Assessment of GCOM-C Satellite Imagery in Bloom Detection: A Case Study in the East China Sea

被引:4
作者
Feng, Chi [1 ]
Zhu, Yuanli [2 ]
Shen, Anglu [3 ]
Li, Changpeng [4 ]
Song, Qingjun [5 ]
Tao, Bangyi [4 ]
Zeng, Jiangning [2 ]
机构
[1] Suzhou Univ Sci & Technol, Sch Geog Sci & Geomat Engn, Suzhou 215009, Peoples R China
[2] Minist Nat Resources, Inst Oceanog 2, Key Lab Marine Ecosyst Dynam, Hangzhou 310012, Peoples R China
[3] Shanghai Ocean Univ, Coll Marine Ecol & Environm, Shanghai 201306, Peoples R China
[4] Minist Nat Resources, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou 310012, Peoples R China
[5] Minist Nat Resources Peoples Republ China, Natl Satellite Ocean Applicat Serv, Beijing 100081, Peoples R China
关键词
bloom detection; remote sensing; East China Sea; GCOM-C; DISSOLVED ORGANIC-MATTER; HARMFUL ALGAL BLOOMS; GULF-OF-MEXICO; PHYTOPLANKTON BLOOMS; KARENIA-BREVIS; RED TIDE; OCEAN; WATERS; DINOFLAGELLATE; RETRIEVAL;
D O I
10.3390/rs15030691
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The coast of the East China Sea (ECS) is one of the regions most frequently affected by harmful algal blooms in China. Remote sensing monitoring could assist in understanding the mechanism of blooms and their associated environmental changes. Based on imagery from the Second-Generation Global Imager (SGLI) conducted by Global Change Observation Mission-Climate (GCOM-C) (Japan), the accuracy of satellite measurements was initially validated using matched pairs of satellite and ground data relating to the ECS. Additionally, using SGLI data from the coast of the ECS, we compared the applicability of three bloom extraction methods: spectral shape, red tide index, and algal bloom ratio. With an RMSE of less than 25%, satellite data at 490 nm, 565 nm, and 670 nm showed good consistency with locally measured remote sensing reflectance data. However, there was unexpected overestimation at 443 nm of SGLI data. By using a linear correction method, the RMSE at 443 nm was decreased from 27% to 17%. Based on the linear corrected SGLI data, the spectral shape at 490 nm was found to provide the most satisfactory results in separating bloom and non-bloom waters among the three bloom detection methods. In addition, the capability in harmful algae distinguished using SGLI data was discussed. Both of the Bloom Index method and the green-red Spectral Slope method were found to be applicable for phytoplankton classification using SGLI data. Overall, the SGLI data provided by GCOM-C are consistent with local data and can be used to identify bloom water bodies in the ECS, thereby providing new satellite data to support monitoring of bloom changes in the ECS.
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页数:17
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