基于HJ1A-HSI超光谱影像的县域耕地土壤盐渍度预测研究

Estimation of Soil Salinity in Cltivated Land at County Scale Based on HJ1A-HIS Hyperspectral Image

针对目前干旱半干旱地区存在的土壤盐渍化问题,以北疆典型盐渍化地区玛纳斯县为研究区,以HJ1A-HSI超光谱影像为主要数据源,结合实测耕地土壤含盐量,分析光谱反射率及其变化形式与盐分含量的相关性,筛选耕地盐分响应的敏感波段,利用多元回归分析方法,建立基于环境卫星影像的耕地含盐量定量反演模型。结果表明,盐分的HSI影像响应波段均位于可见光与近红外波段间,以500～549 nm和696～776 nm范围最佳,相关系数均大于0.5;HSI反射率对数（lgP）预测模型精度最高,可实现对研究区耕地土壤盐分遥感反演。

Soil salinization was widely distributed in the arid and semi-arid region of China. The typical saline area in northern of Xinjiang, Manas County was taken as the study area. The environmental satellite hyperspectral imaging（HSI） was taken as the main data source, combined with the measured cultivated soil salinity. The author analyzed correlation between spectral reflectance and salt content and screened sensitive band of salinity response in farmland, established farmland salt content quantitative inversion model based on environmental satellite images by multiple linear regression. The results showed that： salt response bands of HSI image located in the visible and near-infrared bands, between 500 to 549 nm and 696 to 776 nm range, correlation coefficients were greater than 0.5. The best HSI reflectivity（lgP） predictive accuracy of the model could be realized on the area of farmland soil salinity remote sensing inversion.