采用高光谱指数的龟裂碱土盐碱化信息提取与分析

Analysis and extraction of takyr solonetzs salinization information based on hyperspectral indices

以宁夏平罗县为研究对象,将Unispec-SC便携式光谱仪测得的盐渍化光谱数据和实验室测得的土壤含盐量数据作为基础数据源。运用高光谱数据处理方法,分析不同盐渍化地区植被的光谱特征曲线;对实测植被、土壤光谱曲线进行对数、均方根和一阶微分等变换,筛选与土壤含盐量相关性最好的变换形式和特征波段构造盐分指数SI及多种植被指数,利用多元非线性回归分析建立土壤盐渍化遥感监测模型。结果表明:土壤、植被光谱一阶微分变换与土壤含盐量响应敏感;协同盐分指数SI和植被指数MSAVI构造的土壤盐渍化指数模型,模拟值和实测值相关系数达到0.758 9,模拟效果很好,实现快速提取该区域的土壤盐渍化信息。

In the present study,Pingluo of Ningxia Province in China was taken as the study area,and spectral data obtained by Unispec-SC,the value of soil salt content measured by experiment were taken as the basic data.Hyper-spectral data processing method was used to analyze spectral characteristics of different levels of salinization area vegetation.Spectral data were transformed in 16 different approaches,including logarithm,root mean squares,and first order differentiation.Correlation analysis was carried out between the obtained spectra and soil salinity.The most sensitive bands was selected,soil index and vegetation index were built.Nonlinear regression was employed to establish soil salinization remote sensing monitoring model.The results show that by comparing various spectral transformations,the first order differential of soil spectral was the most sensitive to soil salinization degrees.The model was based on the spectral index,including SI and MSAVI,and it could monitor soil salinization accurately.The correlation between simulated values and measured values was 0.758 9.The soil salinization could be achieved rapidly in the area.