Glacier movement prediction through computer vision and satellite imagery

Vonica, M.-M., Ancuta, A. and Frincu, M. ORCID: 0000-0003-1034-8409, 2021. Glacier movement prediction through computer vision and satellite imagery. In: C. Schneider, M. Marin, V. Negru and D. Zaharie, eds., Proceedings: 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2021). Piscataway: Institute of Electrical and Electronics Engineers, pp. 113-120. ISBN 9781665406505

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Abstract

Over the last decade, climate change has impacted Earths' atmosphere and environment more than anytime before. Glaciers are the most sensitive indicators of its impact. In this work, we model a glacier's evolution by applying computer vision algorithms on high-resolution satellite imagery. We detect changes in the ice coverage movement by applying a dense optical flow algorithm over an image time series covering a particular scene (region) and processed to extract the NDSI. We perform tests on the Jungfrau-Aletsch-Bietschhorn (JAB) glacier in the Swiss Alps. Our results show that we are able to obtain relevant information by computing motion vectors across time. Furthermore, we observe small differences between our predicted NDSI and the observed values demonstrating the efficiency of the approach.

Item Type: Chapter in book
Description: Paper presented at the 23rd International Symposium on
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), Timisoara, Romania [Virtual Conference], 7-10 December 2021.
Creators: Vonica, M.-M., Ancuta, A. and Frincu, M.
Publisher: Institute of Electrical and Electronics Engineers
Place of Publication: Piscataway
Date: 2021
ISBN: 9781665406505
Identifiers:
NumberType
10.1109/SYNASC54541.2021.00029DOI
1490354Other
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 12 Nov 2021 11:56
Last Modified: 04 Apr 2022 08:46
Related URLs:
URI: http://irep.ntu.ac.uk/id/eprint/44743

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