Lead Detection in the Arctic Ocean from Sentinel-3 Satellite Data: A Comprehensive Assessment of Thresholding and Machine Learning Classification Methods. Issue 5 (16th August 2022)
- Record Type:
- Journal Article
- Title:
- Lead Detection in the Arctic Ocean from Sentinel-3 Satellite Data: A Comprehensive Assessment of Thresholding and Machine Learning Classification Methods. Issue 5 (16th August 2022)
- Main Title:
- Lead Detection in the Arctic Ocean from Sentinel-3 Satellite Data: A Comprehensive Assessment of Thresholding and Machine Learning Classification Methods
- Authors:
- Bij de Vaate, Inger
Martin, Ericka
Slobbe, D. Cornelis
Naeije, Marc
Verlaan, Martin - Abstract:
- Abstract: In the Arctic Ocean, obtaining water levels from satellite altimetry is hampered by the presence of sea ice. Hence, water level retrieval requires accurate detection of fractures in the sea ice (leads). This paper describes a thorough assessment of various surface type classification methods, including a thresholding method, nine supervised-, and two unsupervised machine learning methods, applied to Sentinel-3 Synthetic Aperture Radar Altimeter data. For the first time, the simultaneously sensed images from the Ocean and Land Color Instrument, onboard Sentinel-3, were used for training and validation of the classifiers. This product allows to identify leads that are at least 300 meters wide. Applied to data from winter months, the supervised Adaptive Boosting, Artificial Neural Network, Naïve-Bayes, and Linear Discriminant classifiers showed robust results with overall accuracies of up to 92%. The unsupervised Kmedoids classifier produced excellent results with accuracies up to 92.74% and is an attractive classifier when ground truth data is limited. All classifiers perform poorly on summer data, rendering surface classifications that are solely based on altimetry data from summer months unsuitable. Finally, the Adaptive Boosting, Artificial Neural Network, and Bootstrap Aggregation classifiers obtain the highest accuracies when the altimetry observations include measurements from the open ocean.
- Is Part Of:
- Marine geodesy. Volume 45:Issue 5(2022)
- Journal:
- Marine geodesy
- Issue:
- Volume 45:Issue 5(2022)
- Issue Display:
- Volume 45, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 45
- Issue:
- 5
- Issue Sort Value:
- 2022-0045-0005-0000
- Page Start:
- 462
- Page End:
- 495
- Publication Date:
- 2022-08-16
- Subjects:
- Arctic Ocean -- classification -- lead detection -- machine learning -- Sentinel-3 -- synthetic aperture radar
Marine geodesy -- Periodicals
Hydrographic surveying -- Periodicals
526.99 - Journal URLs:
- http://www.tandfonline.com/loi/umgd20#.VvpP-lL2aic ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01490419.2022.2089412 ↗
- Languages:
- English
- ISSNs:
- 0149-0419
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5375.370000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23237.xml