Verification of remote sensing reflectance products and seasonal ocean variation characteristics using the Geostationary Ocean Color Imager II (GOCI-II)

被引:0
作者
Feng, Chi [1 ]
Jing, Yutao [2 ]
Chen, Taisheng [1 ]
Xiong, Can [2 ]
Bao, Liangliang [2 ]
机构
[1] Suzhou Univ Sci & Technol, Sch Geog Sci & Geomatics Engn, Xuefu Rd 99, Suzhou 215009, Peoples R China
[2] Anhui Univ Sci & Technol, Sch Spatial Informat & Mapping Engn, Huainan, Peoples R China
基金
中国国家自然科学基金;
关键词
Geostationary ocean colour satellite; GOCI-II; VIIRS; MODIS; Seasonal variability; The East China Sea; ATMOSPHERIC CORRECTION ALGORITHM; MODIS; CALIBRATION; RETRIEVAL; SEAWIFS; WATER;
D O I
10.1080/01431161.2024.2440133
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The second Geostationary Ocean Color Imager-II (GOCI-II) onboard the Communication, Ocean, and Meteorological satellite (COMS) has higher reliability and practical value in marine environmental monitoring research compared with polar orbit satellites. Nevertheless, the reflectance products may differ due to the sensor performance differences and ocean colour remote sensing intricacy, especially in high-turbidity coastal areas. Consequently, to verify the authenticity of remote sensing reflectance (${R_{rs}}\left({\rm{\lambda }} \right)$Rrs lambda) products, this paper takes the East China Sea (ECS) with complex and changeable ocean colour elements as the research area, establishes GOCI-II&VIIRS, GOCI-II&MODIS, and MODIS&VIIRS ${R_{rs}}\left({\rm{\lambda }} \right)$Rrs lambda data sets based on the matching principles to evaluate the differences between ocean colour remote sensing products. Results indicate (1) Strong agreement between GOCI-II, VIIRS, and MODIS ${R_{rs}}\left({\rm{\lambda }} \right)$Rrs lambda data exists with significant correlation on the 443 nm, 490 nm, and 555 nm wavelengths; (2) The largest discrepancy was between GOCI-II&MODIS, followed by GOCI-II&VIIRS, and the smallest was amongst MODIS&VIIRS. Furthermore, the seasonal variation of reflectance data and quantitative results were extracted using the coefficient of variations (CVs) of ${R_{rs}}\left({\rm{\lambda }} \right)$Rrs lambda in the ECS in 2021. Compared with MODIS and VIIRS, the CVs of ${R_{rs}}\left({\rm{\lambda }} \right)$Rrs lambda obtained by GOCI-II showed significant stability, especially in summer and winter. The results indicate significant space and time (seasonal) dependence in the ECS, primarily related to its physical and biological optical characteristics.
引用
收藏
页码:1773 / 1789
页数:17
相关论文
共 40 条
  • [21] Corrections to the MODIS Aqua Calibration Derived From MODIS Aqua Ocean Color Products
    Meister, Gerhard
    Franz, Bryan A.
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (10): : 6534 - 6541
  • [22] Corrections to the Calibration of MODIS Aqua Ocean Color Bands Derived From SeaWiFS Data
    Meister, Gerhard
    Franz, Bryan A.
    Kwiatkowska, Ewa J.
    McClain, Charles R.
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2012, 50 (01): : 310 - 319
  • [23] Uncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets
    Melin, F.
    Sclep, G.
    Jackson, A.
    Sathyendranath, S.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2016, 177 : 107 - 124
  • [24] Statistical evaluation of satellite ocean color data retrievals
    Mikelsons, Karlis
    Wang, Menghua
    Jiang, Lide
    [J]. REMOTE SENSING OF ENVIRONMENT, 2020, 237
  • [25] Mu B., 2014, Research on Remote Sensing Information Extraction of Turbid Water in the Bohai Sea Based on the Geostationary Aqua Satellite GOCI D
  • [26] The Ocean Colour Climate Change Initiative: II. Spatial and temporal homogeneity of satellite data retrieval due to systematic effects in atmospheric correction processors
    Mueller, Dagmar
    Krasemann, Hajo
    Brewin, Robert J. W.
    Brockmann, Carsten
    Deschamps, Pierre-Yves
    Doerffer, Roland
    Fomferra, Norman
    Franz, Bryan A.
    Grant, Mike G.
    Groom, Steve B.
    Melin, Frederic
    Platt, Trevor
    Regner, Peter
    Sathyendranath, Shubha
    Steinmetz, Francois
    Swinton, John
    [J]. REMOTE SENSING OF ENVIRONMENT, 2015, 162 : 257 - 270
  • [27] Decadal Measurements of the First Geostationary Ocean Color Satellite (GOCI) Compared with MODIS and VIIRS Data
    Park, Myung-Sook
    Lee, Seonju
    Ahn, Jae-Hyun
    Lee, Sun-Ju
    Choi, Jong-Kuk
    Ryu, Joo-Hyung
    [J]. REMOTE SENSING, 2022, 14 (01)
  • [28] A new combined atmospheric correction algorithm for GOCI-2 Data over coastal waters assessed by long-term satellite ocean color platforms
    Qiao, Feng
    Chen, Jianyu
    Han, Bing
    Song, Qingjun
    Zhu, Qiankun
    Jia, Di
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2024, 45 (05) : 1640 - 1657
  • [29] Renhua Z., 2010, SCIENTIA SINICA Terrae, V40, P211
  • [30] Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)
    Joo-Hyung Ryu
    Hee-Jeong Han
    Seongick Cho
    Young-Je Park
    Yu-Hwan Ahn
    [J]. Ocean Science Journal, 2012, 47 (3) : 223 - 233