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  • rse_accuracy_glacier_products_rev170725_tc

    Rights statement: This is the author’s version of a work that was accepted for publication in Remote Sensing of Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Remote Sensing of Environment, 203, 2017 DOI: 10.1016/j.rse.2017.08.038

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Error sources and guidelines for quality assessment of glacier area, elevation change, and velocity products derived from satellite data in the Glaciers_cci project

Research output: Contribution to journalJournal articlepeer-review

Published
  • Frank Paul
  • Tobias Bolch
  • Kate Briggs
  • Andreas Kääb
  • Malcolm McMillan
  • Robert McNabb
  • Thomas Nagler
  • Christopher Nuth
  • Philipp Rastner
  • Tazio Strozzi
  • Jan Wuite
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<mark>Journal publication date</mark>15/12/2017
<mark>Journal</mark>Remote Sensing of Environment
Volume203
Number of pages20
Pages (from-to)256-275
Publication StatusPublished
Early online date11/11/17
<mark>Original language</mark>English

Abstract

Satellite data provide a large range of information on glacier dynamics and changes. Results are often reported, provided and used without consideration of measurement accuracy (difference to a true value) and precision (variability of independent assessments). Whereas accuracy might be difficult to determine due to the limited availability of appropriate reference data and the complimentary nature of satellite measurements, precision can be obtained from a large range of measures with a variable effort for determination. This study provides a systematic overview on the factors influencing accuracy and precision of glacier area, elevation change (from altimetry and DEM differencing), and velocity products derived from satellite data, along with measures for calculating them. A tiered list of recommendations is provided (sorted for effort from Level 0 to 3) as a guide for analysts to apply what is possible given the datasets used and available to them. The more simple measures to describe product quality (Levels 0 and 1) can often easily be applied and should thus always be reported. Medium efforts (Level 2) require additional work but provide a more realistic assessment of product precision. Real accuracy assessment (Level 3) requires independent and coincidently acquired reference data with high accuracy. However, these are rarely available and their transformation into an unbiased source of information is challenging. This overview is based on the experiences and lessons learned in the ESA project Glaciers_cci rather than a review of the literature.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Remote Sensing of Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Remote Sensing of Environment, 203, 2017 DOI: 10.1016/j.rse.2017.08.038