Acta Optica Sinica, Volume. 37, Issue 10, 1028001(2017)
Inverting Study on Soil Water Content Based on Harmonic Analysis and Hyperspectral Remote Sensing
Hyperspectral inversion of soil water content is a current hot research topic. Hengshan County of Shaanxi Provice, which has diverse soil types, is taken as study area. Soil samples are collected in the field and their spectra are tested indoor using ASD Field Spec FR ground object spectrometer. Moreover, the soil water content is calculated by weighing method and the spectral features of the soil samples with different water contents are analyzed. For the construction issue of factors in the spectral inversion of soil water content, and based on the study of inversion input factor generation method and the existing problems of first order differential (FD)-principal component analysis (PCA), wavelet packet transform (WPT)-FD-PCA, the method of constructing the inversion input factor of WPT-FD-HA-PCA based on harmonic analysis (HA) is proposed. On the basis of the three above-mentioned inversion input factors, three back propagation (BP) models of soil water content (FD-PCA-BP, WPT-FD-PCA-BP, WPT-FD-HA-PCA-BP) are constructed. Comparison between the measured values of soil water content and the inversion values of the three BP models shows that the inversion accuracy of WPT-FD-HA-PCA-BP model is the highest. The coefficient of determination (R2) and root mean square error between measured value and inversion value is 0.9599 and 1.667% respectively, and it performs better than the other two models. The results show that WPT and HA can effectively suppress the spectral noise and compress the signal, and to some extent, the inversion precision of soil water content is improved obviously.
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Xueqin Jiang, Qin Ye, Yi Lin, Xican Li. Inverting Study on Soil Water Content Based on Harmonic Analysis and Hyperspectral Remote Sensing[J]. Acta Optica Sinica, 2017, 37(10): 1028001
Category: Remote Sensing and Sensors
Received: Apr. 12, 2017
Accepted: --
Published Online: Sep. 7, 2018
The Author Email: Ye Qin (yeqin@tongji.edu.cn)