NDLI: Diagnosis the dust pollution stress of wheat leaves based on hyperspectral technology

Content Provider	IEEE Xplore Digital Library
Author	Liang Liang Yanjun Li Qin Sun Qin Chen Liping Di Meixia Deng
Copyright Year	2015
Description	Author affiliation: Sch. of Geodesy & Geomatics, Jiangsu Normal Univ., Xuzhou, China (Liang Liang; Yanjun Li; Qin Sun; Qin Chen) \|\| Dept. of Geogr. & Geoinf. Sci., George Mason Univ., Fairfax, VA, USA (Liping Di; Meixia Deng)
Abstract	Wheat leaves under different dust stress intensity were diagnosed with hyperspctrectral technology. A four-level dust stress experiment was conducted using the wheat in growing season as the study object. The spectra of wheat leaves which suffered different stress intensity levels,including severe stress, moderate stress, mild stress and no stress, were collected by ASD FieldSpec®3 spectrometer, and 32 samples were used for each level. All of the samples were divided randomly into two groups, one group with 96 ones used as calibrated set, and another with 32 ones as validated set. The spectra data were then pretreated by the methods of S.Golay smoothing and standard normal variable (SNV), and then the pretreated spectra data were analyzed with principal component analysis (PCA). Using the anterior 6 principal components computed by PCA as the model input variables, and the values of stress level as the output variables, the hyperspectral diagnosis models of dust stress intensity were established. And then the 32 unknown samples in the validated set were predicted by the diagnosis model. The result showed that the accuracy of model prediction was 87.5%, indicated it was feasible to diagnose the dust stress intensity with hyperspctral technology.
Starting Page	192
Ending Page	195
File Size	375013
Page Count	4
File Format	PDF
e-ISBN	9781467380874
DOI	10.1109/Agro-Geoinformatics.2015.7248096
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-20
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dust stress Pollution Accuracy Hyperspectra Computational modeling Agriculture SVM Wheat Stress BP-ANN Hyperspectral imaging Principal component analysis
Content Type	Text
Resource Type	Article

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