determining elevation changes, and (d) data from repeat optical and microwave sensors for calculating surface velocity. For the latter, the two sensor types provide complementary information in terms of spatio-temporal coverage. While (c) and (d) can be generated mostly automatically, (a) and (b) require the intervention of an analyst. Largely based on the results of various round robin experiments (multi-analyst benchmark studies) for each of the products, we suggest and describe the most suitable algorithms for product creation and provide recommendations concerning their practical implementation and the required post-processing. For some of the products (area, velocity) post-processing can influence product quality more than the main-processing algorithm. (C) 2013 Elsevier Inc. All rights reserved.

DOI10.1016/j.rse.2013.07.043
Short TitleRemote Sens. Environ.
Student Publication: 
No
Research Topics: 
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