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遥感技术与应用  2000, Vol. 15 Issue (4): 214-219    DOI: 10.11873/j.issn.1004-0323.2000.4.214
研究与应用     
表面水质遥感监测研究
张渊智,聂跃平,蔺启忠,荆林海,张 兵
(中国科学院遥感应用研究所 北京  100101)
Surface Water Quality Monitoring Using Remote Sensing
ZHANG Yuan-zhi, NIE Yue-ping, LIN Qi-zhong, JING Lin-hai, ZHANG Bing
(Institute of Remote Sensing Applications,The Chinese Academy of Sciences,Beijing100101,China)
 全文: PDF 
摘要:

主要讨论了应用多种传感器遥感技术进行表面水质监测研究的有效性。首先论述了纯水和不
同水质的波谱特性,然后以芬兰海湾和芬兰南部湖泊为应用实例,进行多种遥感数据和主要水质参
数之间的相关性分析,从而确定不同波谱段是否可以有效地监测表面水质的变化情况。本研究为新
一代传感器的设计提供水质监测的重要参数,进一步的试验研究仍在进行之中。

关键词: 表面水质波谱特性传感器遥感技术    
Abstract:

This paper describes the possibility of surface water quality monitoring using remote sensing
technology and the spectral signatures of pure water and other types of water quality. Using airborne and
spaceborne data (TM and ERS-2) analysed with in situ measurements of ground truth points for water
quality parameters, some major factors of surface water quality can be derived from remote sensing data by
case studies. Concurrent in situ surface water quality measurments, Landsat TM data and ERS-2 SAR
data were obtained in the selected locations in August1997. In situ data included measurements of
chlorophyll-a, total dissolved organic carbon and turbidity, Secchi disk depth, color index, estimated wave
height, salinity and surface temperature. The Landsat TM and ERS-2 SAR data from locations of water
samples were extracted and the digital data were examined in their raw states as well as numerous
transformations. Significant correlations were observed between digital numbers and surface water quality
parameters. The results indicate that it may be possible to derive surface water quality parameters using
remote sensing data in our case study area. However, the technique still needs to be refined to detect
differences within the range of water quality which is typically found in the area under study.

Key words: Surface water quality    Spectral signatures    Multi-sensors remote sensing
收稿日期: 2000-06-21 出版日期: 2012-02-23
:  TP 751  
基金资助:

欧盟(EU)合作项目“水质遥感监测”资助。

作者简介: 张渊智,(1964-),男,博士,主要从事遥感与GIS应用研究。
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引用本文:

张渊智,聂跃平,蔺启忠,荆林海,张 兵. 表面水质遥感监测研究[J]. 遥感技术与应用, 2000, 15(4): 214-219.

ZHANG Yuan-zhi, NIE Yue-ping, LIN Qi-zhong, JING Lin-hai, ZHANG Bing. Surface Water Quality Monitoring Using Remote Sensing. Remote Sensing Technology and Application, 2000, 15(4): 214-219.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2000.4.214        http://www.rsta.ac.cn/CN/Y2000/V15/I4/214

〔1〕  Hallikainen M, Kallio K, Hannonen T,et al. SAtellite Remote Sensing for Lake MONitoring (SALMON)〔R〕.
Annual Final Report Submitted to EU, 1998.
〔2〕  Lindell T, Pierson D, Premazzi G,et al. Manual for Monitoring European Lakes Using Remote Sensing
Techniques〔Z〕. European Communities, 1999.
〔3〕  匡定波.卫星遥感解译太湖水质研究〔Z〕.863-308通讯,第2期,P4, 1998.
〔4〕  濮静娟,关燕宁,董卫东.热红外遥感用于陡河水库生态环境研究〔J〕.遥感学报,1997,11(4):290~297.
〔5〕  Palmer K F, Williams D. Optical Properties of Waters in the Near Infrared〔J〕. J Opt Soc America, 1974,64:1107~1110.
〔6〕  Pope R M, Fry E S. Absorption Spectrum (380~700 nm) of Pure Water. II. Integrating cavity measurements〔J〕. Appl Opt,1998,36:8710~8723.
〔7〕  Smith R C, Baker K S.Optical Properties of the Clearest Natural Waters (200~800 nm)〔J〕. Appl Opt,1981,20:177~184.
〔8〕  Zhang Y, Koponen S, Pulliainen J, Hallikainen M.Turbidity and Secchi Disk Depth Aanalysis Derived from
Combined Landsat TM Data and ERS-2 SAR Data in the Gulf of Finland〔R〕. Remote Sensing of Environment, 2000(submitted).
〔9〕  Zhang Y, Koponen S, Pulliainen J,et al. Landsat Thematic Mapper (TM) Data Analysis for Chlorophyll-a and Turbidity in Finland Gulf, URSI/Remote Sensing Club of Finland/IEEE XXIII Convention on Radio Science and Remote Sensing Symposium, 1998,8:69~70, 24~25.
〔10〕  Zhang Y, Koponen S, Pulliainen J,et al. Chlorophyll-a and Turbidity Estimate Using Landsat TM and ERS-2 Data in the Gulf of Finland〔J〕. International Journal of Remote Sensing,1999(in press).
〔11〕  Zhang Y, Koponen S, Pulliainen J,et al. Turbidity and Secchi Disk Depth Aanalysis Derived from Landsat TM Data Combined with ERS-2 in the Gulf of Finland. Presented at the 2nd International Symposium Operationalization of Remote Sensing at ITC〔R〕. Enschede, The Netherlands,1990,8:16~20.
〔12〕  Dekker A G. Detection of Optical Water Quality Parameters for Eutrophic Waters by High Resolution Remote Sensing 〔M〕. PhD thesis, Free University, Amsterdam, 1993.222.

 

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