Impact analysis of spectral resolution on retrieving plant biophysical and biochemical parameters based on continuous wavelet analysis
Received:April 10, 2018  Revised:September 30, 2018  download
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Author NameAffiliationE-mail
ZHANG Jing-Cheng College of Life Information Science and Instrument Engineering,Hangzhou Dianzi University zhangjc_rs@163.com 
LIU Peng College of Life Information Science and Instrument Engineering,Hangzhou Dianzi University,Hangzhou,Zhejiang zzwliupeng@163.com 
WANG Bin College of Life Information Science and Instrument Engineering,Hangzhou Dianzi University,Hangzhou,Zhejiang wangb_rs@163.com 
ZHANG Xue-Xue College of Life Information Science and Instrument Engineering,Hangzhou Dianzi University,Hangzhou,Zhejiang zhangxx_rs@163.com 
HUANG Wen-Jiang Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing huangwj@radi.ac.cn 
WU Kai-Hua College of Life Information Science and Instrument Engineering,Hangzhou Dianzi University,Hangzhou,Zhejiang wukaihua@hdu.edu.cn 
Abstract:In this study, a simulated foliar spectral dataset based on the empirical PROSPECT model was generated according to variations of chlorophyll content (Cab) , carotenoid content (Car) , and leaf water content (LWC) .The spectra data were then resampled to a gradient of spectral resolutions and conducted a CWA analysis.The analysis of the spectral resolution impact on retrieving the plant biophysical and biochemical parameters was then performed.The results showed that: (1) CWA can be used to successfully extract sensitive features and to establish retrieving models of parameters including Cab, Car and LWC with high accuracy. (2) With decline of spectral resolution, the number of sensitive features, their correlation, and retrieving accuracy tend to decrease.However, the decline amplitude and the inflection point of the decline curves are all different, which reflected the different impact of the spectral resolution different for different parameters. (3) A significant difference on the sensitivity of spectral resolution was found among different plant biophysical and biochemical parameters, with the LWC appeared to be the most insensitive, followed by Cab, and Car.Based on this result, in retrieving Car, Cab and LWC with CWA, a reasonable result is expected only if the spectral resolution is no lower than 8 nm, 32 nm and 64 nm, respectively.The present study provides a basic understanding in selection of hyperspectral sensors for retrieving and monitoring of plant biophysical and biochemical parameters with the CWA method.
keywords:Continuous wavelet analysis, Hyperspectral remote sensing, Plant biophysical and biochemical parameters, Spectral resolution
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Copyright:《Journal of Infrared And Millimeter Waves》