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

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 remo...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Lüttig, Christine, Neckel, Niklas, Humbert, Angelika
Format: Article in Journal/Newspaper
Language:unknown
Published: MDPI AG 2017
Subjects:
Online Access:https://epic.awi.de/id/eprint/45710/
https://epic.awi.de/id/eprint/45710/1/remotesensing-09-01062.pdf
https://doi.org/10.3390/rs9101062
https://hdl.handle.net/10013/epic.51821
https://hdl.handle.net/10013/epic.51821.d001
id ftawi:oai:epic.awi.de:45710
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spelling ftawi:oai:epic.awi.de:45710 2023-05-15T13:45:21+02:00 A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods Lüttig, Christine Neckel, Niklas Humbert, Angelika 2017-10-18 application/pdf https://epic.awi.de/id/eprint/45710/ https://epic.awi.de/id/eprint/45710/1/remotesensing-09-01062.pdf https://doi.org/10.3390/rs9101062 https://hdl.handle.net/10013/epic.51821 https://hdl.handle.net/10013/epic.51821.d001 unknown MDPI AG https://epic.awi.de/id/eprint/45710/1/remotesensing-09-01062.pdf https://hdl.handle.net/10013/epic.51821.d001 Lüttig, C. orcid:0000-0003-0018-8472 , Neckel, N. orcid:0000-0003-4300-5488 and Humbert, A. (2017) A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods , Remote Sensing, 9 (10), p. 1062 . doi:10.3390/rs9101062 <https://doi.org/10.3390/rs9101062> , hdl:10013/epic.51821 EPIC3Remote Sensing, MDPI AG, 9(10), pp. 1062, ISSN: 2072-4292 Article isiRev 2017 ftawi https://doi.org/10.3390/rs9101062 2021-12-24T15:43:23Z 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. Article in Journal/Newspaper Antarc* Antarctica Greenland Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Greenland Remote Sensing 9 10 1062
institution Open Polar
collection Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
op_collection_id ftawi
language unknown
description 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.
format Article in Journal/Newspaper
author Lüttig, Christine
Neckel, Niklas
Humbert, Angelika
spellingShingle Lüttig, Christine
Neckel, Niklas
Humbert, Angelika
A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods
author_facet Lüttig, Christine
Neckel, Niklas
Humbert, Angelika
author_sort Lüttig, Christine
title A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods
title_short A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods
title_full A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods
title_fullStr A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods
title_full_unstemmed A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods
title_sort combined approach for filtering ice surface velocity fields derived from remote sensing methods
publisher MDPI AG
publishDate 2017
url https://epic.awi.de/id/eprint/45710/
https://epic.awi.de/id/eprint/45710/1/remotesensing-09-01062.pdf
https://doi.org/10.3390/rs9101062
https://hdl.handle.net/10013/epic.51821
https://hdl.handle.net/10013/epic.51821.d001
geographic Greenland
geographic_facet Greenland
genre Antarc*
Antarctica
Greenland
genre_facet Antarc*
Antarctica
Greenland
op_source EPIC3Remote Sensing, MDPI AG, 9(10), pp. 1062, ISSN: 2072-4292
op_relation https://epic.awi.de/id/eprint/45710/1/remotesensing-09-01062.pdf
https://hdl.handle.net/10013/epic.51821.d001
Lüttig, C. orcid:0000-0003-0018-8472 , Neckel, N. orcid:0000-0003-4300-5488 and Humbert, A. (2017) A Combined Approach for Filtering Ice Surface Velocity Fields Derived from Remote Sensing Methods , Remote Sensing, 9 (10), p. 1062 . doi:10.3390/rs9101062 <https://doi.org/10.3390/rs9101062> , hdl:10013/epic.51821
op_doi https://doi.org/10.3390/rs9101062
container_title Remote Sensing
container_volume 9
container_issue 10
container_start_page 1062
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