基于高光谱参数的枫杨叶绿素含量估算模型优化

doi:10.11707/j.1001-7488.20140408

Abstract

Abstract:

In this study, hyperspectral reflectance of Pterocarya stenoptera leaves was measured with an ASD portable spectrometer under different soil water condition. The corresponding chlorophyll concentration was a lso measured. The effects of soil water condition on chlorophyll concentration of P. stenoptera are discussed. In order to estimate chlorophyll content and establish the best estimation model,, and the corresponding correlation coefficient and regression equation between 9 hyperspectral indices and chlorophyll concentration were established. The principal component analysis (PCA) was used to reduce the dimensions of data, while maintaining the data characteristic effectively. The principal component scores were used as the input variable of ANN-BP to estimate chlorophyll concentration. The results showed that different water treatments significantly affected the chlorophyll content of P. stenoptera seedlings. VOG1 had the closest relation to chlorophyll concentration out of the nine hyperspectral indices in this article and the corresponding correlation coefficient was 0.865. The ANN-BP based on PCA containing more band information was used to estimate chlorophyll content, and the correlation coefficient between the predicted and the measured P. stenoptera chlorophyll content was 0.934. Thus, the ANN-BP based on PCA in this article is a good method to be applied to hyperspectral data for estimating P. stenoptera chlorophyll concentration.

Key words: hyperspectrum, chlorophyll concentration, hyperspectral indexes, PCA, ANN-BP

CLC Number:

S718.43

Li Wenmin, Wei Hong, Li Changxiao, Chen Cungen. Optimization of a Model for Estimating Pterocarya stenoptera Chlorophyll Concentration with Hyperspectral Parameters[J]. Scientia Silvae Sinicae, 2014, 50(4): 55-59.

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Optimization of a Model for Estimating Pterocarya stenoptera Chlorophyll Concentration with Hyperspectral Parameters

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