盐渍化土壤光谱特征分析与建模

Research on remote sensing monitoring model of soil salinization based on spectrum characteristic analysis

为建立土壤盐渍化遥感监测模型,选取宁夏回族自治区平罗县典型土壤盐渍化发生区域作为研究区,以野外原位光谱测量数据和实验室内测得的土壤含盐量与p H值数据为基础,进行高光谱数据处理,分析不同盐渍化程度土壤的光谱特征;对实测土壤光谱反射率进行倒数、对数、均方根及其一阶微分等光谱变换,计算高光谱指数;与土壤样本含盐量进行相关性分析,筛选盐渍化土壤的光谱特征波段,利用多元线性回归分析建立土壤盐渍化监测模型。研究结果表明:以倒数一阶微分变换后的940 nm和1 094 nm波段作为特征波段构建的土壤盐渍化遥感监测模型最优。

To establish the remote sensing monitoring model for soil salinization, the authors chose the typical soil salinization area in Pingluo County of Ningxia as the study area, and measured the spectral data in the field. These data, together with the values of pH and salinity measured in the laboratory, were taken as the basic data. Hyperspectral data processing method was used to analyze the spectral characteristics of different levels of soil salinization. Spectral data were transformed with 11 different approaches, such as reciprocal, logarithm, root mean square and their first order differentials. After the transformation, the correlation analysis was carried out between the obtained soil spectra and soil salinity. The most sensitive band was selected, and the field spectral sensitive band and soil salinity were used and the multiple linear regression was employed to establish the spectral quantitative models for evaluating the soil salinization degrees. The results show that the reciprocal first order differential of measured soil spectral is most sensitive to soil salinization degrees. The spectral quantitative models based on the wavelengths of 940 nm and 1 094 nm are the best.