Reconstruction of geostationary satellite ocean color data based on DINEOF

CHEN Yi-jun; ZHANG Feng; DU Zhen-hong; LIU Ren-yi

doi:10.3969/j.issn.1001-909X.2019.04.002

PDF(3098 KB)

Journal of Marine Sciences ›› 2019, Vol. 37 ›› Issue (4) : 14-23. DOI: 10.3969/j.issn.1001-909X.2019.04.002

Reconstruction of geostationary satellite ocean color data based on DINEOF

CHEN Yi-jun^1,2, ZHANG Feng^1,2, DU Zhen-hong^1,2, LIU Ren-yi^1,2

Author information +

History +

Abstract

Geostationary Ocean Color Imager (GOCI) provides ocean water color data with time resolutions up to the hour, making it possible to monitor the marine environment in a time-varying manner. However, due to the influence of clouds, fog and haze over the ocean, the continuous high-missing rate or even complete loss of data makes the data use value greatly reduced. Based on the Data INterpolating Empirical Orthogonal Functions, highlighting the position of time elements in reconstruction, a reconstruction method using abnormal pixel detection, Laplacian smoothing and temporal coefficient twice decomposition interpolation was proposed for geostationary satellite ocean color data (DINEOF-G). This method is used to reconstruct the total suspended matter data of Hangzhou Bay in 2017. The results show that the proposed method improves the reconstruction accuracy by 8% and the data reconstruction rate by 36% compared with the classical method. The reconstructed data reflects the seasonal variation and spatial distribution characteristics of the total suspended matter in Hangzhou Bay.

Key words

data reconstruction / DINEOF / GOCI / Hangzhou Bay / total suspended matter

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

CHEN Yi-jun, ZHANG Feng, DU Zhen-hong, LIU Ren-yi. Reconstruction of geostationary satellite ocean color data based on DINEOF[J]. Journal of Marine Sciences. 2019, 37(4): 14-23 https://doi.org/10.3969/j.issn.1001-909X.2019.04.002

References

[1] ZHANG Da-ming, XU Dong-feng, ZHANG Ben-zhao, et al. Optimal interpolation and its application to assimilation of SST data in the Tropic Pacific Ocean[J]. Journal of Marine Sciences, 2005, 23(4): 1-7.
张大明,许东峰,章本照,等. 最优插值法及其在热带太平洋海表温度数据同化中的应用[J]. 海洋学研究, 2005, 23(4): 1-7.
[2] MA Xiang-hui. Study on reconstruction methods of missing data in MODIS sea surface chlorophyll data products[D]. Beijing: China University of Geosciences, 2013.
马翱慧. MODIS海洋叶绿素浓度产品缺失数据重构方法研究[D]. 北京: 中国地质大学(北京), 2013.
[3] BECKERS J M, RIXEN M. EOF calculations and data filling from incomplete oceanographic datasets[J]. Journal of Atmospheric and Oceanic Technology, 2003, 20(12): 1 839-1 856.
[4] SHENG Zheng, SHI Han-qing, DING You-zhuan. Missing satellite-based sea surface temperature data reconstructed by DINEOF method[J]. Advances in Marine Science, 2009, 27(2): 243-249.
盛峥,石汉青,丁又专. 利用DINEOF方法重构缺测的卫星遥感海温数据[J]. 海洋科学进展, 2009, 27(2): 243-249.
[5] HE Hai-lun, LI Yi, WANG Yuan, et al. Reconstruction of chlorophyll a mass concentration in the East China Sea using data interpolating empirical orthogonal functions[J]. Journal of Marine Sciences, 2013, 31(2): 10-15.
何海伦,李熠,王渊,等. 利用经验正交函数数据插值法重构东中国海叶绿素a质量浓度场[J]. 海洋学研究, 2013, 31(2): 10-15.
[6] DING You-zhuan. Data reconstruction and assimilation experiment of satellite sea surface temperature and suspended sediment concentration[D]. Nanjing: Nanjing University of Science & Technology, 2009.
丁又专. 卫星遥感海表温度与悬浮泥沙浓度的资料重构及数据同化试实验[D]. 南京: 南京理工大学, 2009.
[7] ALVERA-AZCÁRATE A, BARTH A, PARARD G, et al. Analysis of SMOS sea surface salinity data using DINEOF[J]. Remote Sensing of Environment, 2016, 180: 137-145.
[8] LIU Xiao-ming, WANG Meng-hua. Analysis of ocean diurnal variations from the Korean Geostationary Ocean Color Imager measurements using the DINEOF method[J]. Estuarine, Coastal and Shelf Science, 2016, 180: 230-241.
[9] ALVERA-AZCÁRATE A, BARTH A, RIXEN M, et al. Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature[J]. Ocean Modelling, 2005, 9(4): 325-346.
[10] ALVERA-AZCÁRATE A, SIRJACOBS D, BARTH A, et al. Outlier detection in satellite data using spatial coherence[J]. Remote Sensing of Environment, 2012, 119: 84-91.
[11] SHE Yu-ping. Method for detecting outliers based on double MAD from median[J]. Journal of Langfang Teachers University(Natural Science Edition), 2016, 16(2): 25-27.
佘玉萍. 基于中位数的双MAD的离群值检测方法[J]. 廊坊师范学院学报(自然科学版), 2016, 16(2): 25-27.
[12] LI Guang-ming, TIAN Je, HE Hui-guang, et al. A mesh smoothing algorithm based on distance equalization[J]. Journal of Computer-Aided Design & Computer Graphics, 2002, 14(9): 820-823.
李光明,田捷,何晖光,等. 基于距离均衡化的网格平滑算法[J]. 计算机辅助设计与图形学学报, 2002,14(9): 820-823.
[13] GUO Hai-xia. Data reconstruction of satellite remote sensing chlorophyll-a in offshore China and the related characteristic of spatial-temporal variations[D]. Xiamen: Third Institute of Oceanography, SOA, 2016.
郭海峡. 中国近海叶绿素卫星遥感数据重构及其时空变化特征研究[D]. 厦门: 国家海洋局第三海洋研究所, 2016.
[14] XU Jian-ping, YANG Yi-ju. The division of boundary between Qiantangjiang River and Hangzhouwan Bay[J]. Journal of Marine Sciences, 2007, 25(1): 44-54.
许建平,杨义菊. 钱塘江与杭州湾河海界线的划分[J]. 海洋学研究, 2007, 25(1): 44-54.
[15] ZHOU Yuan, HAO Yan-ling, LIU Dong-wei, et al. Estimation of suspended particulate matter concentration based on Landsat 8 data in the Yellow River Estuary[J]. Journal of Marine Sciences, 2018, 36(1): 35-45.
周媛,郝艳玲,刘东伟,等. 基于Landsat 8影像的黄河口悬浮物质量浓度遥感反演[J]. 海洋学研究, 2018, 36(1): 35-45.
[16] HE Xian-qiang, BAI Yan, PAN De-lu, et al. Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters[J]. Remote Sensing of Environment, 2013, 133: 225-239.
[17] HE Xian-qiang, BAI Yan, PAN De-lu, et al. Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters[J]. Optics Express, 2012, 20(18): 20 754-20 770.
[18] JIANG Bin-bin, ZHANG Xiao-yu, HUANG Da-song, et al. Retrieving high concentration of suspended sediments based on GOCI: An example of coastal water around Hangzhou Bay, China[J]. Journal of Zhejiang University(Science Edition), 2015, 42(2): 213-220.
江彬彬,张霄宇,黄大松,等. 基于GOCI的近岸高浓度悬浮泥沙遥感反演——以杭州湾及邻近海域为例[J]. 浙江大学学报(理学版), 2015, 42(2): 213-220.