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Proceedings Paper

Wavelet Transform (WT) and neural network model applied to canopy hyperspectral data for corn Chl-a estimation in Songnen Plain, China
Author(s): Dongmei Lu; Kaishan Song; Lin Li; Zongming Wang; Jia Du; Lihong Zeng; Xiaochun Lei
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Paper Abstract

In this study, we present spectral measurements of corn chlorophyll content in Changchun (eight times in 2003) and Hailun (five time in 2004), both of which lie in the Songnen Plain, China. Corn canopy reflectance and its derivative reflectance were subsequently used in a linear regression analysis against Chl-a concentration on one by one spectral reflectance. It was found that determination coefficient for Chl-a concentration was high in blue, red and near infrared spectral region, and it was low in green and red edge spectral region, however Chl-a concentration obtained its high determination coefficient in blue, green and red edge spectral region, especially in red edge region with derivative reflectance. Regression models were established based upon 6 spectral vegetation indices and wavelet coefficient, reflectance principal components as well. It was found that wavelet transforms is an effective method of hyperspectral reflectance feature extraction for corn Chl-a estimation, and the best multivariable regressions obtain determination coefficient (R2) up to 0.87 for Chl-a concentration. Finally, neural network algorithms with both specific band reflectance and wavelet coefficient as input variables were applied to estimate corn chlorophyll concentration. The results indicate that estimation accuracy improved with nodes number increasing in the hidden layer, and neural network performs better with wavelet coefficient than that with specific band reflectance as input variables, determination coefficient was up to 0.96 for Chl-a concentration. Further studies are still needed to refine the methods for determining and estimating corn bio-physical/chemical parameters or other vegetation as well in the future.

Paper Details

Date Published: 7 September 2010
PDF: 12 pages
Proc. SPIE 7799, Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII, 77990P (7 September 2010); doi: 10.1117/12.859690
Show Author Affiliations
Dongmei Lu, Jilin Institute of Architecture and Civil Engineering (China)
Kaishan Song, Northeast Institute of Geography and Agricultural Ecology (China)
Indiana Univ.-Purdue Univ. Indianapolis (United States)
Lin Li, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Zongming Wang, Northeast Institute of Geography and Agricultural Ecology (China)
Jia Du, Northeast Institute of Geography and Agricultural Ecology (China)
Lihong Zeng, Northeast Institute of Geography and Agricultural Ecology (China)
Xiaochun Lei, Northeast Institute of Geography and Agricultural Ecology (China)


Published in SPIE Proceedings Vol. 7799:
Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII
Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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