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Remote Sensing Technology and Application  2019, Vol. 34 Issue (2): 313-322    DOI: 10.11873/j.issn.1004-0323.2019.2.0313
    
Research on Chromium Retrieval of Black Soil with Hyperspectral Imagery in Northeast of China#br#
Zhang Mingyue,Zhang Qili,Wang Lu,Tian Weixia,Wang Maozhi
 (Geomathematics Key Laboratory of Sichuan Provence,Chengdu University of Technology,Chengdu 610059,China)

 
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Abstract  According to the definition of spectral integral,a new spectral characteristic parameter,with the name Reversed Spectral Absorption Integral(RSAI),is proposed and used to retrieve the chromium content based on the Partial Least Squares Regression(PLSR) model.The contrastive study with other traditional spectral characteristic parameters,including differential transformation,inverse transformation,absorption area,etc.indicates that(1) the first derivation of square root transformed model can predict the chromium content quantitatively in terms of spectral transformations.(2) the stability of the absorption area model is slightly poor,and the chromium content of samples can only be estimated roughly.(3) However,as to the inversed spectral absorption integral model,the adjustment determination coefficient(Ad-R2) of the modeling and verification is 0.73 and 0.77,while the Root Mean Squared Error(RMSE) is 2.63 mg/kg and 2.36 mg/kg respectively with Relative Percent Deviation(RPD) being 3.21,which shows that the RSAI model has excellent prediction ability.So,the inversed spectral absorption integral new model can improve the accuracy and stability used to retrieve the chromium content,which provides a new idea for monitoring the chromium contamination in soil.
Key words:  Soil chromium content      Spectral transformation      Absorption area      Reversed spectral absorption integral      PLSR     
Published:  10 May 2019
ZTFLH:  TP79  
  S151.9  
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Zhang Mingyue, Zhang Qili, Wang Lu, Tian Weixia, Wang Maozhi. Research on Chromium Retrieval of Black Soil with Hyperspectral Imagery in Northeast of China#br#. Remote Sensing Technology and Application, 2019, 34(2): 313-322.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2019.2.0313     OR     http://www.rsta.ac.cn/EN/Y2019/V34/I2/313

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