Li Ya Li, Qiao Jiang Fei, Dong Tian Yu, Wang Hai Jiang
Key Laboratory of Oasis Ecology Agriculture of Xinjiang Bingtuan, Shihezi University, Shihezi 832003, Xinjiang, China.
Ying Yong Sheng Tai Xue Bao. 2016 Dec;27(12):3807-3815. doi: 10.13287/j.1001-9332.201612.021.
In order to monitor soil water and salt content of saline soil conveniently and quickly, this paper took the typical salinization irrigation district of Xinjiang as the research object, obtained the spectral curve of soil water and salt content by using portable spectrometers based on the hyperspectral technology, transformed the original spectra of soil using the first order differential, second order differential and continuum removal methods. The results showed that the transformation of the original spectral data was beneficial to fingerprint band extraction of soil properties, and the method was not same in soils with different textures. In loam soil, continuum removal analysis was the best method for extraction of characteristic bands when the soil water content was 0% and 10%, first order differential equations were the best method when the soil water content was 15%, and second order differential equations were the best method when the soil water content was 19%. In sandy soil, continuum removal analysis was the best method for extraction of characteristic bands when the soil water content was 0%, whereas second order differential equations were the best method when soil water content was 10%, 15% or 19%. The transformed data were screened for inversion models of soil water and salt content by using the partial least squares regression method. When thesalinity was < 6.38 mS·cm in loam soil and < 5.94 mS·cm in sandy soil, the decision coefficients (R), internal cross validation (R), and external validation (R) were greater than 0.65 (P<0.05). When the soil moisture content was less than 16% in loam soil and 12% in sandy soil, the inversion accuracy of model was higher. The results would provide a reference threshold for si-multaneously monitoring soil water and salt content in salinized areas.
为了方便、快速地监测盐碱土的土壤水分和盐分含量,本文以新疆典型盐碱化灌区为研究对象,利用基于高光谱技术的便携式光谱仪获取土壤水分和盐分含量的光谱曲线,采用一阶微分、二阶微分和连续统去除法对土壤原始光谱进行变换。结果表明,原始光谱数据的变换有利于土壤性质指纹波段的提取,且不同质地土壤的方法不同。在壤土中,当土壤含水量为0%和10%时,连续统去除分析是提取特征波段的最佳方法;当土壤含水量为15%时,一阶微分方程是最佳方法;当土壤含水量为19%时,二阶微分方程是最佳方法。在砂土中,当土壤含水量为0%时,连续统去除分析是提取特征波段的最佳方法;而当土壤含水量为10%、15%或19%时,二阶微分方程是最佳方法。利用偏最小二乘回归法对变换后的数据进行土壤水分和盐分含量反演模型筛选。当壤土中盐分<6.38 mS·cm且砂土中盐分<5.94 mS·cm时,决定系数(R)、内部交叉验证(R)和外部验证(R)均大于0.65(P<0.05)。当壤土中土壤含水量小于16%且砂土中土壤含水量小于12%时,模型反演精度较高。研究结果可为盐碱化地区土壤水分和盐分含量的同步监测提供参考阈值。