Title :
Hyperspectral remote sensing estimation model for rape moisture content under different levels of water stress
Author :
Xiaodong, Zhang ; Hanping, Mao ; Zhiyv, Zuo ; Jun, Sun ; Hongyan, Gao
Author_Institution :
Key Lab. of Modern Agric. Equip. & Technol., Jiangsu Univ., Zhenjiang, China
Abstract :
It was developed that using spectral analysis to quantitatively analyze the rape water stress condition. Region stepwise regression was proposed to select the characteristic wavelength of rape moisture content and to establish the model between the moisture content and the spectral reflectance at characteristic wavelength of rape. From the spectral datum of rape samples under different water levels, it was found that the linear relationships between moisture content of rape and spectral reflectance value at 960nm, 1450nm and 1650nm are very notable. The correlation coefficient between the predict value and the measured value is 0.87, the RMSE is 4.57. The results show that the method of stepwise regression could select the characteristic wavelengths of rape moisture content accurately and enhance model forecast precision.
Keywords :
agriculture; correlation methods; crops; geophysical signal processing; mean square error methods; moisture; reflectivity; regression analysis; remote sensing; spectral analysis; water; RMSE; characteristic wavelength; correlation coefficient; hyperspectral remote sensing estimation model; model forecast precision; oil crop; rape moisture content; rape water stress condition; region stepwise regression; spectral analysis; spectral reflectance; water level; Correlation; Equations; Feature extraction; Mathematical model; Moisture; Predictive models; Reflectivity; characteristic wavelength; moisture content; rape; spectral reflectivity;
Conference_Titel :
New Technology of Agricultural Engineering (ICAE), 2011 International Conference on
Conference_Location :
Zibo
Print_ISBN :
978-1-4244-9574-0
DOI :
10.1109/ICAE.2011.5943801