文献类型： 外文期刊

作者： Jing Xia ¹ ; Huang Wen Jiang ¹ ; Wang Ji Hua ¹ ; Wang Jin Di ² ; Wang Ke-ru ³ ;

作者机构： 1.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

2.Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

3.Shihezi Univ, Coll Agr, Shihezi 832003, Peoples R China

关键词： Cotton; Verticlllium wilt; Severity level; Hyperspectral characteristic variables; Retrieval model

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： 2009 年 29 卷 12 期

页码：

收录情况： SCI

摘要： The correlation of cotton leaf verticillium will severity level with raw hyperspectral reflectance. first derivative hyperspectral reflectance, and hyperspectral characteristic parameters was analyzed. Using linear and nonlinear regression methods, the hyperspectral remote sensing retrieval models of verticillium wilt severity level with remote sensing parameters as independent variables were constructed and validated. The result showed that spectral reflectance increased significantly in visible and short infrared wave band with the increase in the severity level, and this is especially significant in visible hand. The raw spectral reflectance has the maximum coefficient of determination at 694 rim (R-2 = 0. 4616) with severity level and the logarithm model constructed with reflectance at this point is the better one as compared to linear model, By the precision evaluation of retrieval models, the. linear model with the first derivative reflectance at. 717 nm as independent variable was proved to be the best, with R-2 = 0. 4.88 9, RMSE = 0. 257 1. and relative error-12.74%, for the estimation of verticillium wilt severity level of cotton leaf. The results provide a good basis for further studying monitoring mechanism of cotton verticillium wilt by remote sensing data, and have an important application in acquiring cotton disease information using hyperspectral remote sensing.