Variability of suspended particulate matter in the Bohai Sea from the geostationary Ocean Color Imager (GOCI)

This study assesses the performance of the Geostationary Ocean Imager (GOCI) for mapping of suspended particulate matter in the Bohai Sea, a turbid water region. GOCI imagery for remote sensing reflectance and Total Suspended Solids (TSS) is analysed in detail for two days in June 2011 (8 images per day). Both instantaneous and daily composite maps are considered and a comparison is made with corresponding reflectance and TSS products from MODIS-AQUA. Results show TSS distributions corresponding to previous studies of the region. The advantage of the higher acquisition frequency (8 images/day instead of 1) offered by GOCI is clearly demonstrated in the daily composite which is more complete during this period of scattered but moving clouds. Consideration of temporal variation over the day indicates low natural variability but some artificial variability from processing errors ?? this analysis provides a first indication of how the higher frequency of data from geostationary ocean colour could lead to improved data quality control via temporal coherency outlier detection. While there is room for improvement on the GOCI calibration, atmospheric correction and retrieval algorithms, the current study suggests that the GOCI data can already be used now to study qualitatively sediment dynamics except in the extremely turbid waters which are masked out of the current dataset. In a wider context, it is considered that the technical challenges of geostationary ocean colour have been met by the GOCI concept, and, notwithstanding potential improvements on the concept and data processing methods, it is recommended that this mission serve as a model for future geostationary ocean colour sensors over Europe/Africa and the Americas.     

Evaluation of GOCI sensitivity for At-Sensor radiance and GDPS-Retrieved chlorophyll-a products

The signal-to-noise ratio (SNR, or sensitivity) of an ocean color instrument is a critical parameter to determine the accuracy and precision of the data products. Yet published literature showed various formats in SNR specifications under different conditions, making a direct cross-sensor comparison difficult. Here, we compared the SNRs of GOCI spectral bands with those of SeaWiFS and MODIS/Aqua under the same radiance inputs. We also compared their ability to resolve small changes in the retrieved chlorophyll-a data products (Chl). While GOCI visible bands showed similar at-sensor SNRs to SeaWiFS, the near-infrared (NIR) bands showed significantly higher SNRs. Because the NIR bands were used for atmospheric correction, the increases in SNRs led to reduced noise in the retrieved Chl, as shown in the GOCI and SeaWiFS Chl products for Chl < 0.1 mg m^?3. The noise in the retrieved products also depends on the retrieval algorithms in addition to the sensor SNR. When a new band-subtraction algorithm (the Ocean Color Index or OCI algorithm) was applied to the same GOCI remotesensing reflectance data derived from the GDPS software package, significant noise reduction was found in the Chl product for low concentrations (< 0.25 mg m^?3), leading to product precision (??3% in Chl) comparable to those from MODIS/Aqua measurements. This is certainly a significant achievement, as GOCI spatial resolution is much higher than MODIS (500 m versus 1 km). In addition, artifacts across image mosaic edges over low-concentration waters have been removed nearly completely by the OCI algorithm. Data analyses also indicated that GOCI radiometric calibration requires further improvement.     

Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS

Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.     

Assessment of GOCI radiometric products using MERIS, MODIS and field measurements

The first Geostationary Ocean Color Imager (GOCI) launched by South Korea in June 2010 constitutes a major breakthrough in marine optics remote-sensing for its capabilities to observe the diurnal cycles of the ocean. The light signal recorded at eight wavelengths by the sensor allows, after correction for Solar illumination and atmospheric effects, the retrieval of coloured biogeochemical products such as the chlorophyll, suspended sediment and coloured dissolved organic matter concentrations every hour between 9:00 am and 4:00 pm local time around the Korean peninsula. However operational exploitation of the mission needs beforehand a sound validation of first the radiometric calibration, i.e. inspection of the top-of-atmosphere reflectance, and second atmospheric corrections for retrieval of the water-leaving reflectance at sea surface. This study constitutes a contribution to the quality assessment of the GOCI radiometric products generated by the Korea Ocean Satellite Center (KOSC) through comparison with concurrent data from the MODerate-resolution Imaging Spectroradiometer (MODIS, NASA) and MEdium Resolution Imaging Spectrometer (MERIS, ESA) sensors as well as in situ measurements. These comparisons are made with spatially and temporally collocated data. We focus on Rayleigh-corrected reflectance (?? _RC ) and normalized remote-sensing marine reflectance (nRrs). Although GOCI compares reasonably well with MERIS and MODIS, what demonstrates the success of Ocean Colour in geostationary orbit, we show that the current GOCI atmospheric correction systematically masks out data over very turbid waters and needs further examination and correction for future release of the GOCI products.     

Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI)

This paper describes an atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI) and its early phase evaluation. This algorithm was implemented in GOCI Data Processing System (GDPS) version 1.1. The algorithm is based on the standard SeaWiFS method, which accounts for multiple scattering effects and partially updated in terms of turbid case-2 water correction, optimized aerosol models, and solar angle correction per slot. For turbid water correction, we used a regional empirical relationship between water reflectance at the red (660 nm) and near infrared bands (745 nm and 865 nm). The relationship was derived from turbid pixels in satellite images after atmospheric correction, and processed using aerosol properties derived for neighboring non-turbid waters. For validation of the GOCI atmospheric correction, we compared our results with in situ measurements of normalized water leaving radiance (nL _w ) spectra that were obtained during several cruises in 2011 around Korean peninsula. The match up showed an acceptable result with mean ratio of the GOCI to in situ nL _w (??), 1.17, 1.24, 1.26, 1.15, 0.86 and 0.99 at 412 nm, 443 nm, 490 nm, 555 nm, 660 nm and 680 nm, respectively. It is speculated that part of the deviation arose from a lack of vicarious calibration and uncertainties in the above water nLw measurements.     

Spatial scales of mesoscale eddies from GOCI Chlorophyll-a concentration images in the East/Japan Sea

The spatial scales of mesoscale eddies are of importance to understand physio-biogeochemical processes in the East/Japan Sea. Chlorophyll-a concentration images from the Geostationary Ocean Color Imager (GOCI) revealed numerous eddies during the phytoplankton bloom in spring. These eddies were manually digitized to obtain geolocation information at the peripheries from GOCI images and then least-square fitted to each ellipse. The elliptic elements were the geolocation position of the eddy center, the rotation angle from due east, the eccentricity, the lengths of the semi-major and semi-minor axes, and the mean radius of the ellipse. The spatial scales of eddies had a mean radii ranging from 10 km to 75 km and tended to be smaller in the northern region. The scales revealed a linear trend of about ?7.26 km/°N as a function of the latitude. This tendency depended on the latitudinal variation of the internal Rossby radius of deformation, which originates from the substantial difference in the density structure of the water column. The scales from the sea surface temperature image were larger by 1.30 times compared to those from ocean color image. This implies that physical processes along the periphery of the eddy affect the nutrient dynamics.     

Down-scaled regional ocean modeling system (ROMS) for high-resolution coastal hydrodynamics in Korea

A down-scaled operational oceanographic system is developed for the coastal waters of Korea using a regional ocean modeling system(ROMS).The operational oceanographic modeling system consists of atmospheric and hydrodynamic models.The hydrodynamic model,ROMS,is coupled with wave,sediment transport,and water quality modules.The system forecasts the predicted results twice a day on a 72 h basis,including sea surface elevation,currents,temperature,salinity,storm surge height,and wave information for the coastal waters of Korea.The predicted results are exported to the web-GIS-based coastal information system for real-time dissemination to the public and validation with real-time monitoring data using visualization technologies.The ROMS is two-way coupled with a simulating waves nearshore model,SWAN,for the hydrodynamics and waves,nested with the meteorological model,WRF,for the atmospheric surface forcing,and externally nested with the eutrophication model,CE-QUAL-ICM,for the water quality.The operational model,ROMS,was calibrated with the tidal surface observed with a tide-gage and verified with current data observed by bottom-mounted ADCP or AWAC near the coastal waters of Korea.To validate the predicted results,we used real-time monitoring data derived from remote buoy system,HF-radar,and geostationary ocean color imager(GOCI).This down-scaled operational coastal forecasting system will be used as a part of the Korea operational oceanographic system(KOOS) with other operational oceanographic systems.     

Impact of multiple satellite ocean color samplings in a day on assessing phytoplankton dynamics

Ocean-color imagers on conventional polar-orbiting satellites have a revisit time of ??2 days for most regions, which is further reduced if the area is frequently cloudy. The Geostationary Ocean Color Imager (GOCI), the first ocean-color imager on a geostationary satellite, provides measurements 8 times a day, thus significantly improving the frequency of measurements for studies of ocean environments. Here, we use results derived from GOCI measurements over Taihu Lake to demonstrate that the extra sampling can be used to improve the accuracy of statistically averaged longer-term (daily) measurements. Additionally, using numerical simulations, we demonstrate that the coupling of diurnal variations of both biomass and photosynthetic available radiation can improve the accuracy of daily primary production estimates. These results echo that higher sampling frequency can improve our estimates of longer-term dynamics of biogeochemical processes and highlights the value of ocean color measurements from geostationary satellites.     

基于DINEOF的静止海洋水色卫星数据重构方法研究

静止轨道海洋水色成像仪(Geostationary Ocean Color Imager, GOCI)提供了时间分辨率达小时级的海洋水色数据,使得对海洋环境的逐时变化监测成为可能。然而受到海洋上空云、雾和霾的影响,数据出现连续高缺失率甚至完全缺失的情况,使得数据使用价值大大降低。在经验正交函数重构法(Data INterpolating Empirical Orthogonal Functions, DINEOF)的基础上,突出时间要素在重构中的地位,运用异常像元检测、拉普拉斯平滑滤波和时间模态2次分解插值,提出了适用于静止海洋水色卫星数据的重构方法——DINEOF-G。利用此方法对杭州湾2017年的GOCI总悬浮物质量浓度数据进行重构,结果表明该方法相比经典方法在重构精度上提高了8%,数据重构率提高了36%,且重构结果较好地反映了杭州湾总悬浮物质量浓度的季节变化规律和空间分布特征。     

基于GOCI数据渤海海冰厚度算法研究

提出一种基于GOCI数据提取渤海海冰厚度方法并将其应用于2014年-2015年冬季渤海海冰厚度动态变化监测。首先基于高时间分辨率的GOCI数据建立GOCI短波宽带反射率与各波段反射率模型,然后建立海冰厚度与GOCI短波宽带反射率模型,并将此模型应用于渤海海冰厚度监测,最后通过基于MODIS数据、热动力学模型（Lebedev和Zubov模型）反演获得的海冰厚度以及实测海冰厚度数据对实验结果进行验证。实验结果表明：基于GOCI数据建立海冰厚度模型所反演的海冰厚度与基于MODIS数据反演的海冰厚度以及Lebedev和Zubov模型具有较高相关性（R2>0.86）,而且反演结果接近实测数据（RMS为6.82 cm）。     

Estimating photosynthetically available radiation at the ocean surface from GOCI data

A technique is presented to estimate photosynthetically available radiation (PAR) at the ocean surface from Geostationary Ocean Color Imager (GOCI) data. The sensor is adapted to the problem, since it measures at visible wavelengths and does not saturate over clouds, and the hourly data provides adequate temporal sampling to describe diurnal variability of clouds. Instantaneous surface PAR is computed as the difference between the solar irradiance incident at the top of the atmosphere (known) and the solar irradiance reflected back to space (derived from GOCI radiance), taking into account absorption and scattering by the clear atmosphere (modeled). Knowledge of pixel composition is not required. Apart from planetary albedo and sun zenith angle, the model parameters are fixed at their climatological values. The instantaneous PAR estimates at hourly intervals are integrated over time to provide daily values. The technique is applied to GOCI imagery acquired on 5 April 2011, and the GOCI daily PAR estimates are compared with those obtained from MODerate Resolution Imaging Spectrometer (MODIS) data. Agreement is good between the two types of estimates, with a coefficient of determination (r ²) of 0.778, a bias of 0.23 Em^?2d^?1 (0.5% with higher GOCI values), and a root-mean-squared difference of 5.00 Em^?2d^?1 (11.2%). Differences in cloudy conditions are attributed to daily cloudiness changes not captured by the MODIS observations. The comparison statistics indicate that GOCI PAR estimates have acceptable accuracy for regional studies of aquatic photosynthesis.     

MODIS和GOCI卫星遥感反射率产品在浑浊海区交叉检验分析

对Geostationary Ocean Color Imager(GOCI)和Moderate Resolution Imaging Spectroradiometer(MODIS)传感器在中国渤海辽东湾海区的卫星大气校正算法开展评估工作。主要对比了GOCI和MODIS的412 nm,443 nm,488 nm,547 nm,678 nm波段的遥感反射率(Remote Sensing Reflectance:Rrs)。结果表明:GOCI的去云算法较严格,在卫星有效数据覆盖率方面差于MODIS;遥感反射率产品比对结果表明:GOCI和MODIS的遥感反射率产品有较好的线性相关,且GOCI反演值大于MODIS反演值;分区域的对比结果表明,MODIS和GOCI的遥感反射率差异随着水体的浑浊度增加而增大,GOCI需要开发适用于近岸水体的大气校正算法。     

利用FY-4A气象卫星观测海洋内波

随着遥感技术的迅猛发展,可用于观测海洋内波的数据源越来越丰富。本文基于静止轨道气象卫星连续观测的优势,开展了FY-4A气象卫星海洋内波观测研究。首先计算得到了FY-4A遥感影像耀斑区位置,并基于遥感影像对结果进行了验证;然后,以此为依据选择了适用于内波观测的FY-4A数据,对比了FY-4A与MODIS遥感影像成像的差异,表明了在一定条件下FY-4A遥感影像可观测到海洋内波;最后本文利用FY-4A遥感影像计算了内波的传播速度。本研究表明随着遥感器空间分辨率的提高,静止轨道气象卫星在海洋内波观测方面越来越体现出其优势,为海洋内波的研究提供跟踪观测数据。     

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 China’s 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 products 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 calibration 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 suspended mater concentration (TSM) and the absorption coefficient of CDOM and NAP (YS443) from China’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 successful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.     

基于GOCI静止水色卫星数据的长江口及邻近海域Kd(490)遥感反演及其在机载激光测深预评估中的应用

长江口水下三角洲地形地貌对于长江口航道安全、生态环境、海岸带工程等均具有重要意义,本次研究拟采用世界上第一颗静止水色卫星GOCI(Geostationary Ocean Color Imager)开展长江口Kd(490)的季节和潮汐变化规律研究,以期为采用机载激光测深提供预评估信息。研究得到结论如下:长江口及邻近海域水体为典型的二类水体,悬浮泥沙含量最高可由杭州湾内几千mg/L迅速降低至10 mg/L以下,因此,分段式的漫衰减系数反演算法适用于研究区域;Kd(490)反演结果表明长江口及邻近海域的Kd(490)值的季节变化特征表现为冬高夏低,春秋居中,长江冲淡水流量和季风是影响其季节变化的主要因素,而在一个潮周期内,Kd(490)值总体表现为低潮期低于高潮期,悬浮泥沙浓度和潮水的潮位是长江口及邻近海域的Kd(490)值的重要影响因素;研究指出,长江口及杭州湾内激光可探测深度约在5~22 m范围内,夏季退潮低潮位最适合激光雷达观测。由此可见,GOCI 8景/d,1景/h的分辨率可以实现Kd(490)的动态变化监控,而且可以实现在相同潮位下更为合理地描述Kd(490)值的季节变化,为机载激光雷达探测的进一步开展提供了技术支持。     

A study on quality and availability of COCTS images of HY-1 satellite by simulation

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Detecting massive green algae (Ulva prolifera) blooms in the Yellow Sea and East China Sea using Geostationary Ocean Color Imager (GOCI) data

The historically massive bloom of the green macroalgae Ulva prolifera reported in June?CAugust 2008 around the Qingdao, Yellow Sea, East China Sea and Japan coasts has recurred in a similar season and region. On June 13, 2011, around Qingdao, China, the world??s first Geostationary Ocean Color Imager (GOCI) detected an enormous bloom of floating green algae, which originated from the nearshore Subei Bank, China. The large floating green algae patches were observed along and across the Yellow Sea and in the East China Sea during 2011 summer by various oceanic cruises. To detect the massive macroalgae blooms from space, we analyzed their spectral characteristics from in situ optical measurements and satellite-derived green algae spectra. An ??Index of floating Green Algae for GOCI?? (IGAG) was developed from the multiple spectral band ratios using three wavelengths (555, 660, 745 nm), which the spectral response of green algae reflected at 555, 745, and 865 nm and absorbed at 660 and 680 nm. The results were compared with those obtained by the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and Korea Ocean Satellite Center (KOSC) approaches. An advantage of the IGAG method was that muted or subtle signals of floating green algae were enhanced and separated from surrounding complex water signals. Although maps of floating green algae derived by the other approaches delineated dense green algae, they were less sensitive to subtle (less dense) features and in cases of nearby cloudy or complex water conditions. The floating green algae maps from IGAG provided a more robust estimate of wide floating green algae blooms than those derived using NDVI, EVI, or KOSC approaches. The IGAG approach should be useful for tracing and monitoring changes in green algae blooms on regional and global scales.     

基于GOCI影像的长江口及其邻近海域CDOM遥感反演及其日内变化研究

采用静止轨道海洋水色卫星（GOCI）数据对长江口及其邻近海域有色溶解有机物（CDOM）反演。以QAA-CDOM算法为基础,根据实测数据,利用BP神经网络模型来拟合QAA-CDOM算法中需要针对长江口水体进行优化的悬浮颗粒后向散射系数b_bp与吸收系数a_p的关系,从而准确估算CDOM的浓度。结果表明,反演结果准确度较高,平均相对误差为0.35。基于GOCI日内连续成像的优势,选取2014年3月15日8景GOCI影像,利用优化后的QAA-CDOM-BP算法,对长江口及其邻近海域CDOM的日内变化进行反演和分析,得到的变化规律如下:长江口及其邻近海域的CDOM日变化主要受潮流、长江径流等共同影响。长江口内CDOM浓度在涨潮期高于退潮期,由于受长江冲淡水的作用,CDOM从口外往外海区呈现逐渐递减趋势。     

东海试验区水体光谱特性现场测量与数据分析

星载水色遥感器 Ｓｅａ Ｗｉ Ｆ Ｓ 已业务化地为海洋学家提供高质量的海洋水色遥感数据。要有效地利用水色遥感数据,需要经常地对遥感器进行定标,并对测得的离水辐射率以及导出的生物—光学特性进行真实性检验。１９９８ 年５ 月, 我们在东海试验区,应用多光谱剖面／ 表面辐射仪（ Ｓ Ｐ Ｍ Ｒ／ Ｓ Ｍ Ｓ Ｒ） ,进行了光谱测量。本文介绍了现场测量的方法,以及根据我国海区的特点对实测数据的处理结果     

中国海洋水色遥感器瑞利散射定标研究

水色遥感是海洋环境监测的主要技术手段之一.对于任何海洋水色遥感器来说,监测其在轨期间的定标系数变化是非常重要的,否则无法得到精确的定量产品.以我国“HY-1B”卫星水色遥感器为研究对象,开展了基于大洋水体上空的瑞利散射定标方法研究,利用通过对SeaWiFS数据叶绿素、离水辐亮度和气溶胶产品进行分析,选择了符合条件的7个海区实施大气瑞利散射定标,根据2010年12月份选定的4个区域定标结果得到不同海区/不同时间获得的定标系数一致性较好,CH1至CH6的定标系数标准差分布在0.9％～2.1％的范围内,因此瑞利散射定标是有效的非现场定标方法,具有较高的定标精度,其总误差在4.09％.