Using Canopy Hyperspectral Ratio Index to Retrieve Relative Water Content of Wheat Under Yellow Rust Stress

文献类型： 外文期刊

第一作者： Chen Yun-hao

作者： Chen Yun-hao;Jiang Jin-bao;Huang Wen-jiang

作者机构：

关键词： Wheat; Canopy spectral; Yellow rust; Relative water content(RWC); Inversion models

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： 2010 年 30 卷 7 期

页码：

收录情况： SCI

摘要： The aim of this paper is to estimate canopy relative water contents (RWC) of winter wheat under yellow rust stress by using hyperspectral remote sensing. The canopy reflectance of winter wheat that infected different severity yellow rust was collected and the disease index (DI) of the wheat was investigated respectively in the fields, whereafter the wheat was sampled corresponding to the canopy reflectance measurements and the RWC of the whole wheat were measured in the Laboratory. The research showed that the canopy spectra reflectance gradually decreased in the near-infrared (NIR) region (900-1 300 nm) with RWC reduction, however, canopy spectra reflectance gradually increased in the short-wave-infrared (SWIR) region (1 300-2 500 nm), and there was just higher minus correlation between RWC and DI. Smoothing the canopy spectra, the ratio indices were built by using the sensitive bands for water in NW and SWIR, and then the estimation RWC linear models were built by using ratio indices as variables, and the model inversion precision and stability were analyzed and compared for estimation RWC. The result indicated that the inversion precision and the stability of the model with ratio index R-1 300/R-1 200 as variable excel other models, the linear model's RMSE is 3. 43, and the relative error is 4. 78%. So, this study results not only can provide assistant information for diagnosing wheat disease but also can supply theories and methods for inversion vegetation RWC by using hyperspectral images in the future.

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