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Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China

JIANG Guangjia,  LIU Dianwei,  SONG Kaishan,  WANG Zongming,  ZHANG Bai,  WANG Yuandong

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文章导航 > Chinese Geographical Science  > 2010 >  20(4): 337-344
JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. 中国地理科学, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
引用本文: JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. 中国地理科学, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
shu
JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. Chinese Geographical Science, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
Citation: JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. Chinese Geographical Science, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
shu

Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China

doi: 10.1007/s11769-010-0406-4
  • 1.

    Northeast Institute of Geography and Agroecology, Chinese Academy Sciences, Changchun 130012, China;

  • 2.

    Graduate University of the Chinese Academy Sciences, Beijing 100049, China

基金项目: Under the auspices of Knowledge Innovation Programs of Chinese Academy of Sciences (No.KZCX2-YW-340,KZCX2-YW-341);Key Project of Jilin Province Scientific and Technological Development Program (No.20080425)
详细信息
    通讯作者:

    LIU Dianwei.E-mail:liudianwei@neigae.ac.cn

Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China

  • 1.

    Northeast Institute of Geography and Agroecology, Chinese Academy Sciences, Changchun 130012, China;

  • 2.

    Graduate University of the Chinese Academy Sciences, Beijing 100049, China

Funds: Under the auspices of Knowledge Innovation Programs of Chinese Academy of Sciences (No.KZCX2-YW-340,KZCX2-YW-341);Key Project of Jilin Province Scientific and Technological Development Program (No.20080425)

  • 摘要: This study applied a multivariate model based on three simulated sensors to estimating water quality variables in Shitoukoumen Reservoir,Changchun City,Jilin Province,China,including concentration of total suspended matter,concentration of chlorophyll-a and non-pigment matter absorption.Two field campaigns for spectra measurements with a total of 40 samples were carried out on June 13 and September 23,2008.The in-situ spectra were recalculated to the spectral bands and sensitivities of the instruments applied in this paper,i.e.Landsat TM,Alos and P6,by using the average method.And the recalculated spectra were used for estimating water quality variables by the single model and multivariate model.The results show that the multivariate model is superior to the single model as the multivariate model takes the combined effects of water components into consideration and can estimate water quality variables simultaneously.According to R2 and RMSE,Alos is superior to other sensors for water quality variables estimation although the precision of non-pigment matter absorption inversion performed the second.
    Abstract: This study applied a multivariate model based on three simulated sensors to estimating water quality variables in Shitoukoumen Reservoir,Changchun City,Jilin Province,China,including concentration of total suspended matter,concentration of chlorophyll-a and non-pigment matter absorption.Two field campaigns for spectra measurements with a total of 40 samples were carried out on June 13 and September 23,2008.The in-situ spectra were recalculated to the spectral bands and sensitivities of the instruments applied in this paper,i.e.Landsat TM,Alos and P6,by using the average method.And the recalculated spectra were used for estimating water quality variables by the single model and multivariate model.The results show that the multivariate model is superior to the single model as the multivariate model takes the combined effects of water components into consideration and can estimate water quality variables simultaneously.According to R2 and RMSE,Alos is superior to other sensors for water quality variables estimation although the precision of non-pigment matter absorption inversion performed the second.
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  • 收稿日期:  2009-12-15
  • 修回日期:  2010-04-28
  • 刊出日期:  2010-07-01

Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China

doi: 10.1007/s11769-010-0406-4
  • 1. Northeast Institute of Geography and Agroecology, Chinese Academy Sciences, Changchun 130012, China;
  • 2. Graduate University of the Chinese Academy Sciences, Beijing 100049, China
    • 基金项目:  Under the auspices of Knowledge Innovation Programs of Chinese Academy of Sciences (No.KZCX2-YW-340,KZCX2-YW-341);Key Project of Jilin Province Scientific and Technological Development Program (No.20080425)
    通讯作者: LIU Dianwei.E-mail:liudianwei@neigae.ac.cn
  • 收稿日期: 2009-12-15
  • 修回日期: 2010-04-28
  • 刊出日期: 2010-07-01

摘要: This study applied a multivariate model based on three simulated sensors to estimating water quality variables in Shitoukoumen Reservoir,Changchun City,Jilin Province,China,including concentration of total suspended matter,concentration of chlorophyll-a and non-pigment matter absorption.Two field campaigns for spectra measurements with a total of 40 samples were carried out on June 13 and September 23,2008.The in-situ spectra were recalculated to the spectral bands and sensitivities of the instruments applied in this paper,i.e.Landsat TM,Alos and P6,by using the average method.And the recalculated spectra were used for estimating water quality variables by the single model and multivariate model.The results show that the multivariate model is superior to the single model as the multivariate model takes the combined effects of water components into consideration and can estimate water quality variables simultaneously.According to R2 and RMSE,Alos is superior to other sensors for water quality variables estimation although the precision of non-pigment matter absorption inversion performed the second.

English Abstract

JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. 中国地理科学, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
引用本文: JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. 中国地理科学, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
shu
JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. Chinese Geographical Science, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
Citation: JIANG Guangjia, LIU Dianwei, SONG Kaishan, WANG Zongming, ZHANG Bai, WANG Yuandong. Application of Multivariate Model Based on Three Simulated Sensors for Water Quality Variables Estimation in Shitoukoumen Reservoir, Jilin Province, China[J]. Chinese Geographical Science, 2010, 20(4): 337-344. doi: 10.1007/s11769-010-0406-4
shu

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