Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data

Show full item record



Permalink

http://hdl.handle.net/10138/300124

Citation

Yan , Y , Huang , K , Shao , D , Xu , Y & Gu , W 2019 , ' Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data ' , Sustainability , vol. 11 , no. 3 , 777 . https://doi.org/10.3390/su11030777

Title: Monitoring the Characteristics of the Bohai Sea Ice Using High-Resolution Geostationary Ocean Color Imager (GOCI) Data
Author: Yan, Yu; Huang, Kaiyue; Shao, Dongdong; Xu, Yingjun; Gu, Wei
Contributor: University of Helsinki, Institute for Atmospheric and Earth System Research (INAR)
Date: 2019-02-01
Language: eng
Number of pages: 17
Belongs to series: Sustainability
ISSN: 2071-1050
URI: http://hdl.handle.net/10138/300124
Abstract: Satellite remote sensing data, such as moderate resolution imaging spectroradiometers (MODIS) and advanced very high-resolution radiometers (AVHRR), are being widely used to monitor sea ice conditions and their variability in the Bohai Sea, the southernmost frozen sea in the Northern Hemisphere. Monitoring the characteristics of the Bohai Sea ice can provide crucial information for ice disaster prevention for marine transportation, oil field operation, and regional climate change studies. Although these satellite data cover the study area with fairly high spatial resolution, their typically limited cloudless images pose serious restrictions for continuous observation of short-term dynamics, such as sub-seasonal changes. In this study, high spatiotemporal resolution (500 m and eight images per day) geostationary ocean color imager (GOCI) data with a high proportion of cloud-free images were used to monitor the characteristics of the Bohai Sea ice, including area and thickness. An object-based feature extraction method and an albedo-based thickness inversion model were used for estimating sea ice area and thickness, respectively. To demonstrate the efficacy of the new dataset, a total of 68 GOCI images were selected to analyze the evolution of sea ice area and thickness during the winter of 2012-2013 with severe sea ice conditions. The extracted sea ice area was validated using Landsat Thematic Mapper (TM) data with higher spatial resolution, and the estimated sea ice thickness was found to be consistent with in situ observation results. The entire sea ice freezing-melting processes, including the key events such as the day with the maximum ice area and the first and last days of the frozen season, were better resolved by the high temporal-resolution GOCI data compared with MODIS or AVHRR data. Both characteristics were found to be closely correlated with cumulative freezing/melting degree days. Our study demonstrates the applicability of the GOCI data as an improved dataset for studying the Bohai Sea ice, particularly for purposes that require high temporal resolution data, such as sea ice disaster monitoring.
Subject: sea ice monitoring
geostationary ocean color imager
ocean remote sensing
Bohai Sea
SUSPENDED PARTICULATE MATTER
HARMFUL ALGAL BLOOM
EAST CHINA SEA
THICKNESS
MODIS
SATELLITE
CURRENTS
MODEL
VARIABILITY
SALINITY
1172 Environmental sciences
Rights:


Files in this item

Total number of downloads: Loading...

Files Size Format View
sustainability_11_00777.pdf 4.251Mb PDF View/Open

This item appears in the following Collection(s)

Show full item record