Retrieval of soil organic matter content from hyper-spectra in Songnen Plain

doi:10.7523/j.issn.2095-6134.2011.2.008

Abstract

Abstract:

A total of 252 soil samples were collected in Songnen Plain. Reflectance was measured in a controlled laboratory environment. After pre-processing of the primitive spectra, hyper-spectral models for predicting soil organic matter content were built up by using the methods of Stepwise Multiple Linear Regression (SMLR) and Partial Least Squares Regression(PLSR). The results show that the models using the two methods are capable of predicting SOM content and the model using PLSR is more robust.

Key words: hyper-spectral, soil organic matter, stepwise multiple linear regression, partial least squares regression

CLC Number:

TP79

WU Yan-Qing, ZHANG Bai, SONG Kai-Shang, LIU Huan-Jun, WANG Zong-Ming, LIU Dian-Wei. Retrieval of soil organic matter content from hyper-spectra in Songnen Plain[J]. , 2011, 28(2): 187-194.

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