Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data

It is of great significance to monitor sea ice for relieving and preventing sea ice disasters. In this paper, the growth and development of sea ice in Liaodong Bay of Bohai Sea in China were monitored using Sentinel-2 remote sensing data during the freezing period from January to March in 2018. Base...

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Published in:Journal of Spectroscopy
Main Authors: Zhiyong Wang, Peilei Sun, Lihua Wang, Mengyue Zhang, Zihao Wang
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2021
Subjects:
Online Access:https://doi.org/10.1155/2021/9974845
https://doaj.org/article/5575ed18fa5748e189073f7567a458f8
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spelling ftdoajarticles:oai:doaj.org/article:5575ed18fa5748e189073f7567a458f8 2024-09-15T18:34:07+00:00 Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data Zhiyong Wang Peilei Sun Lihua Wang Mengyue Zhang Zihao Wang 2021-01-01T00:00:00Z https://doi.org/10.1155/2021/9974845 https://doaj.org/article/5575ed18fa5748e189073f7567a458f8 EN eng Wiley http://dx.doi.org/10.1155/2021/9974845 https://doaj.org/toc/2314-4939 2314-4939 doi:10.1155/2021/9974845 https://doaj.org/article/5575ed18fa5748e189073f7567a458f8 Journal of Spectroscopy, Vol 2021 (2021) Optics. Light QC350-467 article 2021 ftdoajarticles https://doi.org/10.1155/2021/9974845 2024-08-05T17:48:40Z It is of great significance to monitor sea ice for relieving and preventing sea ice disasters. In this paper, the growth and development of sea ice in Liaodong Bay of Bohai Sea in China were monitored using Sentinel-2 remote sensing data during the freezing period from January to March in 2018. Based on the comprehensive analysis of the spectral characteristics of seawater and sea ice in visible bands, supplemented by the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI), we proposed a new method based on decision tree classification for extracting sea ice types in Liaodong Bay of Bohai Sea. Using the remote sensing data of eight satellite overpasses acquired from Sentinel-2A/B satellites, the distribution and area of the different sea ice types in Liaodong Bay during the freezing period of 2017/2018 were obtained. Compared with the maximum likelihood (ML) classification method and the support vector machine (SVM) classification method, the proposed method has higher accuracy when discriminating the sea ice types, which proved the new method proposed in this paper is suitable for extracting sea ice types from Sentinel-2 optical remote sensing data in Liaodong Bay. And its classification accuracy reaches 88.05%. The whole process of evolution such as the growth and development of sea ice in Liaodong Bay during the freezing period from January to March in 2018 was monitored. The maximum area of sea ice was detected on 27 January 2018, about 10,187 km2. At last, the quantitative relationship model between the sea ice area and the mean near-surface temperature derived by MODIS data in Liaodong Bay was established. Through research, we found that the mean near-surface temperature was the most important factor for affecting the formation and melt of sea ice in Liaodong Bay. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Journal of Spectroscopy 2021 1 16
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Optics. Light
QC350-467
spellingShingle Optics. Light
QC350-467
Zhiyong Wang
Peilei Sun
Lihua Wang
Mengyue Zhang
Zihao Wang
Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data
topic_facet Optics. Light
QC350-467
description It is of great significance to monitor sea ice for relieving and preventing sea ice disasters. In this paper, the growth and development of sea ice in Liaodong Bay of Bohai Sea in China were monitored using Sentinel-2 remote sensing data during the freezing period from January to March in 2018. Based on the comprehensive analysis of the spectral characteristics of seawater and sea ice in visible bands, supplemented by the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI), we proposed a new method based on decision tree classification for extracting sea ice types in Liaodong Bay of Bohai Sea. Using the remote sensing data of eight satellite overpasses acquired from Sentinel-2A/B satellites, the distribution and area of the different sea ice types in Liaodong Bay during the freezing period of 2017/2018 were obtained. Compared with the maximum likelihood (ML) classification method and the support vector machine (SVM) classification method, the proposed method has higher accuracy when discriminating the sea ice types, which proved the new method proposed in this paper is suitable for extracting sea ice types from Sentinel-2 optical remote sensing data in Liaodong Bay. And its classification accuracy reaches 88.05%. The whole process of evolution such as the growth and development of sea ice in Liaodong Bay during the freezing period from January to March in 2018 was monitored. The maximum area of sea ice was detected on 27 January 2018, about 10,187 km2. At last, the quantitative relationship model between the sea ice area and the mean near-surface temperature derived by MODIS data in Liaodong Bay was established. Through research, we found that the mean near-surface temperature was the most important factor for affecting the formation and melt of sea ice in Liaodong Bay.
format Article in Journal/Newspaper
author Zhiyong Wang
Peilei Sun
Lihua Wang
Mengyue Zhang
Zihao Wang
author_facet Zhiyong Wang
Peilei Sun
Lihua Wang
Mengyue Zhang
Zihao Wang
author_sort Zhiyong Wang
title Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data
title_short Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data
title_full Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data
title_fullStr Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data
title_full_unstemmed Monitoring Sea Ice in Liaodong Bay of Bohai Sea during the Freezing Period of 2017/2018 Using Sentinel-2 Remote Sensing Data
title_sort monitoring sea ice in liaodong bay of bohai sea during the freezing period of 2017/2018 using sentinel-2 remote sensing data
publisher Wiley
publishDate 2021
url https://doi.org/10.1155/2021/9974845
https://doaj.org/article/5575ed18fa5748e189073f7567a458f8
genre Sea ice
genre_facet Sea ice
op_source Journal of Spectroscopy, Vol 2021 (2021)
op_relation http://dx.doi.org/10.1155/2021/9974845
https://doaj.org/toc/2314-4939
2314-4939
doi:10.1155/2021/9974845
https://doaj.org/article/5575ed18fa5748e189073f7567a458f8
op_doi https://doi.org/10.1155/2021/9974845
container_title Journal of Spectroscopy
container_volume 2021
container_start_page 1
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