Study on detection of coastal water environment of China by ocean color remote sensing

Coastal water environment is essentially enhanced by ocean color which is basically decided by substances concentration in water such as chlorophyll, suspended material and yellow substance. It is very difficult, even not possible, to detect water color by expensive ship routing, because of its temporal and spatial variety of feature and scales in the very complicated dynamical system of coastal water. With the development of satellite technique in the last 20 a, space sensors can be applied to detect ocean color by measuring the spectra of water leaving radiance.It is proven that ocean color remote sensing is a powerful tool for understanding the process of oceanic biology and physics. Since the 1980s, great attention has been paid to the advanced remote sensing technique in China, especially to development of satellite programs for the coastal water environment. On 7 September 1988, China launched her first polar orbit satellite FY-1A for meteorological and oceanographic application (water color and temperature) and the second satellite FY-1B two years later. In May 1999, China launched her second generation environment satellite FY-1C with higher sensitivies, more channels and stable operation. The special ocean color satellite HY-1 is planned to be in the orbit in 2001, whose main purpose is to detect the coastal water environment of China seas. China is also developing a very advantageous sensor termed as Chinese moderate imaging spectra radiometer (CMODIS) with 91 channels, which will be a good candidate of the third generation satellite FY-3 in 2003. The technical system of ocean color remote sensing was developed by the Second Institute of Oceanography (SIO), State Oceanic Administration (SOA) in 1997. The system included data receiving, processing, distribution, calibration, validation and application units. The Hangzhou Station of SIO, SOA has the capability to receive FY-1 and AVHRR data since 1989. It was also a SeaWiFS scientific research station authorized by NASA,USA to free receive SeaWiFS data from 16 September 1997. In the recent years, the local algorithms of atmospheric correction and inversion of ocean color have been developed for FY-1C and SeaWiFS, to improve the accuracy of the measurement from satellites efficiently. The satellite data are being applied to monitor coastal water environment, such as the spatial distribution of chlorophyll, suspended material and yellow substance, red tide detection and coastal current study. The results show that the ocean color remote sensing has latent capacity in the detection of coastal water environment.In consideration of the update technique progress of ocean color remote sensing and its more important role in the detection of coastal water in the 2000s, some suggestions are set forth, which would be beneficial to the design of a cheaper but practical coastal water detection system for marine environment preservation.

Progress in the application of ocean color remote sensing in China

After many years＇ endeavor of research and application practice, the ocean color remote sensing in China has been growing into a new technique with valuable practicality from its initiate stage of trial research. With the aim of operational service, several kinds of ocean color remote sensing application systems have been developed and realized the long-term marine environmental monitoring utilizing the real-time or near real-time satellite and airborne remote sensing data. New progresses in the technology and application of ocean color remote sensing in China are described, including the research of key techniques and the development of various application systems. Meanwhile, according to the application status and demand, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite （ HY-1 B） orbiting on 11 April 2007 and the development of airborne ocean color remote sensing system for Chinese surveillance planes, great strides will take place in Chinese ocean color remote sensing application with the unique function in marine monitoring, resources management and national security, etc.

Atmospheric correction of ocean color imagery over turbid coastal waters using active and passive remote sensing

This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) aerosol data, assuming that there exists "nonturbid" water in the study area where MODIS aerosol optical properties can be retrieved accurately. Aerosol properties from CALIOP measurements were obtained and related to those from MODIS. This relationship, combined with CALIOP aerosol data, was extended to turbid water to derive MODIS aerosol properties, where atmospheric correction using MODIS data alone often fails. By combining MODIS and CALIOP data, aerosol signals were separated from the total signals at the satellite level, and water-leaving radiances in turbid waters were subsequently derived. This method was tested on several MODIS/Aqua ocean color images over South China turbid waters. Comparison with field data shows that this method was effective in reducing the errors in the retrieved water-leaving radiance values to some extent. In the Zhujiang (Pearl) River Estuary, this method did not overestimate the aerosol effects as severely, and provided far fewer negative water-leaving radiance values than the NASA (National Aeronautics and Space Administration) default methods that used MODIS data alone.

The application of hyperspectral remote sensing to coast environment investigation

Requirements for monitoring the coastal zone environment are first summarized. Then the appli- cation of hyperspectral remote sensing to coast environment investigation is introduced, such as the classification of coast beaches and bottom matter, target recognition, mine detection, oil spill identification and ocean color remote sensing. Finally, what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

Satellite-observed significant improvement in nearshore transparency of the Bohai Sea during pollution control

The Bohai Sea(BS)is the unique semi-closed inland sea of China,characterized by degraded water quality due to significant terrestrial pollution input.In order to improve its water quality,a dedicated action named“Uphill Battles for Integrated Bohai Sea Management”(UBIBSM,2018–2020)was implemented by the Chinese government.To evaluate the action effectiveness toward water quality improvement,variability of the satelliteobserved water transparency(Secchi disk depth,Z_(SD))was explored,with special emphasis on the nearshore waters(within 20 km from the coastline)prone to terrestrial influence.(1)Compared to the status before the action began(2011–2017),majority(87.3%)of the nearshore waters turned clear during the action implementation period(2018–2020),characterized by the elevated Z_(SD)by 11.6%±12.1%.(2)Nevertheless,the improvement was not spatially uniform,with higher Z_(SD)improvement in provinces of Hebei,Liaoning,and Shandong(13.2%±16.5%,13.2%±11.6%,10.8%±10.2%,respectively)followed by Tianjin(6.2%±4.7%).(3)Bayesian trend analysis found the abrupt Z_(SD)improvement in April 2018,which coincided with the initiation of UBIBSM,implying the water quality response to pollution control.More importantly,the independent statistics of land-based pollutant discharge also indicated that the significant reduction of terrestrial pollutant input during the UBIBSM action was the main driver of observed Z_(SD)improvement.(4)Compared with previous pollution control actions in the BS,UBIBSM was found to be the most successful one during the past 20 years,in terms of transparency improvement over nearshore waters.The presented results proved the UBIBSM-achieved remarkable water quality improvement,taking the advantage of long-term consistent and objective data record from satellite ocean color observation.

The statistic inversion algorithms of water constituents for the Huanghai Sea and the East China Sea

A group of statistical algorithms are proposed for the inversion of the three major components of CaseII waters inthe coastal area of the Huanghai Sea and the East China Sea. The algorithms are based on the in situ data collected inthe spring of 2003 with strict quality assurance according to NASA ocean bio-optic protocols. These algorithms arethe first ones with quantitative confidence that can be applied for the area. The average relative error of the inversedand in situ measured components' concentrations are: Chl-a about 37%, total suspended matter (TSM) about 25%,respectively. This preliminary result is quite satisfactory for CaseII waters, although some aspects in the modelneed further study. The sensitivity of the input error of 5% to remote sensing reflectance (Rrs) is also analyzed andit shows the algorithms are quite stable. The algorithms show a large difference with Tassans local SeaWiFSalgorithms for different waters, except for the Chl-a algorithm.

The black water around the Changjiang (Yangtze) Estuary in the spring of 2003

The Changjiang （Yangtze） Estuary is located in the East China Sea shelf with shallow water. Affected by the tide mixing and the runoff of the Changjiang River and the Qiantang River the turbidity is very high. Generally, the water-leaving radiance is high in the turbid water because of the large particle scattering. Based on the in-situ data and ocean color remote sensing data of SeaWiFS, it was found that there was a black water region with the normalized water-leaving radiances less than 0.5 mW/（cm2-μm2-sr）. The optical principle of the occurrence of this black water was analyzed by the inherent optical properties and the ocean color components. The results show that black water is caused by the relative low values of the suspended particle matter concentration and the back scattering ratio. In the black water region, the percentage of the phytoplankton absorption was relatively high, and the large size of the phytoplankton caused the low value of the particle backscattering ratio.

Spectral classification of water masses under the influence of the Amazon River plume

The large amount of dissolved and particulate material discharged by the Amazon River into the Equatorial Atlantic Ocean cause distinct spectral response of its waters as compared to the nearby ocean waters. This paper shows the application of K-means clustering algorithm for classifying water masses in the region under the Amazon River plume influence according to their spectral behavior. Salinity and temperature data from 67 oceanographic stations were related to Sea-viewing Wide Field-of-view Sensor （SeaWiFS） remote sensing reflectances values and the following bio-optical products： （i） chlorophyll-a concentration, （ii） water attenuation coefficient and （iii） absorption coefficient for dissolved and detrital material. Four different water masses were identified such as： （1） oceanic water, （2） intermediate oceanic water, （3） intermediate river plume water and （4） Amazon River plume water. The spectral behavior of these water masses allowed concluding that the main active optical component of the waters in the region is the colored dissolved organic matter originated mostly from the Amazon River.

Performance evaluation of operational atmospheric correction algorithms over the East China Seas

To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) were evaluated over the East China Seas(ECS) using MERIS data. The spectral remote sensing reflectance R_(rs)(λ), aerosol optical thickness(AOT), and ?ngstr?m exponent(α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R_(rs), AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R_(rs)(λ) showed a mean percentage difference(MPD) of 9%–13% in the 490–560 nm spectral range, and significant overestimation was observed at 413 nm(MPD>72%). The AOTs were overestimated(MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm(MPD=41%) but not by the NASA algorithm(MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo(SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.

An ultraviolet to visible scheme to estimate chromophoric dissolved organic matter absorption in a Case-2 water from remote sensing reflectance

In a typical Case-2 coastal water environment(here,the Pearl River Estuary(PRE),China),chromophoric dissolved organic matter(CDOM)and suspended particulates dominate the water optical properties,and CDOM fluorescence contributes considerably to surface water reflectance.In this paper,an ultraviolet(UV)to visible scheme to retrieve CDOM absorption(ag)is developed based on a set of in situ observations.First,the CDOM UV absorption and spectral slope(Sg)are derived directly from the visible remote sensing reflectance;then the Sg is extrapolated to obtain the spectrum from UV to visible spectral range.This algorithm performs well,with an overall mean absolute percent difference(MAPD)of^30%,~5%and^6%for the estimation of ag in 250–450 nm,Sg over 250–400 nm,and 250–700 nm,respectively.The effectiveness and stability of the algorithm is further demonstrated in capturing the distribution pattern of CDOM absorption in the PRE from satellite ocean color imagery with multiple spatial and spectral resolution,namely:the Visible Infrared Imaging Radiometer Suite(VIIRS)(750 m/Multispectral),the Ocean and Land Color Instrument(OLCI)(300 m/Multispectral),the Hyperspectral Imager for the Coastal Ocean(HICO)(100 m/Hyperspectral),and the Landsat 8 Operational Land Imager(OLI)(30 m/Multispectral).The UV to visible scheme can benefit the CDOM absorption estimation in two aspects:1)it is free from the disturbance of suspended matter;2)it avoids uncertainties caused by the low signalto-noise ratio(SNR)of ag measurements in the visible range.The algorithm is effective in revealing multiple scales of variation of CDOM absorption from ocean color observations.