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A Field-Based Pushbroom Imaging Spectrometer for Estimating Chlorophyll Content of Maize

文献类型： 外文期刊

作者： Zhang Dong-yan 1 ; Liu Rong-yuan 2 ; Song Xiao-yu 2 ; Xu Xin-gang 2 ; Huang Wen-jiang 2 ; Zhu Da-zhou 2 ; Wang Ji-hua 1 ;

作者机构： 1.Zhejiang Univ, Inst Remote Sensing & Informat Tech, Hangzhou 310029, Zhejiang, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China

关键词： Hyperspectral imaging; Vegetation indices; Corn; Chlorophyll content

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2011 年 31 卷 3 期

页码：

收录情况： SCI

摘要： As an image-spectrum merging technology, the field-hperspectral imaging technology is a need for dynamic monitoring and real-time management of crop growth information acquiring at field scale in modern digital agriculture, and it is also an effective approach to promoting the development of quantitative remote sensing on agriculture. In the present study, the hyperspectral images of maize in potted trial and in field were acquired by a self-development push broom imaging spectrometer (PIS). The reflectance spectra of maize leaves in different layers were accurately extracted and then used to calculate the spectral vegetation indices, such as TCARI, OSAVI, CART and NDVI. The spectral vegetation indices were used to construct the prediction model for measuring chlorophyll content. The results showed that the prediction model constructed by spectral index of MCARI/OSAVI had high accuracy. The coefficient of determination for the validation samples was R-2=0. 887, and RMSE was 1. 8. The study indicated that PIS had extensive application potentiality on detecting spectral information of crop components in the micro-scale.

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