Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques

A new combination of phase- and cross-correlation techniques for sea ice tracking from sequential synthetic aperture radar images investigated. An operational Python-based sea ice drift algorithm based on this combination from Sentinel-1 images is proposed.

Bibliographic Details
Published in:2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)
Main Authors: Demchev, Denis, Kharchenko, Victoria V., Andeeva, Olga M., Korobov, Petr V., Eriksson, Leif
Language:unknown
Published: 2020
Subjects:
Atom and Molecular Physics and Optics
phase-correlation
SAR
sea ice
image retrieval
Sea ice
Online Access:https://doi.org/10.1109/EIConRus49466.2020.9039240
https://research.chalmers.se/en/publication/516482
id ftchalmersuniv:oai:research.chalmers.se:516482
record_format openpolar
spelling ftchalmersuniv:oai:research.chalmers.se:516482 2023-05-15T18:16:06+02:00 Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques Demchev, Denis Kharchenko, Victoria V. Andeeva, Olga M. Korobov, Petr V. Eriksson, Leif 2020 text https://doi.org/10.1109/EIConRus49466.2020.9039240 https://research.chalmers.se/en/publication/516482 unknown http://dx.doi.org/10.1109/EIConRus49466.2020.9039240 https://research.chalmers.se/en/publication/516482 Atom and Molecular Physics and Optics phase-correlation SAR sea ice image retrieval 2020 ftchalmersuniv https://doi.org/10.1109/EIConRus49466.2020.9039240 2022-12-11T07:11:10Z A new combination of phase- and cross-correlation techniques for sea ice tracking from sequential synthetic aperture radar images investigated. An operational Python-based sea ice drift algorithm based on this combination from Sentinel-1 images is proposed. Other/Unknown Material Sea ice Chalmers University of Technology: Chalmers research 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) 1378 1381
institution Open Polar
collection Chalmers University of Technology: Chalmers research
op_collection_id ftchalmersuniv
language unknown
topic Atom and Molecular Physics and Optics
phase-correlation
SAR
sea ice
image retrieval
spellingShingle Atom and Molecular Physics and Optics
phase-correlation
SAR
sea ice
image retrieval
Demchev, Denis
Kharchenko, Victoria V.
Andeeva, Olga M.
Korobov, Petr V.
Eriksson, Leif
Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
topic_facet Atom and Molecular Physics and Optics
phase-correlation
SAR
sea ice
image retrieval
description A new combination of phase- and cross-correlation techniques for sea ice tracking from sequential synthetic aperture radar images investigated. An operational Python-based sea ice drift algorithm based on this combination from Sentinel-1 images is proposed.
author Demchev, Denis
Kharchenko, Victoria V.
Andeeva, Olga M.
Korobov, Petr V.
Eriksson, Leif
author_facet Demchev, Denis
Kharchenko, Victoria V.
Andeeva, Olga M.
Korobov, Petr V.
Eriksson, Leif
author_sort Demchev, Denis
title Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
title_short Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
title_full Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
title_fullStr Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
title_full_unstemmed Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
title_sort improving sea ice drift retrieval from sar images using phase- and cross-correlation techniques
publishDate 2020
url https://doi.org/10.1109/EIConRus49466.2020.9039240
https://research.chalmers.se/en/publication/516482
genre Sea ice
genre_facet Sea ice
op_relation http://dx.doi.org/10.1109/EIConRus49466.2020.9039240
https://research.chalmers.se/en/publication/516482
op_doi https://doi.org/10.1109/EIConRus49466.2020.9039240
container_title 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)
container_start_page 1378
op_container_end_page 1381
_version_ 1766189535450890240

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