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.

Sea ice thickness estimation in the Bohai Sea using geostationary ocean color imager data

A method to estimate the thickness of the sea ice of the Bohai Sea is proposed using geostationary ocean color imager （GOCI） data and then applied to the dynamic monitoring of the sea ice thickness in the Bohal Sea during the winter of 2014 to 2015. First of all, a model is given between the GOCI shortwave broadband albedo and the reflectance of each band with high temporal resolution GOCI data. Then, the relationship model between the sea ice thickness and the GOCI shortwave broadband albedo is established and applied to the thickness extraction of the sea ice in the Bohai Sea. Finally, the sea ice thickness extraction method is tested by the results based on the MODIS data, thermodynamic empirical models （Lebedev and Zubov）, and the in situ ice thickness data. The test results not only indicated that the sea ice thickness retrieval method based on the GOCI data was a good correlation （r2〉0.66） with the sea ice thickness retrieved by the MODIS and thermodynamic empirical models, but also that the RMS is only 6.82 cm different from the thickness of the sea ice based on the GOCI and in situ data.

A general purpose exact Rayleigh scattering look-up table for ocean color remote sensing

The current exact Rayleigh scattering calculation of ocean color remote sensing uses the look-up table （LUT）, which is usually created for a special remote sensor and cannot be applied to other sensors. For practical application, a general purpose Rayleigh scattering LUT which can be applied to all ocean color remote sensors is generated. An adding-doubling method to solve the vector radiative transfer equation in the plane-parallel atmosphere is deduced in detail. Compared with the exact Rayleigh scattering radiance derived from the MODIS exact Rayleigh scattering LUT, it is proved that the relative error of Rayleigh scattering calculation with the adding-doubling method is less than 0.25%, which meets the required accuracy of the atmospheric correction of ocean color remote sensing. Therefore, the adding-doubling method can be used to generate the exact Rayleigh scattering LUT for the ocean color remote sensors. Finally, the general purpose exact Rayleigh scattering LUT is generated using the adding-doubling method. On the basis of the general purpose LUT, the calculated Rayleigh scattering radiance is tested by comparing with the LUTs ofMODIS, SeaWiFS and the other ocean color sensors, showing that the relative errors are all less than 0.5%, and this general purpose LUT can be applied to all ocean color remote sensors.

FY-3A/MERSI, ocean color algorithm, products and demonstrative applications

A medium resolution spectral imager （MERSI） on-board the first spacecraft of the second generation of Chinas polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to thermal infrared spectral region. FY-3A/MERSI is capable of making continuous global observations, and ocean color application is one of its main targets. The objective is to provide information about the ocean color products of FY-3A/MERSI, including sensor calibration, ocean color algorithms, ocean color prod- ucts validation and applications. Although there is a visible on-board calibration device, it cannot realize the on-board absolute radiometric calibration in the reflective solar bands. A multisite vicarious calibration method is developed, and used for monitoring the in-flight response change and providing post-launch cal- ibration coefficients updating. FY-3A/MERSI ocean color products consist of the water-leaving reflectance retrieved from an atmospheric correction algorithm, a chlorophyll a concentration （CHL1） and a pigment concentration （PIG1） from global empirical models, the chlorophyll a concentration （CHL2）, a total sus- pended mater concentration （TSM） and the absorption coefficient of CDOM and NAP （YS443） from Chi- na＇s regional empirical models. The atmospheric correction algorithm based on lookup tables and ocean color components concentration estimation models are described. By comparison with in situ data, the FY-3A/MERSI ocean color products have been validated and preliminary results are presented. Some suc- cessful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.

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.

Ocean color products retrieval and validation around China coast with MODIS

Waters along China coast are very turbid with high concentrations of suspended sediment nearly all the time,especially at the Hangzhou Bay,the Changjiang （Yangtze） River Estuary and the shoal along Jiangsu Province.In these turbid and optically complex waters,the standard MODIS ocean color products tend to have invalid values.Because the water-leaving radiances in the near-infrared （NIR） are significant resulting from the strong scattering of suspended particles,the standard MODIS atmospheric correction algorithm often gets no results or produces significant errors.And because of the complex water optical properties,the OC3 model used in the standard MODIS data processing tends to get extremely high chlorophyll-a （Chl-a） concentrations.In this paper,we present an atmospheric correction approach using MODIS short wave infrared （SWIR） bands based on the fact that water-leaving radiances are negligible in the SWIR region because of the extreme strong absorption of water even in turbid waters.A regional Chl-a concentration estimation model is also constructed for MODIS from in situ data.These algorithms are applied to MODIS Aqua data processing in the China coastal regions.In situ data collected in the Yellow Sea and the East China Sea in spring and autumn,2003 are used to validate the performance.Reasonably good results have been obtained.It is noted that water-leaving reflectance in the NIR bands are significant in waters along the China coast with high sediment loadings.The satellite derived and in-situ reflectance spectra can match in the turbid waters along China coast,and there is relatively good linear relationship between satellite derived and in-situ reflectance.The RMSE value of Rrs（λ） is 0.0031 sr ？1 for all the nine ocean color bands （412 to 869 nm）.The satellite-derived Chl-a value is in the reasonable range and the root mean square percentage difference is 46.1%.

A Real-Time Photo-Realistic Rendering Algorithm of Ocean Color Based on Bio-Optical Model

A real-time photo-realistic rendering algorithm of ocean color is introduced in the paper, which considers the impact of ocean bio-optical model. The ocean bio-optical model mainly involves the phytoplankton, colored dissolved organic material(CDOM), inorganic suspended particle, etc., which have different contributions to absorption and scattering of light. We decompose the emergent light of the ocean surface into the reflected light from the sun and the sky, and the subsurface scattering light. We establish an ocean surface transmission model based on ocean bidirectional reflectance distribution function(BRDF) and the Fresnel law, and this model's outputs would be the incident light parameters of subsurface scattering. Using ocean subsurface scattering algorithm combined with bio-optical model, we compute the scattering light emergent radiation in different directions. Then, we blend the reflection of sunlight and sky light to implement the real-time ocean color rendering in graphics processing unit(GPU). Finally, we use two kinds of radiance reflectance calculated by Hydrolight radiative transfer model and our algorithm to validate the physical reality of our method, and the results show that our algorithm can achieve real-time highly realistic ocean color scenes.

Empirical ocean color algorithm for estimating particulate organic carbon in the South China Sea

We examined regional empirical equations for estimating the surface concentration of particulate organic carbon(POC) in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance,R rs( λ B)/ R rs(555). The best error statistics among the considered formulas were produced using the power function POC(mg/m 3)=262.173 [ R rs(443)/ R rs(555)]- 0.940. This formula resulted in a small mean bias of approximately-2.52%,a normalized root mean square error of 31.1%,and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm,in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-toblue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally,we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.

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 optimal retrieval of ocean color constituent concentrations based on the variational method

In this paper, a new approach to the optimal retrieval of the ocean color based on the variational method is developed by setting up a rational target functional combining with the Broydor Fletcher, Goldfarb, Shanno （BFGS） optimal algorithm. The numerical tests and the exemplary retrievals are carried out and compared with the statistical retrievals and the optimal retrievals based on the genetic algorithm. The results show that this approach enjoys a higher accuracy as compared to the statistical method and a higher efficiency as compared to the genetic algorithm. The optimal retrieval method presented in this paper provides a new idea for the ocean color inversion and could also be used as a reference for the direct assimilation of the satellite data into the ecological models.

The primary results of quantitative ocean color retrieval in China coastal area with CBERS CCD data

Using the techniques of quantitative ocean color sensing, the in-water ocean color algorithms for sediment and chlorophyll-a retrieval are established for CBERS-02 CCD broad spectral bands based on in situ data. The remote sensing reflectance of water is derived from CCD radiance data by a clear water atmospheric correction algorithm. Then, the sediment and chlorophyll-a concentrations are retrieved from CCD image. The sediment retrieval is quite satisfactory, but the chlorophyll-a retrieval is not so good because of the broadband width and low signal-to-noise ratio of the CCD camera.

A Bayesian based quasianalytical algorithm for retrieval of inherent optical properties from ocean color

The recently developed quasi-analytical algo-rithm (QAA) is a promising algorithm for deriving inherentoptical properties from ocean color. Unlike the conventionalsemi-analytical algorithm, QAA does not need a prioriknowledge of the spectral shape of chlorophyll absorption.However, several empirical relations, which may not be uni-versally applicable and can result in low noise tolerance, areinvolved in QAA. In this study, the Bayesian inversion theoryis introduced to improve the performance of QAA. In theestimation of total absorption coefficient at the referencewavelength, instead of empirical algorithms used in the QAAthe Bayesian approach is employed in combination with anoptical model that uses separate parameters to account ex-plicitly for the contribution of molecular and particle scat-terings to remote sensing reflectance, a priori knowledgeproduced by the QAA, the Akaike’s Bayesian informationcriterion (ABIC) for choosing the optimal regularizationparameter, and genetic algorithms for global optimization.Coefficients at other wavelengths are then derived using anempirical estimate of particle backscattering spectral shape.When applied to a simulated dataset synthesized by IOCCG,the Bayesian algorithm outperforms QAA algorithm, espe-cially in higher chlorophyll concentration waters. The rootmean square errors (RMSEs) between the true and the de-rived a(440) and bb(440) are reduced from 0.918 and 0.039m–1 for QAA-555 to 0.367 and 0.023 m–1 for Bayes-555, 0.205and 0.007 m–1 for QAA-640 to 0.092 and 0.005 m–1 forBayes-640, and 0.207 and 0.007 m–1 for QAA-blending to0.096 and 0.005 m–1 for Bayes-blending. Results of noise sen-sitivity analysis show that the Bayesian algorithm is morerobust than QAA.

Spatiotemporal characteristics and remote sensing estimation of colored dissolved organic matter around the Leizhou Peninsula

Colored dissolved organic matter(CDOM)is an important optically active substance in marine environment.Its biochemical conservatism makes it an important indicator to offshore pollution process.Monitoring the content,composition,and diffusion process of CDOM is a good approach to analyze the terrestrial input,optical properties,and ecological environment of offshore areas.The spatiotemporal characteristics of CDOM around the Leizhou Peninsula were analyzed based on field observation data collected in the autumn 2020 and spring 2021,and an empirical inversion model of the ag(355)(absorption coefficient at 355 nm)and spectral slope(Sg)(g stands for gelbstoff/gilvin,which is called CDOM)based on Sentinel-3A ocean and land color instrument(OLCI)images was constructed.The results show(1)the order of average ag(355)value around the Leizhou Peninsula was east coast(0.503/m)>Qiongzhou Strait(0.502/m)>west coast(0.365/m);(2)the best band combinations of CDOM inversion in spring and autumn were(B4+B11)/B3 and(B7-B1)/B6(B stands for the band of spectral images),and the final inversion results are close to the measured results,indicating that the model has good accuracy;(3)the S_(g)value of the CDOM absorption spectrum was fitted to the hyperbolicexponential model.The fitting accuracy of the model was higher than those of the exponential model and the hyperbolic model,and the best S_(g)inversion model was constructed by selecting Sg(275-295)and Sg(250-295)in spring and autumn;(4)the spatial distributions of ag(355)and S_(g)were inverted,and CDOM in the waters around the Leizhou Peninsula originated from terrestrial organic matter carried by coastal aquaculture zones and runoff in the northeast Zhanjiang and the northern Beibu Gulf.

遥感统计推断理论与应用初探

提出一种新的介于遥感分类(定性分析)与遥感反演(定量分析)之间的遥感定性-定量分析方法,即遥感统计推断。遥感统计推断在理论上基于统计光学和概率分布变换,主要研究在一定区域范围内的地物参数的概率分布特征(如土壤的湿度、温度,水体盐度、叶绿素浓度等)如何改变和影响传感器所观测到的光学参数(如地表反射率、水体的遥感反射率等)的概率分布特征(称之为光谱概率分布),以及如何基于传感器观测到的光谱概率分布去反向推断地物参数在此区域内的统计分布特征,从而为刻画地物参数提供相应的定性与定量信息。相比于传统的遥感分类和反演,遥感统计推断的优点在于:(1)能够快速地获取地物参数的全局统计特征,如均值、方差、极值等等,而不需要反演分析每一个像素光谱,这一优点对于当前很多基于大数据、高分辨率的遥感应用尤为重要,因为有些应用部门的管理人员最感兴趣的往往是管理对象(如湖泊、水库、农田)的整体特征,他们并不需要知道在每一个像素处的地物参数的大小;(2)地物的光谱概率分布可以直接用于地物的分类研究,提供了一种有别于基于像素光谱签名特征的传统遥感分类的新分类方法,这种方法提供的是研究区域的整体分类(如一个湖泊的分类)而不是每个像素的分类(如水质的分类);(3)遥感统计推断可以为遥感反演建模提供辅助信息,基于这些信息调整反演模型的函数和/或参数,使得反演模型结果的统计特征与遥感统计推断的结果相匹配。该文简要介绍了遥感统计推断的一些基本概念、原理以及其相较于遥感分类和反演的优势、推断的适用对象和面向推断的遥感数据处理方法,分析了国内主要湖泊水体的光谱概率分布特征,并基于杭州西湖实地采测数据,提出了一种基于自展法(bootstrap-based)的用于推断关键统计分布参数(例如西湖悬浮颗粒浓度的平均值)的简易遥感统计推断方法。

星载GNSS-R检测太湖水华可行性分析

星载全球导航卫星系统反射信号(GNSS-R)属于被动遥感技术,具有数据重访周期高、全天时、全天候、信号源丰富等优势。基于此,研究星载GNSS-R检测太湖水华的可行性。星载GNSS-R可以有效检测反射面的粗糙程度,通过使用相干反射表征反射面的粗糙度,研究不同风速区间内相干反射与蓝藻水华的关系。利用2020年4—8月美国气旋全球导航卫星系统(CYGNSS)数据,计算CYGNSS镜面反射点的时延多普勒图(DDM)功率比。以“哨兵-3”卫星水色遥感仪器(OLCI)影像最大特征峰高度(MPH)算法反演出的太湖叶绿素浓度作为参照,与欧洲中期天气预报中心(ECMWF)的风速产品进行时空间线性匹配,分析发现,在1~2.5 m/s风速区间内,叶绿素浓度达到0.1 mg/L以上时,极易引起镜面反射点发生相干反射,且功率比与叶绿素浓度的相关系数为0.84,具有良好的相关性。实验结果证明了利用星载GNSS-R的功率比及相关特性实现太湖水华检测的可行性。

A new merged dataset of global ocean chlorophyll a concentration with higher spatial and temporal coverage

Understanding the ocean＇s role in the global carbon cycle and its response to environmental change requires a high spatio-temporal resolution of observation.Merging ocean color data from multiple sources is an effective way to alleviate the limitation of individual ocean color sensors（e.g.,swath width and gaps,cloudy or rainy weather,and sun glint） and to improve the temporal and spatial coverage.Since the missions of Sea-Viewing Wide Field-of-View Sensor（Sea Wi FS） and Medium-spectral Resolution Imaging Spectrometer（MERIS） ended on December 11,2010 and May 9,2012,respectively,the number of available ocean color sensors has declined,reducing the benefits of the merged ocean color data with respect to the spatial and temporal coverage.In present work,Medium Resolution Spectral Imager（MERSI）/FY-3 of China is added in merged processing and a new dataset of global ocean chlorophyll a（Chl a） concentration（2000–2015） is generated from the remote sensing reflectance（Rrs（λ）） observations of MERIS,Moderate-resolution imaging spectra-radiometer（MODIS）-AQUA,Visible infrared Imaging Radiometer（VIIRS） and MERSI.These data resources are first merged into unified remote sensing reflectance data,and then Chl a concentration data are inversed using the combined Chl a algorithm of color index-based algorithm（CIA） and OC3.The merged data products show major improvements in spatial and temporal coverage from the addition of MERSI.The average daily coverage of merged products is approximately 24% of the global ocean and increases by approximately 9% when MERSI data are added in the merging process.Sampling frequency（temporal coverage） is greatly improved by combining MERSI data,with the median sampling frequency increasing from 15.6%（57 d/a） to 29.9%（109 d/a）.The merged Chl a products herein were validated by in situ measurements and comparing them with the merged products using the same approach except for omitting MERSI and Glob Colour and MEa SUREs merged data.Correlation and relative error between the new merged Chl a products and in situ observation are stable relative to the results of the merged products without the addition of MERSI.Time series of the Chl a concentration anomalies are similar to the merged products without adding MERSI and single sensors.The new merged products agree within approximately 10% of the merged Chl a product from Glob Colour and MEa SUREs.

台风事件对东中国海悬沙浓度时空演变的影响分析

东海大陆架常受台风侵扰,强风浪在破坏水体结构的同时引起大量泥沙再悬浮。台风是影响东海表层悬沙浓度(suspended sediment concentration,SSC)的主要动力之一。本文将台风类型分为登陆和非登陆两大类共八种。基于GOCI(geostationary ocean color imager)遥感数据统计分析了2017~2020年9个不同类型台风事件对表层悬沙浓度时空分布的影响。结果表明,近海活动型和远海活动型台风使SSC显著增高了150%~200%;随着风速减小,SSC逐渐下降,但需要3~4 d才能恢复至台风之前的SSC。风速变化与SSC变化率的相关性高达0.86。近海及远海活动型台风影响研究区域的风向为偏北风,该类型台风使秋季SSC等值线向外海延伸,出现舌状分布特点;而登陆型台风影响研究区域的风向前期为偏北风,后期为偏南风,该类型台风使SSC等值线呈基本平行向外海移动较短距离,但不出现向外海延伸的舌状分布。近海及远海活动型台风事件使SSC分布迅速向气候态平均天气下的冬季输运类型转变,其中近海活动型台风对SSC分布的影响比远海活动型更显著。登陆型台风对研究区域SSC跨陆架方向分布的影响比远海活动型台风更小。

Effects of Ocean Particles on the Upwelling Radiance and Polarized Radiance in the Atmosphere–Ocean System

Based on a vector radiative transfer model of the atmosphere–ocean system,the influence of oceanic components on radiation processes,including polarization effects,was investigated in the wavelength region ranging from 0.380 to 0.865 μm.The components considered were phytoplankton,inorganic suspended material（sediment）,and colored,dissolved organic matter.Due to their important roles in oceanic radiation processes,the sensitivity of the bidirectional reflectance to the rough ocean surface,represented by the wind velocity 10 m above the ocean surface,and aerosol,were taken into account.The results demonstrated that both radiance and polarized radiance just below the ocean surface were sensitive to the change of the concentrations of the considered components,while the dependence of polarized radiance on the observation geometry was more sensitive than radiance.Significant differences in the specular plane existed between the impacts of the phytoplankton and sediment on the degree of polarization just above the ocean surface at 670 nm.At the top of the atmosphere（TOA）,polarization was relatively insensitive to changing concentrations of ocean particles at longer wavelengths.Furthermore,the radiance at the TOA in the solar plane was more sensitive to the aerosol optical thickness than wind velocity.In contrast,wind velocity strongly influenced the radiance at the TOA in the sun glint region,while the polarization degree showed less dependence in that region.Finally,a nonlinear optimal inversion method was proposed to simultaneously retrieve the aerosol and wind velocity using radiance measurement.

Current Status and Main Application Achievements of Ocean Satellites

Ocean satellites have realized multi-satellite networked operation.The HY-1D satellite launched in June 2020 realized networked with HY-1C satellite,and completed the construction of ocean color satellite constellation.The HY-2D satellite launched in May 2021 is networked with the on orbit HY-2B and HY-2C satellites to complete the construction of marine dynamic environment satellite constellation.The 1 mC-SAR satellite 01 launched in November 2021 is networked with GF-3,which initially forms the marine monitoring satellite constellation.This year,the networking of 1 mC-SAR satellite 02 with satellite 01 and GF-3 is realized,and the construction of marine monitoring satellite constellation is completed.At present,the ocean satellites have the operational application capabilities of remote sensing investigation,monitoring,evaluation and supervision of marine ecology,marine disaster prevention and reduction,global oceans and Polar Regions,Sea Islands,rights and interests maintenance.

Variability in the Light Absorption Coefficient by Phytoplankton,Non-Algal Particles and Colored Dissolved Organic Matter in the Northern Gulf of California

Variability of the optical properties of the northern Gulf of California (México) were analyzed for the first time based on six cruises performed from spring to summer (March to September) between 2008 and 2013. The changes observed in the absorption by three seawater components (phytoplankton, detritus and chromophoric dissolved organic matter or CDOM) were analyzed in relation to changes in bio-optical regions and composition of the phytoplankton community (determined based on phytoplankton pigments). Two regions with unique bio-optical characteristics were identified separated by a narrow transition zone: the Upper Gulf of California (UGC) and Northern Gulf of California (NGC). Despite the temporal changes in their spatial distribution they maintained particular characteristic. UGC is characterized by an average Chla of 1.78 mg/m3, the dominance of microphytoplankton (diatoms and dinoflagellates) and a stronger contribution of detritus to total light absorption. NGC is characterized by an average Chla of 0.7 mg/m3 and the predominance of picophytoplankton, characterized by the dominance of zeaxanthin (marker pigment for cyanobacteria) and/or chlorophyll b (marker pigment for green algae), along with a co-dominium by CDOM and phytoplankton to light absorption. Results indicate that Case II waters can be very different when evaluating the individual contribution by phytoplankton, detritus and CDOM to total light absorption what has to be considered for the selection of bio-optical models for each specific region what can also help to a better definition of the related uncertainties.