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Geosynchronous Satellite GF-4 Observations of Chlorophyll-a Distribution Details in the Bohai Sea, China

Authors :
Lina Cai
Juan Bu
Danling Tang
Minrui Zhou
Ru Yao
Shuyi Huang
Source :
Sensors, Vol 20, Iss 19, p 5471 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

We analyzed the distribution of chlorophyll-a (Chla) in the Bohai Sea area based on data from the geosynchronous orbit optical satellite Gaofen-4 (GF-4), which was launched in 2015, carrying a panchromatic multispectral sensor (PMS). This is the first time the geosynchronous orbit optical satellite GF-4 remote-sensing data has been used in China to detect the Chla change details in the Bohai Sea. A new GF-4 retrieved model was established based on the relationship between in situ Chla value and the reflectance combination of 2 and 4 bands, with the R2 of 0.9685 and the total average relative error of 37.42%. Twenty PMS images obtained from 2017 to 2019 were applied to analyze Chla in Bohai sea. The results show that: (1) the new built Chla inversion model PMS-1 for the GF-4 PMS sensor can extract Chla distribution details in the Bohai Sea well. The high Chla content in the Bohai Sea is mainly located in coastal areas, such as the top of Laizhou Bay, Bohai Bay and Liaodong Bay, with the value being around 13 µg/L. The concentration of Chla in the Bohai Strait and northern Yellow Sea is relatively low with the value being around 5 µg/L. (2). Taking full advantage of the continuous observation of geostationary orbit satellite, GF-4 with a high-resolution sensor PMS of 50 m can effectively detect short-term change (changes within 10 min) in Chla concentration. The changes mainly appear at the southwest and northeast costal area as well as in the center of Bohai Sea with the change value of around 3 µg/L. (3) The change of Chla concentration in the Bohai sea is related to the environmental factors such as seawater temperature, salinity, illumination and nutrient salts, as well as the dynamic factors such as wind, flow field and tidal current.

Details

Language :
English
ISSN :
14248220
Volume :
20
Issue :
19
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.2711fb64ca34d959a1ad51eec4f96b4
Document Type :
article
Full Text :
https://doi.org/10.3390/s20195471