Using ocean colour remote sensing products to estimate turbidity at the Wadden Sea time series station Spiekeroog

被引:40
|
作者
Garaba, S. P. [1 ]
Badewien, T. H. [1 ]
Braun, A. [1 ]
Schulz, A. -C. [1 ]
Zielinski, O. [1 ]
机构
[1] Carl von Ossietzky Univ Oldenburg, Inst Chem & Biol Marine Environm Terramare, D-26382 Wilhelmshaven, Germany
关键词
Turbidity; ocean colour remote sensing; time series; water quality; SUSPENDED PARTICULATE MATTER; ABOVE-WATER; COASTAL WATERS; PHYTOPLANKTON; REFLECTANCE;
D O I
10.2971/jeos.2014.14020
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Time series measurements at the Wadden Sea time series station Spiekeroog (WSS) in the southern North Sea were used to empirically develop approaches for determining turbidity from ocean colour remote sensing products (OCPs). Turbidity was observed by a submerged optical sensor. Radiometric quantities were collected using hyperspectral radiometers. Surface reflected glint correction was applied to the radiometric quantities to compute remote sensing reflectance (R-RS) and the R-RS was converted into perceived colour of seawater matching the Forel-Ule colour Index (FUI) scale. The empirical approaches for determining turbidity from OCPs showed good least squares linear correlations and statistical significance (R-2 > 0.7, p < 0.001). These OCP approaches had relatively low uncertainties in predicting turbidity with encouraging mean absolute percent difference less than 31 %. The problem of bio-fouling on submerged sensors and the potential application of OCPs to monitor or correct for sensor drifts was evaluated. A protocol is proposed for the acquisition and processing of hyperspectral radiometric measurements at this optically complex station. Use of the classic FUI as a time series indicator of surface seawater changes did show promising results. The application of these OCPs in operational monitoring changes in water quality was also explored with the aim to evaluate the potential use of the WSS datasets in calibration and validation of satellite ocean colour remote sensing of these very turbid coastal waters.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] ASSESSMENT OF ENVIRONMENTAL CHANGE AND LAND DEGRADATION USING TIME SERIES OF REMOTE SENSING IMAGES
    Kavzoglu, Taskin
    Colkesen, Ismail
    FRESENIUS ENVIRONMENTAL BULLETIN, 2011, 20 (1A): : 274 - 281
  • [42] Study on the Vegetation Dynamic Change Using Long Time Series of Remote Sensing Data
    Fan Jinlong
    Zhang Xiaoyu
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XII, 2010, 7824
  • [43] Production Capacity Evaluation of Farmland Using Long Time Series of Remote Sensing Images
    Lu, Mei
    Gu, Xiaohe
    Sun, Qian
    Li, Xu
    Chen, Tianen
    Pan, Yuchun
    AGRICULTURE-BASEL, 2022, 12 (10):
  • [44] Multiple-Scale Variations of Sea Ice and Ocean Circulation in the Bering Sea Using Remote Sensing Observations and Numerical Modeling
    Dong, Changming
    Gao, Xiaoqian
    Zhang, Yiming
    Yang, Jingsong
    Zhang, Hongchun
    Chao, Yi
    REMOTE SENSING, 2019, 11 (12)
  • [45] Estimation of primary production in the Arctic Ocean using ocean colour remote sensing and coupled physical-biological models: Strengths, limitations and how they compare
    Babin, M.
    Belanger, S.
    Ellingsen, I.
    Forest, A.
    Le Fouest, V.
    Lacour, T.
    Ardyna, M.
    Slagstad, D.
    PROGRESS IN OCEANOGRAPHY, 2015, 139 : 197 - 220
  • [46] A comparison of methods for smoothing and gap filling time series of remote sensing observations - application to MODIS LAI products
    Kandasamy, S.
    Baret, F.
    Verger, A.
    Neveux, P.
    Weiss, M.
    BIOGEOSCIENCES, 2013, 10 (06) : 4055 - 4071
  • [47] Spatial-Temporal Variations of Turbidity and Ocean Current Velocity of the Ariake Sea Area, Kyushu, Japan Through Regression Analysis with Remote Sensing Satellite Data
    Arai, Kohei
    Sarusawa, Yuichi
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2013, 4 (03) : 20 - 25
  • [48] Correlation analysis of the sea surface features under eddy modulation in the global ocean using remote sensing data
    Huang, Chunming
    Chen, Xiaoyan
    Wang, Xuan
    Chen, Ge
    National Remote Sensing Bulletin, 2024, 28 (08) : 2002 - 2013
  • [49] A high-frequency time series at ocean Weather ship station M (Norwegian Sea):: population dynamics of Calanus finmarchicus
    Hirche, HJ
    Brey, T
    Niehoff, B
    MARINE ECOLOGY PROGRESS SERIES, 2001, 219 : 205 - 219
  • [50] Changes in ecosystem service values in Zhoushan Island using remote sensing time series data
    Zhang, Xiaoping
    Qin, Yanpei
    Lyu, Ying
    Zhen, Guangwei
    Gong, Fang
    Li, Chaokui
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XIX, 2017, 10421