Please wait a minute...
 
国土资源遥感  2021, Vol. 33 Issue (2): 108-115    DOI: 10.6046/gtzyyg.2020216
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
基于GOCI数据的胶州湾水体透明度遥感反演及日变化研究
周燕(), 禹定峰(), 刘晓燕, 杨倩, 盖颖颖
齐鲁工业大学(山东省科学院),山东省科学院海洋仪器仪表研究所,山东省海洋监测仪器装备技术重点实验室,国家海洋监测设备工程技术研究中心,青岛 266100
Research on remote sensing retrieval and diurnal variation of Secchi disk depth of Jiaozhou Bay based on GOCI
ZHOU Yan(), YU Dingfeng(), LIU Xiaoyan, YANG Qian, GAI Yingying
Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Shandong Provincial Key Laboratory of Marine Monitoring Instrument Equipment Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, Qingdao 266100, China
全文: PDF(4188 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

透明度是描述海洋和湖泊水体光学性质的一个重要参数。利用2017年5月16日胶州湾航次的现场实测数据和GOCI卫星影像,采用2种半分析算法Doron11和Lee15对水体透明度进行反演。研究表明,Lee15算法在胶州湾海域表现较好,透明度反演值与实测值之间的决定系数为0.98,均方根误差为0.02 m。选择当日8幅GOCI影像,利用Lee15算法反演获得胶州湾水体透明度日变化的时空分布特征。空间分布上,海域整体透明度较低(0~4 m),从湾内到湾外透明度呈现出逐渐增大的趋势。时间变化上,湾内水体透明度的变化受潮汐影响明显,湾外和湾口的变化由太阳天顶角主导,海域平均水体透明度的变化由太阳天顶角和潮汐共同作用。根据各采样点实测水体透明度与现场同步测量的其他环境因子的统计分析,胶州湾水体透明度的变化是多个环境因子共同作用的结果,与水深存在较强的正相关,相关系数达0.84,与其他环境因子均呈负相关关系。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
周燕
禹定峰
刘晓燕
杨倩
盖颖颖
关键词 透明度GOCI影像半分析算法日变化环境因子    
Abstract

Secchi disk depth (Zsd) is an important parameter for describing the optical properties of water bodies. With high spatial and temporal resolution, satellite remote sensing technology has become an important method of Zsd observation. Using the in-situ measured data and GOCI images of Jiaozhou Bay (JZB) on May 16, 2017, the authors used semi-analytical algorithms Doron11 and Lee15 to retrieve the Zsd. It is shown that the Lee15 performed better than Doron11, with the decision coefficient of 0.976 and the root mean square error of 0.02 m between the estimated values and in-situ measured values. Selecting eight GOCI images from 8: 16 to 15: 16, the authors used Lee15 algorithm to get the spatial and temporal distribution characteristics of the diurnal variation ofZsd on the JZB. On the spatial distribution, the overall Zsd level of the JZB is low (0~4 m), and gradually increases from the inside to the outside of the Bay. On the time variations, the Zsd at the Bay mouth is obviously affected by the tides. The changes between the Bay mouth and the Bay outside are dominated by the solar zenith angle (SOLZ). The change of averageZsd of the JZB is mainly caused by the joint effect of the SOLZ and the tide. According to the respectively statistical analysis between the in-situ Zsd at each sampling station and simultaneously measured other environmental factors, the change in the Zsd of the JZB is the result of the joint action of multiple environmental factors, and has a strong positive correlation with the water depth, with correlation coefficient reaching 0.84, but it is negatively correlated with other environmental factors.

Key wordsSecchi disk depth    GOCI image    semi-analytical algorithm    diurnal variation    environmental factors
收稿日期: 2020-07-15      出版日期: 2021-07-21
ZTFLH:  P76  
基金资助:山东省重点研发计划项目“面向沿海水色环境监测的机载高光谱成像探测仪研究”(2019GHY112017);国家重点研发计划项目“多基平台海洋生态环境监测系统集成”(2017YFC1404802);热带海洋环境国家重点实验室(中国科学院南海海洋研究所开放课题“基于遥感数据的南海海水透明度长时序时空演变规律及其环境调控机制研究”编号: LTO2017);山东省自然科学基金项目“基于多传感器卫星数据的海洋牧场生态环境监测研究”(ZR2019PD021);国家海洋公益性项目“海洋高光谱仪和机载激光测量系统产品化关键技术研究及应用示范”(2015031)
通讯作者: 禹定峰
作者简介: 周 燕(1985-),女,硕士,助理研究员,主要从事海洋水色遥感应用研究。Email: zhouyan_ocrs@qlu.edu.cn
引用本文:   
周燕, 禹定峰, 刘晓燕, 杨倩, 盖颖颖. 基于GOCI数据的胶州湾水体透明度遥感反演及日变化研究[J]. 国土资源遥感, 2021, 33(2): 108-115.
ZHOU Yan, YU Dingfeng, LIU Xiaoyan, YANG Qian, GAI Yingying. Research on remote sensing retrieval and diurnal variation of Secchi disk depth of Jiaozhou Bay based on GOCI. Remote Sensing for Land & Resources, 2021, 33(2): 108-115.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2020216      或      https://www.gtzyyg.com/CN/Y2021/V33/I2/108
Fig.1  胶州湾海域采样点站位置分布
Fig.2  采样点实测遥感反射率光谱曲线
Fig.3  波段等效遥感反射率与GOCI大气校正影像的遥感反射率的光谱曲线对比
步骤 物理量 计算公式
1 rrs(λ) rrs(λ)=Rrs(λ)/(0.52+1.7R(λ))
2 u(λ) u ( λ ) = - g 0 + ( g 0 ) 2 + 4 g 1 r rs ( λ ) 2 g 1 ,g0=0.089, g1=0.125
Rrs(670)<0.001 5sr-1 (QAA_V5) Rrs(670)≥0.001 5sr-1 (QAA_V6)
3 a(λ0) a(λ0)=a(55x)=aw0)+ 10 h 0 + h 1 χ + h 2 χ 2
h0=-1.146, h1=-1.366, h2=-0.469
χ = lg r rs ( 443 ) + r ( 490 ) r rs ( 55 x ) + 5 r rs ( 670 ) r rs ( 490 ) r rs ( 670 )
= a ( 670 ) = a w ( 670 ) + 0.39 R rs ( 670 ) R rs ( 443 ) + R rs ( 490 ) 1.14
4 bbp(λ0) bbp(λ0)=bbp(55x)= u ( λ 0 ) - a ( λ 0 ) 1 - u ( λ 0 ) -bbw(55x) bbp(λ0)=bbp(670)= u ( λ 0 ) - a ( λ 0 ) 1 - u ( λ 0 ) -bbw(670)
5 η η = 2 . 0 1 - 1.2 exp - 0.9 r rs ( 443 ) r rs ( 55 x )
6 bbp(λ) bbp(λ)=bbp0) λ 0 λ η
7 a(λ) a(λ)=[1-u(λ)][bbw(λ)+bbp(λ)]/u(λ)
Tab.1  QAA_V6模型计算流程
Fig.4  透明度实测值与算法反演值的散点图
Fig.5  2017年5月16日08: 16—15: 16胶州湾水体透明度时空分布
Fig.6  胶州湾水体透明度、太阳天顶角和潮汐的日变化曲线
统计 [Chl-a]/
(mg·m-3)
[TSM]/
(mg·l-3)
ay(400)/
(m-1)
水深/m 海表温度/℃ 海表盐度 风速/(m·s-1)
最小值 1.12 3.40 0.161 2.00 15.20 0.296 0.20
最大值 4.30 45.30 0.453 41.40 22.30 0.320 7.50
中值 3.36 21.59 0.315 4.85 19.40 0.315 3.60
平均值±标准误差 3.06±0.21 24.07±3.17 0.319±0.019 10.62±3.00 19.20±0.47 0.312±0.002 3.72±0.55
标准差 0.90 13.44 0.082 12.71 1.99 0.008 2.34
变异系数 0.293 0.559 0.257 0.896 0.103 0.025 0.629
皮尔逊相关系数 -0.660 -0.816 -0.713 0.840 -0.805 -0.560 -0.484
Tab.2  实测水体透明度与其他环境因子的相关性
[1] Padial A A, Thomaz S M. Prediction of the light attenuation coefficient through the Secchi disk depth:Empirical modeling in two large neotropical ecosystems[J]. Limnology, 2008, 9(2):143-151.
doi: 10.1007/s10201-008-0246-4
[2] Swift T J, Perez-Losada J, Schladow S G, et al. Water clarity modeling in Lake Tahoe:Linking suspended matter characteristics to Secchi depth[J]. Aquatic Sciences, 2006, 68(1):1-15.
doi: 10.1007/s00027-005-0798-x
[3] Swan B K, Reifel K M, Tiffany M A, et al. Spatial and temporal patterns of transparency and light attenuation in the Salton Sea,California,1997—1999[J]. Lake and Reservoir Management, 2007, 23(5):653-662.
doi: 10.1080/07438140709354044
[4] Testa J M, Lyubchich V, Zhang Q. Patterns and trends in Secchi disk depth over three decades in the Chesapeake Bay estuarine complex[J]. Estuaries and Coasts, 2019, 42(4):927-943.
doi: 10.1007/s12237-019-00547-9
[5] Kukushkin A S. Long-term seasonal variability of water transparency in the surface layer of the deep part of the Black Sea[J]. Russian Meteorology and Hydrology, 2014, 39(3):178-186.
doi: 10.3103/S1068373914030066
[6] Wernand M R. On the history of the Secchi disc[J]. Journal of the European Optical Society:Rapid Publications, 2010, 5:10013.
[7] Li N, Shi K, Zhang Y L, et al. Decline in transparency of Lake Hongze from long-term MODIS observations:Possible causes and potential significance[J]. Remote Sensing, 2019, 11(2):177.
doi: 10.3390/rs11020177
[8] Prasad K S, Bernstein R L, Kahru M, et al. Ocean color algorithms for estimating water clarity (Secchi Depth) from Sea WiFS[J]. Journal of Advanced Marine Science and Technology Society, 2000, 4(2):301-306.
[9] Kratzer S, Hkansson B, Sahlin C. Assessing secchi and photic zone depth in the baltic sea from satellite data[J]. AMBIO:A Journal of the Human Environment, 2003, 32(8):577-585.
doi: 10.1579/0044-7447-32.8.577
[10] Tyler J E. The Secchi disc[J]. Limnology and Oceanography, 1968, VIII(1):1-6.
[11] Preisendorfer R W. Secchi disk science:Visual optics of natural waters[J]. Limnology and Oceanography, 1986, 31(5):909-926.
doi: 10.4319/lo.1986.31.5.0909
[12] Doron M, Babin M, Hembise O, et al. Ocean transparency from space:Validation of algorithms using MERIS,MODIS and SeaWiFS data[J]. Remote Sensing of Environment, 2011, 115(12):2986-3001.
doi: 10.1016/j.rse.2011.05.019
[13] Lee Z P, Shang S L, Hu C M, et al. Secchi disk depth:A new theory and mechanistic model for underwater visibility[J]. Remote Sensing of Environment, 2015, 169:139-149.
doi: 10.1016/j.rse.2015.08.002
[14] Shang S, Lee Z, Shi L, et al. Changes in water clarity of the Bohai Sea:Observations from MODIS[J]. Remote Sensing of Environment, 2016, 186:22-31.
doi: 10.1016/j.rse.2016.08.020
[15] Mao Y, Wang S Q, Qiu Z F, et al. Variations of transparency derived from GOCI in the Bohai Sea and the Yellow Sea[J]. Optics Express, 2018, 26(9):12191-12209.
doi: 10.1364/OE.26.012191
[16] Luis K M A, Rheuban J E, Kavanaugh M T, et al. Capturing coastal water clarity variability with Landsat 8[J]. Marine Pollution Bulletin, 2019, 145:96-104.
doi: 10.1016/j.marpolbul.2019.04.078
[17] Vundo A, Matsushita B, Jiang D, et al. An overall evaluation of water transparency in Lake Malawi from MERIS data[J]. Remote Sensing, 2019, 11(3):279.
doi: 10.3390/rs11030279
[18] Gomes A C, Alcantara E, Rodrigues T, et al. Satellite estimates of euphotic zone and Secchi disk depths in a colored dissolved organic matter-dominated inland water[J]. Ecological Indicators, 2020, 110(b):105848.
doi: 10.1016/j.ecolind.2019.105848
[19] 孙晓霞, 孙松, 张永山, 等. 胶州湾叶绿素a及初级生产力的长期变化[J]. 海洋与湖沼, 2011, 42(5):654-661.
Sun X X, Sun S, Zhang Y S, et al. Long-term changes of chlorophyll-a concentration and primary productivity in the Jiaozhou Bay[J]. Oceanologia et Limnologia Sinica, 2011, 42(5):654-661.
[20] 董兆选, 娄安刚, 崔文连. 胶州湾海域营养状况研究[J]. 海洋科学, 2010, 34(12):36-39.
Dong Z X, Lou A G, Cui W L. Assessment of eutrophication of Jiaozhou Bay[J]. Marine Sciences, 2010, 34(12):36-39.
[21] Mobley C D. Estimation of the remote-sensing reflectance from above-surface measurements[J]. Applied Optics, 1999, 38(36):7442-7455.
pmid: 18324298
[22] Lee Z P, Du K P, Arnone R, et al. Penetration of solar radiation in the upper ocean:A numerical model for oceanic and coastal waters[J]. Journal of Geophysical Research Oceans, 2005, 110(9):13.
[23] Lee Z P, Hu C M, Shang S L, et al. Penetration of UV-visible solar radiation in the global oceans:Insights from ocean color remote sensing[J]. Journal of Geophysical Research:Oceans, 2013, 118(9):4241-4255.
doi: 10.1002/jgrc.20308
[24] Pope R M, Fry E S. Absorption spectrum (380-700 nm) of pure water II.integrating cavity measurements[J]. Applied Optics, 1997, 36(33):8710-23.
pmid: 18264420
[25] Smith R C, Baker K S. Optical properties of the clearest natural waters (200-800 nm)[J]. Applied Optics, 1981, 20(2):177-184.
doi: 10.1364/AO.20.000177 pmid: 20309088
[26] Morel A, Huot Y, Gentili B, et al. Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach[J]. Remote Sensing of Environment, 2007, 111(1):69-88.
doi: 10.1016/j.rse.2007.03.012
[27] 魏国妹, 商少凌, 李忠平, 等. 基于固有光学特性的北部湾透明度遥感反演及其检验[J]. 高技术通讯, 2009, 19(9):977-982.
Wei G M, Shang S L, Lee Z P, et al. An IOP-based remote-sensing algorithm for secchi depth and its validation for the Gulf of Tonkin[J]. Chinese High Technology Letters, 2009, 19(9):977-982.
[28] 任玲, 张曼平, 李铁, 等. 胶州湾内外海水中营养盐的分布[J]. 青岛海洋大学学报(自然科学版), 1999, 29(4):692-698.
Ren L, Zhang M P, Li T, et al. Distribution of nutrients inside and outside Jiaozhou Bay[J]. Journal of Ocean University of Qingdao, 1999, 29(4):692-698.
[29] Kirk J T O. Dependence of relationship between inherent and apparent optical properties of water on solar altitude[J]. Limnology and Oceanography, 1984, 29(2):350-356.
doi: 10.4319/lo.1984.29.2.0350
[30] 丁文兰. 胶州湾的潮汐与潮流[J]. 海洋科学集刊, 1986, 26:1-25.
Ding W L. Tides and currents in Jiaozhou Bay[J]. Studia Marina Sinica, 1986, 26:1-25.
[31] 康兴伦, 李培泉, 刘玉珊, 等. 胶州湾自净能力的研究[J]. 黄渤海海洋, 1990, 8(3):48-56.
Kang X L, Li P Q, Liu Y S, et al. The study of self-purification capacity of Jiaozhou Bay[J]. Journal of Oceanography of Huanghai & Bohai Seas, 1990, 8(3):48-56.
[32] Gattuso J-P, Gentili B, Duarte C M, et al. Light availability in the coastal ocean:Impact on the distribution of benthic photosynthetic organisms and their contribution to primary production[J]. Biogeosciences, 2006, 3(4):489-513.
doi: 10.5194/bg-3-489-2006
[1] 朱利, 李云梅, 赵少华, 郭宇龙. 基于GF-1号卫星WFV数据的太湖水质遥感监测[J]. 国土资源遥感, 2015, 27(1): 113-120.
[2] 陈蕾, 谢健, 彭晓鹃, 李振, 娄全胜, 张晓浩, 杨帆. 珠江口海水透明度与光谱相关关系研究[J]. 国土资源遥感, 2011, 23(3): 151-155.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《自然资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 E-mail:zrzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发