Inversion of Organic Matter Content of the North Fluvo-Aquic Soil Based on Hyperspectral and Multi-Spectra

文献类型： 外文期刊

第一作者： Wang Yan-cang

作者： Wang Yan-cang;Zhu Jin-shan;Wang Yan-cang;Gu Xiao-he;Long Hui-ling;Xu Peng;Liao Qin-hong;Wang Yan-cang;Gu Xiao-he

作者机构：

关键词： Organic matter; Fluvo-aquic soil; Multi-spectra; Hyperspectral; Partial least squares regression

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2014 年 34 卷 1 期

页码：

收录情况： SCI

摘要： The present study aims to assess the feasibility of multi-spectral data in monitoring soil organic matter content. The data source comes from hyperspectral measured under laboratory condition, and simulated multi-spectral data from the hyperspectral. According to the reflectance response functions of Landsat TM and HJ-CCD (the Environment and Disaster Reduction Small Satellites, HJ), the hyperspectra were resampled for the corresponding bands of multi-spectral sensors. The correlation between hyperspectral, simulated reflectance spectra and organic matter content was calculated, and used to extract the sensitive bands of the organic matter in the north fluvo-aquic soil. The partial least square regression (PLSR) method was used to establish experiential models to estimate soil organic matter content. Both root mean squared error (RMSE) and coefficient of the determination (R-2) were introduced to test the precision and stability of the modes. Results demonstrate that compared with the hyperspectral data, the best model established by simulated multi-spectral data gives a good result for organic matter content, with R-2=0. 586, and RMSE=0. 280. Therefore, using multi-spectral data to predict tide soil organic matter content is feasible.

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