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

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Chinese Journal of oceanology and Limnology 2009年第1期27卷 124-128页

作者：田礼乔陈晓玲张亭禄龚威陈莉琼陆建忠赵羲张伟于之锋 State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University The Key Lab. of Poyang Lake Environment and Resource Utilization Ministry of Education Nanchang University The Key Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education Jiangxi Normal University Laboratory of ocean remote sensing Ministry of Education Ocean Remote Sensing Institute Ocean University of China

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.

关键词： ocean color remote sensing atmospheric correction turbid coastal waters CALIOP MODIS

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

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Acta oceanologica Sinica 2009年第4期28卷 23-31页

作者： BAI Yan HE Xianqiang PAN Delu ZHU Qiankun GONG Fang State Key Laboratory of Satellite ocean Environment Dynamics State Oceanic Administration Hangzhou 310012 China Second Institute of oceanography State Oceanic Administration Hangzhou 310012 China

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.

关键词： Black water Changjiang Estuary Inherent optical properties ocean color remote sensing

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

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Acta oceanologica Sinica 2010年第3期29卷 1-8页

作者： Gustavo Souto Fontes Molleri Milton Kampel Evlyn Mrcia Leo de Moraes Novo National Institute for Space Research-INPE Remote Sensing Division So Jos dos Campos

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.

关键词： ocean color remote sensing amazon river plume spectral behavior cluster analysis

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

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Frontiers of Earth Science 2020年第2期14卷 384-400页

作者： Xia LEI Jiayi PAN Adam DEVLIN Institute of Space and Earth Information Science The Chinese University of Hong KongHong KongChina School of Geography and Environment Jiangxi Normal UniversityNanchang 330022China

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 *** this paper,an ultraviolet(UV)to visible scheme to retrieve CDOM absorption(ag)is developed based on a set of in situ ***,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 *** 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,*** 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 *** algorithm is effective in revealing multiple scales of variation of CDOM absorption from ocean color observations.

关键词： Chromophoric dissolved organic matter ocean color remote sensing Pearl River Estuary ultraviolet

The application of hyperspectral remote sensing to coast environment investigation

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Acta oceanologica Sinica 2009年第2期28卷 1-13页

作者： ZHANG Liang ZHANG Bin CHEN Zhengchao ZHENG Lanfen TONG Qingxi State Key Laboratory of remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Science Beijing 100101 China Naval Institute of Hydrographic Surveying and Charting Tianjin 300061 China Center for Earth Observation and Digital Earth Chinese Academy of Science Beijing 100190 China

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.

关键词： hyperspectral remote sensing coastal zone ocean color remote sensing