Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System

Sensors

Bo Liu¹  Yue-Min Yue²  Ru Li³  Wen-Jing Shen¹ 

[1] Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China; E-Mails:;Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China; E-Mail:;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; E-Mail:

关键词: field imaging spectroscopy system;    spectral sensor;    chlorophyll;    spectral analysis;   

DOI  :  10.3390/s141019910

来源: mdpi

【 摘 要 】

A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.