Next Article in Journal
Exploring the Potential of WorldView-2 Red-Edge Band-Based Vegetation Indices for Estimation of Mangrove Leaf Area Index with Machine Learning Algorithms
Previous Article in Journal
Crop Classification and LAI Estimation Using Original and Resolution-Reduced Images from Two Consumer-Grade Cameras
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(10), 1062;

A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods

Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
University of Bremen, 28359 Bremen, Germany
Author to whom correspondence should be addressed.
Received: 21 July 2017 / Revised: 14 September 2017 / Accepted: 22 September 2017 / Published: 18 October 2017
Full-Text   |   PDF [17744 KB, uploaded 18 October 2017]   |  


Various glaciological topics require observations of horizontal velocities over vast areas, e.g., detecting acceleration of glaciers, as well as for estimating basal parameters of ice sheets using inverse modelling approaches. The quality of the velocity is of high importance; hence, methods to remove noisy points in remote sensing derived data are required. We present a three-step filtering process and assess its performance for velocity fields in Greenland and Antarctica. The filtering uses the detection of smooth segments, removal of outliers using the median and constraints on the variability of the flow direction over short distances. The applied filter preserves the structures in the velocity fields well (e.g., shear margins) and removes noisy data points successfully, while keeping 72–96% of the data. In slow flowing regions, which are particularly challenging, the standard deviation is reduced by up to 96%, an improvement that affects vast areas of the ice sheets. View Full-Text
Keywords: filter; surface velocity; glaciers; outlier; processing filter; surface velocity; glaciers; outlier; processing

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Lüttig, C.; Neckel, N.; Humbert, A. A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods. Remote Sens. 2017, 9, 1062.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top