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1.
《海洋通报(英文版)》2017,(2)
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。 相似文献
2.
为利用遥感技术快速、及时的掌握厦门近岸海域水体中悬浮颗粒物的总体分布情况,现场测量了厦门海域水体的下行入射辐射、天空光以及经过水气界面后反射回的辐射,计算了该海域水体表面的离水辐射获得了水体表面以上遥感反射率;同时采集了与光谱信息同步的水体样品,并分析了水体中的悬浮颗粒物质量浓度,获取了对应站位的水体反射波谱曲线和采集样品的浓度数据.通过研究不同站位水体的反射光谱数据,依据GF-WFV波段设置,对现场实测的光谱数据进行了拟合,并创建了基于GF-WFV拟合波段的悬浮颗粒物浓度经验反演算法.通过研究发现拟合(Rrs3+Rrs4)/Rrs2(其中Rrs1、Rrs2、Rrs3、Rrs4分别是GF-WFV第1、2、3、4波段的遥感反射率)同实测水体悬浮颗粒物质量浓度之间的决定系数为0.655,依据研究得出的反演算法反演该海域水体悬浮颗粒物质量浓度,其均方根误差为11.03 mg/dm3,相对误差为8.40 mg/dm3.利用同步的GF-WFV遥感数据对厦门近岸水体中总悬浮颗粒物质量浓度进行了研究,获取了研究区水体悬浮颗粒物的空间分布情况,结果表明GF-WFV遥感数据能很好的反映厦门近岸水体悬浮颗粒物浓度分布状况. 相似文献
3.
4.
基于高光谱数据的珠江口表层水体悬浮泥沙遥感反演模式 总被引：4，自引：0，他引：4
利用2006年12月4日珠江口海域实测的高光谱遥感反射率数据及悬浮泥沙质量浓度数据,进行了该海域表层水体悬浮泥沙遥感反演模式的研究。研究结果表明,悬浮泥沙质量浓度与Rrs(λ1)/Rr s(λ2)-Rrs(λ1)/Rrs(λ3)的相关性较好,其中Rrs(λ)代表遥感反射率,λ代表波长,λ1=762.6 nm,λ2=559.09 nm,λ3=772.78 nm,建立了悬浮泥沙质量浓度定量遥感反演模式,该模式的均方根误差为4.67 mg/L,可以用于珠江口海域的悬浮泥沙质量浓度的遥感监测。 相似文献
5.
《海洋技术学报》2018,(6)
由于渤海湾水质光学性质复杂,使用传统线性叶绿素浓度反演方法进行反演时的精度不高。为提高渤海湾叶绿素浓度的反演精度,利用2012年4月渤海湾的表层叶绿素浓度实测数据和GOCI同步遥感反射率数据,建立了渤海湾叶绿素浓度反演的BP神经网络模型,并与GOCI的3种叶绿素浓度业务算法(OC2算法、OC3G算法和YOC算法)进行比较。结果表明,在渤海湾GOCI 3种业务算法的标准误差均大于1,决定系数均小于20%;BP神经网络算法的标准误差为0.615 4,决定系数为89.98%,且反演的叶绿素浓度分布与实测值的分布趋势一致,反演的精度高于GOCI传统业务算法。因此该BP神经网络模型可用于反演春季渤海湾表层叶绿素浓度,且反演精度比GOCI业务反演算法精度高。 相似文献
6.
为提高我国海洋水色遥感技术和海水环境监测水平,文章根据北海区海水遥感现场监测数据,基于经验算法和荧光基线高度法的回归分析,开展海水表层叶绿素a浓度的遥感定量反演,并选取北黄海近岸海域样本数据进行算法检验。研究结果表明:辽东湾等9个北海区典型海域具有相同或相似海水表层光学特性,适宜建立海水表层叶绿素a浓度遥感定量反演模型;典型海域海水表层叶绿素a浓度与遥感反射率之间的相关关系较强,模型均为简单波段比值模型;二类海水研究区域海水表层叶绿素a浓度与荧光基线高度之间的相关关系不明显;北黄海近岸海域海水表层叶绿素a浓度的最优模型遥感定量反演值的相对误差的平均值为0.669μg/L。 相似文献
7.
《海洋通报(英文版)》2017,(2)
渤海湾水体交换能力差,自净能力低,每年都要接纳大量的陆源污染物,叶绿素浓度的遥感估算对研究渤海湾海洋赤潮,监测海洋水体水质有重要作用,选择最佳算法反演叶绿素浓度有利于提高反演的精度。本文使用渤海湾的现场测量数据及GOCI遥感反射率数据,利用荧光线高度法、OC3算法、蓝绿波段比值法和近红-红波段比值法建立叶绿素浓度反演模型,并利用实测数据进行算法验证,通过比较各算法的拟合效果和验证结果,对各算法模型进行了评价。结果显示,不同的反演方法准确性有明显差别,荧光线高度法的拟合和反演效果为最佳,而近红-红波段比值法的反演效果最差,OC3算法与蓝绿波段比值法的拟合和反演效果基本相似。 相似文献
8.
基于现场光谱数据的珠江口MERIS悬浮泥沙分段算法 总被引：1，自引：0，他引：1
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. 相似文献
9.
南海叶绿素a浓度垂直分布的统计估算 总被引：2，自引：0，他引：2
分析整理了1993—2006年近10 a南海北部海域、南沙海域和南海其他海域的叶绿素a浓度历史航次调查资料,基于前人提出的全球叶绿素浓度垂直分布的统计分析模式,根据南海表层叶绿素a浓度大小的不同分级,对南海叶绿素a浓度进行了参数化处理,拟合估算了南海各水层剖面的叶绿素a浓度分布值,并结合不同海区的环境特征,分析了南海叶绿素a浓度垂直分布与其海水物理环境的关系。初步分析结果表明,叶绿素a浓度随深度垂直变化的拟合曲线呈一定倾斜的正态分布特征,当表层叶绿素a浓度较低时,作为南海深水海盆区的代表,拟合值更接近实测平均值的分布,叶绿素a浓度高值集中在次表层剖面上;当表层叶绿素a浓度较高时,作为近岸区和河口区的代表,高值多集中在表层海水,拟合误差偏大。该统计估算模式对于揭示南海叶绿素a浓度垂直分布结构进行了有益的尝试,为发展适合不同海区特点的模式以及校正参数奠定了基础。利用该模式与海洋水色卫星遥感数据有效结合,将对南海叶绿素a浓度时空分布格局的研究具有重要的意义。 相似文献
10.
利用SeaDAS从SeaWiFS卫星数据反演中国东海叶绿素浓度 总被引：1，自引：0，他引：1
卫星海洋遥感反演海中叶绿素浓度,对海洋初级生产力估算及赤潮预报均有重要意义.本文介绍了SeaWiFS卫星传感器业务化算法OC4,利用SeaDAS软件反演中国东海叶绿素浓度,并与东海同步现场数据进行验证.结果表明:利用SeaDAS方法计算的东海叶绿素含量与实测含量之间具有较好的相关性,但总体上计算值要高于实际测量值;东海叶绿素含量具有分带性,河口、近岸海域高,中陆架次之,外陆架最低,这种发育特点与该海域的陆源营养盐输入、海洋动力系统有着显著的关系. 相似文献
11.
基于19GHz修正91GHz频段改进的ASI海冰密集度算法 总被引：1，自引：1，他引：0
基于数据融合算法思想，利用低频修正高频微波数据提出改进的ASI海冰密集度反演算法，对北极海冰进行反演研究。目前用于整体海冰密集度反演的算法中，使用低频数据的算法受天气影响较弱，但空间分辨率相对较低；而使用高频数据的算法，空间分辨率相对较高，但受天气影响较大，虽然使用天气滤波器处理，能消除那些被误判成海冰的水点，但并没有改变冰点的密集度。改进的ASI算法，利用低频数据（19GHz）修正高频数据（85.5GHz），进而得到修正后的85.5GHz的极化差P''，将P带入ASI算法，最终得到以2008-2016年每年的1月3日SSMIS数据为例的北冰洋整体海冰密集度反演结果。结果表明，改进后的ASI算法得到的总体海冰面积介于ASI与NASA Team两个结果之间；在边缘海冰区，改进后的ASI算法结果与传统的ASI算法结果在海冰面积与平均海冰密集度上都有较大差异，且前者更接近NASA Team算法。因此改进后的ASI算法，在空间分辨率上优于NASA Team算法，在受天气影响程度上更弱于ASI算法，并且有效变了边缘海冰区像元的海冰密集度。 相似文献
12.
HY-1 CCD宽波段水色要素反演算法 总被引：7，自引：4，他引：3
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. 相似文献
13.
Eko Siswanto Junwu Tang Hisashi Yamaguchi Yu-Hwan Ahn Joji Ishizaka Sinjae Yoo Sang-Woo Kim Yoko Kiyomoto Keiko Yamada Connie Chiang Hiroshi Kawamura 《Journal of Oceanography》2011,67(5):627-650
A bio-optical dataset collected during the 1998?C2007 period in the Yellow and East China Seas (YECS) was used to provide alternative empirical ocean-color algorithms in the retrieval of chlorophyll-a (Chl-a), total suspended matter (TSM), and colored dissolved organic matter (CDOM) absorption coefficients at 440 nm (ag440). Assuming that remote-sensing reflectance (Rrs) could be retrieved accurately, empirical algorithms for TChl (regionally tuned Tassan??s Chl-a algorithm) in case-1 waters (TChl2i in case-2 waters), TTSM (regionally tuned Tassan??s TSM algorithm), and Tag440 or Cag440 (regionally tuned Tassan??s or Carder??s ag440 algorithm) were able to retrieve Chl-a, TSM, and ag440 with uncertainties as high as 35, 46, and 35%, respectively. Applying the standard SeaWiFS Rrs, TChl was not viable in the eastern part of the YECS, which was associated with an inaccurate SeaWiFS Rrs retrieval because of improper atmospheric correction. TChl behaved better than other algorithms in the turbid case-2 waters, although overestimation was still observed. To retrieve more reliable Chl-a estimates with standard SeaWiFS Rrs in turbid water (a proxy for case-2 waters), we modified TChl for data with SeaWiFS normalized water-leaving radiance at 555 nm (nLw555) > 2 mW cm?2 ??m?1 sr?1 (TChl2s). Finally, with standard SeaWiFS Rrs, we recommend switching algorithms from TChl2s (for case-2 waters) to MOCChl (SeaWiFS-modified NASA OC4v4 standard algorithm for case-1 waters) for retrieving Chl-a, which resulted in uncertainties as high as 49%. To retrieve TSM and ag440 using SeaWiFS Rrs, we recommend empirical algorithms for TTSM (pre-SeaWiFS-modified form) and MTag440 or MCag440 (SeaWiFS Rrs-modified forms of Tag440 or Cag440). These could retrieve with uncertainties as high as 82 and 52%, respectively. 相似文献
14.
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%. 相似文献
15.
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. 相似文献
16.
Satellite observations of the partial pressure of carbon dioxide in the surface water of the Huanghai Sea and the Bohai Sea 总被引：1，自引：0，他引：1
Based on 5 831 continuous in situ measurements of the partial pressure of carbon dioxide on the sea surface p(CO2),related parameters of the sea surface temperature(SST) and chlorophyll-a(Chl a) concentration in 2010 winter,spring and summer of the Huanghai Sea and the Bohai Sea,the inherent relations among them are investigated preliminarily.This study reveals that the seasonal variability of SST and Chl a concentration has a significant influence on p(CO2).The authors have proposed a new algorithm to estimate p(CO2) from SST and Chl a concentration measurements.Compared with the vessel data,the root mean square error(RMSE) of p(CO2) retrieved by using the new model is 13.45 μatm(1atm=101.325 kPa) and the relative error is less than 4%.Then,SST and Chl a concentration data observed by satellite are used to retrieve p(CO2) in the Huanghai Sea and the Bohai Sea;and a better accuracy can be obtained if the quality control for sea surface chlorophyll-a concentration observed by satellite is used.The RMSE of retrieved p(CO2) data with quality control and that without quality control are 15.82 μatm and 31.74 μatm,respectively. 相似文献
17.
The statistic inversion algorithms of water constituents for the Huanghai Sea and the East China Sea 总被引：21，自引：2，他引：21
TANG Junwu WANG Xiaomei SONG Qingjun LI Tongji CHEN Jiezhong HUANG Haijun REN Jingping 《海洋学报(英文版)》2004,23(4):617-626
A group of statistical algorithms are proposed for the inversion of the three major components of Case-Ⅱ waters in the coastal area of the Huanghai Sea and the East China Sea. The algorithms are based on the in situ data collected in the spring of 2003 with strict quality assurance according to NASA ocean bio-optic protocols. These algorithms are the first ones with quantitative confidence that can be applied for the area. The average relative error of the inversed and in situ measured components‘ concentrations are: Chl-a about 37%, total suspended matter (TSM) about 25%, respectively. This preliminary result is quite satisfactory for Case-Ⅱ waters, although some aspects in the model need further study. The sensitivity of the input error of 5% to remote sensing reflectance (Rrs) is also analyzed and it shows the algorithms are quite stable. The algorithms show a large difference with Tassan‘s local SeaWiFS algorithms for different waters, except for the Chl-a algorithm. 相似文献
18.
Xiao-Gang Xing Dong-Zhi Zhao Yu-Guang Liu Jian-Hong Yang Peng Xiu Lin Wang 《Ocean Science Journal》2007,42(1):49-59
Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid
methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal
blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll
fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics
such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there
exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield,
physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc.
Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color
sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyl
l - a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated,
the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and
new algorithms could be expected. 相似文献
19.
基于遥感与现场观测数据的南海北部内波传播速度 总被引：2，自引：0，他引：2
南海北部是全球海洋中内波最为活跃、生成和演变机制较为复杂的海域,本文利用多源卫星遥感数据(MODIS、GF-1、ENVISAT ASAR、RADARSAT-2)和现场观测数据开展了南海北部内波传播速度的研究。通过匹配捕获同一条内波的相邻两幅遥感图像,由内波的空间位移和时间间隔反演传播速度,并以0.5°×0.5°网格给出了南海北部内波传播速度的分布图。研究结果表明,内波传播速度受背景流场、水体层结和底地形变化等多因素影响,特别是水深。在南海北部由东至西、由南至北方向,内波传播速度逐渐递减。深海区内波传播速度最大,可达3m/s以上;内波在向西大陆架传播过程中,随着水深变浅速度逐渐减慢,传播速度为1—2m/s;大陆架浅海的内波传播速度较小,仅为零点几米每秒。同时,利用Kd V方程反演了内波传播速度理论值,对遥感数据提取的内波传播速度进行了精度验证,结果较为一致。 相似文献
20.
Sea-ice concentration is a key item in global climate change research.Recent progress in remotely sensed sea-ice concentration product has been stimulated by the use of a new sensor,advanced microwave scanning radiometer for EOS(AMSR-E),which offers a spatial resolution of 6 km×4 km at 89GHz.A new inversion algorithm named LASI(linear ASI) using AMSR-E 89GHz data was proposed and applied in the antarctic sea areas.And then comparisons between the LASI ice concentration products and those retrieved by the other two standard algorithms,ASI(arctic radiation and turbulence interaction study sea-ice algorithm) and bootstrap,were made.Both the spatial and temporal variability patterns of ice concentration differences,LASI minus ASI and LASI minus bootstrap,were investigated.Comparative data suggest a high result consistency,especially between LASI and ASI.On the other hand,in order to estimate the LASI ice concentration errors introduced by the tie-points uncertainties,a sensitivity analysis was carried out.Additionally an LASI algorithm error estimation based on the field measurements was also completed.The errors suggest that the moderate to high ice concentration areas(>70%) are less affected(never exceeding 10%) than those in the low ice concentration.LASI and ASI consume 75 and 112 s respectively when processing the same AMSR-E time series thourghout the year 2010.To conclude,by using the LASI algorithm,not only the seaice concentration can be retrieved with at least an equal quality as that of the two extensively demonstrated operational algorithms,ASI and bootstrap,but also in a more efficient way than ASI. 相似文献