利用HJ1A-HSI数据定量反演松辽平原土壤含盐量

Quantitative Inversion of Salinity Based on Hyper-spectral Data in Songliao Plain

以HSI高光谱影像作为数据源,使用FLAASH大气校正模型对HSI影像进行大气校正,获得地表反射率图像。将反射率图像进行多种数学变换后,采用地理信息系统的分析方法,与土壤含盐量的实测值进行偏最小二乘回归分析,定量反演松辽平原土壤盐碱含量。结果表明:HSI高光谱影像的反射率经过倒数(1/R)、一阶微分(R′)变换后,能够显著提高与盐碱土含盐量的相关系数R2,且相关系数分别达到0.818和0.851,均方根误差分别为0.770和0.694。该文在土壤含盐量的定量反演方面,探索使用了HSI影像作为新的数据源,并为松辽平原土壤盐分含量的精确、定量、快速获取及盐碱化防治等方面提供重要参考。

HSI sensor of HJ - 1A is the first hyper-spectral image in China. It has high time resolution （96 hours） and fine spectrum （5 nm）, which will be widely used in resources, environment, disaster monitoring, etc. However, as a new sensor, application of HSI data is still in the exploratory stage in China. To get surface reflectance of HSI images, atmospheric correction model of FLAASH was used to correct the HSI images. The reflectance after a variety of mathematical transformation was carried on par- tial least squares regression analysis with the measured values of soil salinity to retrieve the salinity in Songliao plain using the analysis method of GIS. The results show that, reflectance of HSI hyper-spectral images after the countdown and the first-order differential transform can significantly improve the correla- tion coefficient with salinity of saline-alkali soil. The correlation coefficient was 0.818 and 0.851. The Root-Mean-Square Error was 0.770 and 0.694. HSI images were used as new data source in quantitative inversion of soil salinity, which has provided significant reference for getting salinity precisely, quantita- tively, quickly and salinization control in Songliao plain.