干旱区土壤盐渍化遥感估测模型研究——以宁夏平罗县为例

Research on models for the remote sensing of soil salinization in the arid region——A case of Pingluo, Ningxia

以宁夏平罗县为研究靶区,以野外实测的高光谱数据和土壤含盐量为基础数据源,进行光谱反射率及其变换形式与土壤含盐量的相关分析,筛选敏感波段,建立高光谱土壤盐分指数模型;通过尺度转化,用原位采集的高光谱盐分指数修正传统遥感影像盐分指数,构建传统影像高精度土壤盐渍化遥感监测模型,并利用实测土壤含盐量对反演结果进行分析与验证。结果表明,高光谱盐分指数和实测土壤含盐量的相关性明显高于传统遥感影像光谱数据;将高光谱数据和传统Landsat-8 OLI影像数据结合,提取的区域土壤盐渍化信息精度明显提高,解决了实测数据和影像之间的时间滞后性问题。

In order to establish a model for the remote sensing of soil salinization in the arid region, Pingluo of Nningxia Province in China, a typical soil salinization area, was selected to study. Firstly, based on the measured hyperpectral data of different soil salinization extent and soil salinity, a hyperspectral soil salinization index monitoring model was established by correlation analysis. Then the high precision soil salinization remote sensing monitoring model from landsat images was build by using hyperspectral soil salinization index monitoring model to calibrate the soil salinity index calculated from the situ-landsat-8 images in view of scaling transformation method. Lastly, the obtained results based on the model were tested further by the measured data. it is found that the soil salinity index model constructed was best model among the different salinization monitoring model. It showed high precision on the soil salinization information and avoided the time lag between the measured data and the imaging.