黄、东海区总悬浮泥沙对HY-1 CCD数据叶绿素浓度反演的影响

悬浮泥沙含量对叶绿素浓度遥感反演具有一定的抑制作用,我国近岸水体受其影响更为严重.利用国家卫星海洋应用中心组织的2003年春季大规模黄、东海区海上试验获得的较高精度实测数据,详细分析了该海区各站点总悬浮泥沙含量、叶绿素浓度与遥感反射率之间的关系,确立了悬浮泥沙含量对叶绿素浓度反演的影响方式,从而获得了不同悬浮泥沙含量条件下,HY-1卫星CCD等效波段的叶绿素浓度反演模式.分析结果表明,将总悬浮泥沙含量小于6 mg/L定义为中低混浊度水体,把大于6 mg/L定义为中高混浊度水体,然后通过选择不同的悬浮泥沙修正指数分别建模,相关性能够达到实用反演的要求.建模的精度分别为中低混浊度水体,相关性R2= 0.919,平均相对误差= 0.277;中高混浊度水体,相关性R2= 0.877,平均相对误差=0.564.中高混浊度水体叶绿素浓度的反演误差较大,主要体现在低叶绿素浓度区(Cchl<1 mg/m3),表明利用CCD数据反演中高混浊度水体低值叶绿素浓度模式还有待于进一步完善.     

HY-1 CCD宽波段水色要素反演算法

利用2003年春季黄海、东海区现场实测数据,建立了HY1卫星4波段CCD成像仪水色要素反演算法.由于HY1CCD的宽波段特性阻碍了黄色物质的反演,因此反演的水色要素仅包括水体表层的总悬浮物、悬浮泥沙(SS)以及叶绿素a的浓度.现场遥感反射率光谱由ASD地物波谱仪测量,对于叶绿素a的浓度利用现场萃取荧光法测量,总悬浮物、悬浮泥沙由实验室滤膜称重法获得.反演算法的拟合相关系数均大于0.88,平均相对误差在40%以下.对反演算法进行了误差灵敏度分析,结果表明对于总悬浮物、悬浮泥沙和低浊度水体中的叶绿素a的浓度反演算法能够满足日常的业务运行要求,但是对于高浊度水体中叶绿素a的浓度反演算法对某个波段组合比较敏感,仍需要进一步探讨.     

南海北部水体叶绿素a浓度反演的生物光学模型

利用2003年至2005年秋季在南海多个航次的现场观测数据,研究了南海北部海区遥感反射率的变化,并分析了用于全球海洋叶绿素a浓度反演的OC2和OC4模型在本海区的适用性。结果表明,在南海北部海域,OC2和OC4模型高估了叶绿素a浓度,高估范围一般约在80%—200%之间,其中最高可达640%,即OC2和OC4模型并不适用于南海海域。在此基础上,根据现场实测的表观光学数据,利用遥感反射率比值(Rrs(433)/Rrs(555))与叶绿素a浓度的关系建立了两套能够精确反演南海北部海域叶绿素a浓度的本地化经验算法———算法1和算法2,并利用其对南海北部海域的叶绿素a浓度进行反演。结果表明,由本地化模型反演得到的叶绿素a浓度与实测的叶绿素a浓度具有较好的相关关系,其平均相对偏差分别为51%和53%,相关系数为0.75。     

基于现场光谱数据的珠江口MERIS悬浮泥沙分段算法

利用珠江口海域4个航次共59个站位的实测遥感反射比和悬浮泥沙数据(悬浮泥沙浓度范围为4-140g·m-3),建立了利用MERIS遥感数据反演珠江口悬浮泥沙浓度的分段算法.算法以Rrs(620)/Rrs(560)=0.9为阈值,当Rrs(620)/Rrs(560)<0.9时,红绿波段比值可以较好地反演悬浮泥沙浓度.随着悬浮泥沙浓度的增加,Rrs(620)/Rrs(560)>0.9,红绿比值趋于饱和,对悬浮泥沙的变化响应不敏感,此时采用包含红波段和近红外波段的波段比值提取水体的悬浮泥沙浓度.利用该分段算法从MERIS遥感图像中提取珠江口水体的悬浮泥沙浓度分布,得到较好的结果.     

杭州湾——舟山渔场秋季浮游植物现存量和初级生产力

1995年9月在杭州湾和长江口至舟山海区进行了浮游植物细胞丰度、叶绿素a浓度和初级生产力的现场观测研究.结果表明,表层水浮游植物平均细胞丰度为(22.68±63.33)×104个/dm3;平均叶绿素a浓度为2.80±3.46μg/dm3,小于20μm的微型和微微型浮游生物细胞对叶绿素a的贡献占71%;平均初级生产力(C)为692.5±1192.4mg/(m2·d),小于20μm的微型和微微型浮游生物细胞对总生产力的贡献占68%.河口区悬浮物质浓度高,浮游植物光合作用受光的限制,各项生物参数与真光层深度紧密相关.生物锋区位于真光层深度10～20m、盐度26～32的长江冲淡水稀释区.同时探讨了浮游植物细胞活性(R)与光合作用同化数(AN)、叶绿素a与初级生产力、叶绿素a与海面光谱反射率的相互关系,为海洋水色遥感在初级生产力的应用研究提供科学依据     

渤海湾叶绿素浓度的反演与验证（英文）

叶绿素a浓度是浮游植物现存量的表征。本文基于2012年春季渤海湾叶绿素实测数据,下载了相应的遥感数据,利用MODIS数据的OC3M和OC2方法进行叶绿素浓度a反演,利用GOCI数据的波段比值、OC3G以及YOC算法对叶绿素a浓度进行反演,反演结果与实测结果的空间分布趋势一致。由反演精度分析,GOCI的波段比值法与MODIS的OC3M算法的反演精度相近,GOCI数据的YOC叶绿素浓度算法在渤海湾反演精度比其他反演算法高。     

杭州湾——舟山渔场秋季浮游植物现存量和初级生产力

1995年 9月在杭州湾和长江口至舟山海区进行了浮游植物细胞丰度、叶绿素a浓度和初级生产力的现场观测研究 .结果表明 ,表层水浮游植物平均细胞丰度为(2 2 6 8± 6 3 33)× 1 0 4个 /dm3;平均叶绿素a浓度为 2 80± 3 46 μg/dm3,小于 2 0μm的微型和微微型浮游生物细胞对叶绿素a的贡献占 71 % ;平均初级生产力 (C)为6 92 5± 1 1 92 4mg/ (m2 ·d) ,小于 2 0 μm的微型和微微型浮游生物细胞对总生产力的贡献占 6 8% .河口区悬浮物质浓度高 ,浮游植物光合作用受光的限制 ,各项生物参数与真光层深度紧密相关 .生物锋区位于真光层深度 1 0～ 2 0m、盐度 2 6～ 32的长江冲淡水稀释区 .同时探讨了浮游植物细胞活性 (R)与光合作用同化数 (AN)、叶绿素a与初级生产力、叶绿素a与海面光谱反射率的相互关系 ,为海洋水色遥感在初级生产力的应用研究提供科学依据     

基于GF-4卫星的杭州湾悬浮泥沙浓度遥感监测研究

悬浮泥沙作为重要水质参数，其分布和动态变化对河口及近岸的生态、环境、物质循环等都具有深远的影响。我国静止轨道高分四号(GF-4)卫星数据具有高时间和高空间分辨率的观测优势，在水色遥感上具有重大应用潜力。为探究GF-4卫星对悬浮泥沙浓度的监测能力，本文以杭州湾为研究区，构建反演模型，利用静止海洋水色成像仪进行交叉验证。结果表明，以GF-4卫星第5和第4波段遥感反射率的比值作为遥感因子建立的反演模型精度较高，决定系数为0.92，均方根误差为223.2 mg/L，平均相对误差为17.2%。交叉验证结果显示，GF-4卫星作为一种新的遥感数据源，在低浓度区与静止海洋水色成像仪反演悬浮泥沙浓度分布相似，但在高浓度区的差异随浓度增高而增大，总体可满足中国大部分海区的监测需求。     

巴林塘海峡东部海区夏季叶绿素a的分布和初级生产力估算

我所“实验3”号船于1984年6月对巴林塘海峡东部海区的叶绿素和初级生产力进行了调查研究。结果表明,该海区的叶绿素a含量和初级生产力都比较低,平均分别为0.09±0.06rag/m3和108±16mgC/m2·d,真光层内叶绿素a的现存量平均为10.69±2.03mg/m2。叶绿素a含量在100m水层出现最大值,平均为0.16±0.04mg/m3。平面分布较均匀,25m层变化幅度最大为64%,其他水层均小于50%。叶绿素a含量与现场测定的荧光值呈显著的正相关(P<0.01)。     

冬季西太平洋雅浦海山(Y3)区次表层叶绿素最大值层分布及其对悬浮体粒度的影响

2014年冬季对西太平洋雅浦(Y3)海山区两条相交断面进行水文和悬浮体调查。利用温盐深仪(CTD)和深水型原位激光粒度仪(LISST-Deep)获取调查区各站位水体剖面的温度、盐度、叶绿素a浓度以及悬浮体体积浓度和粒度分布数据,对上层(350m以浅)水体的水文和悬浮体调查结果进行分析。结果表明:Y3海山对流经该海区的洋流产生影响,在海山顶部水体中形成具有上凸形态的温、盐跃层,在局部海域形成呈下凹形态的涡旋水文结构;受温、盐跃层的影响和控制,Y3海山上层水体中次表层叶绿素最大值层(SCML)的分布与温、盐跃层的水深范围(约50—160m)相一致,其荧光叶绿素a浓度总体小于1μg/L;Y3海山上层水体的悬浮体总体积浓度在0—120μl/L之间变化,其中悬浮体体积浓度的高值水层集中分布在SCML中,且悬浮体粒度分布存在5个峰值粒级,分别为15.4、68.6、95.5、185和304μm;其中15.4μm粒级的悬浮体体积浓度最低,但其与水层中荧光叶绿素a浓度的相关性最好,反映了水层中微型浮游植物的浓度与荧光叶绿素a浓度关系比较密切;其他4个较大峰值粒级悬浮体可能由小型或中型浮游生物(及其絮凝集合体)等构成,体积浓度较高,对水体叶绿素a浓度的影响很小;Y3海山区东侧Y3-14站的悬浮体组成和分布不同于其他站位,可能有未知的环境因素影响该站位的悬浮体组成和分布。本文研究结果可为进一步开展海山区沉积和生态环境研究提供参考和依据。     

The algorithms of chlorophyll-a concentration for CMODIS

The algorithms of extracting chlorophyll-a(Chl-a) concentration have been established for Chinese moderate resolution imaging spectrometer(CMODIS) mounted on Shenzhou-3 spaceship launched on 25 March 2002.The CMODIS is an ocean color sensor with 30 visible channels and 4 infrared channels,much different from other ocean color satellites and needs new algorithms to process data.Three models of Chl-a concentration were established based on Chl-a data retrieved from sea-viewing wide field-of-view sensor(SeaWiFS),with the average relative errors of 26.6%,24%.0% and 33.5%,respectively.This practical and economic approach can be used for developing the algorithms of Chinese ocean color and temperature sensor(COCTS) on the satellite Haiyang-1 to derive the Chl-a concentration concentration distribution.The applicability of the algorithms was analyzed using some in situ measurements.Suspended sediment is the main factor influencing the accuracy of the spectral ratio algorithms of Chl-a concentration.The algorithms are suitable to using in the regions where suspended sediment concentrations(SSC) are less than 5 g/m3 under the condition of relative error of Chl-a concentration retrieval within 35%.High concentration of suspended sediment leads to the overestimate remote sensing retrieval of concentration of Chl-a,while low-middle SSCs lead to the low Chl-a concentration values using the spectral ratio algorithms.Since the accuracy of Chl-a concentration by the spectral ratio algorithms is limited to waters of Case 2,it is necessary to develop semi-analytical models to improve the performance of satellite ocean color remote sensing in turbid coastal waters.     

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

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利用海洋多波段扫描仪航空遥感海面叶绿素浓度的研究

本文首先介绍了由中国科学院上海技术物理研究所最新研制的海洋多波段扫描仪（OMS）的性能和特色，并描述了1999年10月份在黄渤海典型海区进行航空校飞的实验的概况及校飞资料的处理过程。然后，针对不同海区的水色特点，着重探讨了通过最佳通道选择进行假彩色合成叶绿素的定性提取法和模式计算的定量提取法的原理和方法。最后，通过航空校飞、卫星遥感和实测三种准同步资料所得叶绿素浓度空间分布的趋势比较验证了两种叶绿素提取方法和可信度，同时也显示了在OMS基础上所研制的我国第一颗海洋水色卫星水色遥感器的应用前景。     

Quantification of the Total Suspended Matter Concentration around the Sea Breaking Zone from In Situ Measurements and Terra/Aster Data

Remote sensing techniques can be used to quantify the total suspended matter concentration (TSM). The main objective of this study is the quantification of the TSM concentration around the sea breaking zone for a particular area of the Portuguese coast, near Aveiro city. The methodology used was based on in situ measurements and on multispectral satellite image from TERRA/ASTER. In situ experimental techniques were used to determine a relationship between the TSM concentration and the seawater reflectance. Empirical relationships were established between TSM concentration and the equivalent reflectance values for TERRA/ASTER at visible and near infrared bands computed from the experimental data. The reflectance values had a very high correlation with the TSM concentration in the wavelength between 500 and 900 nm. The ASTER image was calibrated, atmospherically and geometric corrected. Equations of linear, polynomial, logarithmic, power and exponential models were applied. The best results were found with the linear and polynomial models, with a determination factor higher than 0.95. However, the differences in the TSM concentration calculated for the three bands indicate that we should not use the information of a single band to obtain the TSM concentration.     

Quantification of the Total Suspended Matter Concentration around the Sea Breaking Zone from In Situ Measurements and Terra/Aster Data

Remote sensing techniques can be used to quantify the total suspended matter concentration (TSM). The main objective of this study is the quantification of the TSM concentration around the sea breaking zone for a particular area of the Portuguese coast, near Aveiro city. The methodology used was based on in situ measurements and on multispectral satellite image from TERRA/ASTER. In situ experimental techniques were used to determine a relationship between the TSM concentration and the seawater reflectance. Empirical relationships were established between TSM concentration and the equivalent reflectance values for TERRA/ASTER at visible and near infrared bands computed from the experimental data. The reflectance values had a very high correlation with the TSM concentration in the wavelength between 500 and 900 nm. The ASTER image was calibrated, atmospherically and geometric corrected. Equations of linear, polynomial, logarithmic, power and exponential models were applied. The best results were found with the linear and polynomial models, with a determination factor higher than 0.95. However, the differences in the TSM concentration calculated for the three bands indicate that we should not use the information of a single band to obtain the TSM concentration.     

利用卫星遥感进行海上透明云薄云的检测

海上透明云、薄云的存在,会在一定程度上影响利用卫星遥感进行定量化的水色(泥沙含量、叶绿素、海水透明度等)反演的精度,也会影响海温定量化产品的精度[1].因此,在卫星遥感中深入研究海上透明云薄云是进行水色质量控制的一个很重要的内容.本文针对目前的海洋一号卫星水色扫描仪(HY-1 COCTS)、EOS卫星中分辨率成像光谱仪(MODIS)和神舟三号飞船中分辨率成像光谱仪(SZ3-CMODIS)的遥感云检测方法进行了分析,提出了一种实用的海上透明云薄云检测算法,检测有效率在80%以上,最后给出了检测结果图例.     

基于AMSR-E数据的多年冰密集度反演算法研究

In recent years, the rapid decline of Arctic sea ice area(SIA) and sea ice extent(SIE), especially for the multiyear(MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square(rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and0.69×106 km2 during January to March, –0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang's, Lomax' and NASA TEAM algorithms.     

大连长兴岛海域疏浚区GF-1 WFV影像悬浮物遥感反演研究

利用2017年8-9月期间大连长兴岛海域实测遥感反射率、悬浮物浓度及GF-1 WFV数据,研究了该区域悬浮物浓度的遥感反演算法,发现遥感反射率与悬浮物浓度的散点图存在两种不同的变化趋势,将2008-2015年期间辽东湾内其它海域的数据与长兴岛海域数据进行叠加后,可初步推断产生两种变化趋势的主要原因在于疏浚区与非疏浚区悬浮物的粒径大小不同,导致其光学特性和反演算法也存在差异。将两种算法分别应用于2017年9月20日辽东湾及长兴岛近岸海域的GF-1 WFV4影像,发现采用非疏浚区算法反演长兴岛海域悬浮物浓度时,出现明显的低估现象,而疏浚区算法则能较好地反映出疏浚施工过程中悬浮物的分布规律,具有较好的工程应用价值。     

人工神经网络反演珠江口海域叶绿素浓度

利用2003年1月、2004年1月在珠江口海域的叶绿素浓度和辐射同步实测资料,建立了反演珠江口海域叶绿素浓度的人工神经网络模型。应用该模型由SeaWiFS资料获取珠江口海域叶绿素浓度分布图,并与SeaBAM推荐的OC2和OC4这2种统计算法的反演结果进行比较,结果表明人工神经网络模型的反演效果明显优于统计算法。人工神经网络模型的均方根差是0．2899,可决系数是0．8848;而统计算法的均方根差大于0．5,可决系数小于0．6。     

Method for determining atmospheric motion characteristics using measurements on geostationary meteorological satellites

The method for determining the dynamic characteristics of the atmosphere using the data of sounding from geostationary meteorological satellites developed by the authors and based on using inhomogeneities of the conservative admixture concentration field as tracers and on applying the correlation extreme algorithms is described in detail. The accuracies in calculating the horizontal wind velocity vector (V) and coefficient of horizontal mesoscale turbulent diffusion (K _d ) are estimated on the basis of processing the data of sounding the atmosphere with a SEVIRI (Spinning Enhanced Visible and Infrared Imager) radiometer on the Meteosat-8 and Meteosat-9 European geostationary meteorological satellites in the water vapor channels centered at 6.2 and 7.3 μm and on comparing the results with the data of independent observations and theoretical models. It is indicated that the accuracy in calculating V using the developed method almost coincides with the accuracy of the commonly used foreign methods. In contrast to the methods applied abroad, the developed method makes it possible to determine not only the wind velocity vector field but also the coefficient of mesoscale turbulent diffusion and vorticity on one scale of air mass motion.