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...
Published in: | Journal of Spectroscopy |
---|---|
Main Authors: | , , , , |
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 |
id |
ftdoajarticles:oai:doaj.org/article:5575ed18fa5748e189073f7567a458f8 |
---|---|
record_format |
openpolar |
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 |
op_container_end_page |
16 |
_version_ |
1810475858424496128 |