基于综合高光谱指数的区域土壤盐渍化监测研究

Study on the Soil Salinization Monitoring Based on Synthetical Hyperspectral Index

选取新疆塔里木盆地北缘渭干河-库车河三角洲绿洲盐渍化土壤、植被及其光谱反射率为研究对象,对实测土壤、植被高光谱进行包络线、倒数、对数、均方根、一阶微分等各种光谱变换,分析并确定反映盐渍化程度最敏感的波段,结果表明:实测高光谱土壤、植被一阶微分光谱变换对土壤盐渍化响应程度最敏感;基于实测综合光谱指数的盐渍化监测高光谱模型可以准确提取土壤盐渍化信息,明显优于传统遥感方法中单纯利用植被指数或者土壤盐分指数的模型,对土壤盐渍化的高精度遥感监测研究具有较好促进作用。

The present paper selected the spectral reflectivity of saline soil and vegetation of Weigan-Kuqa River Delta Oasis in the northern margin of the Tarim Basin in Xinjiang as objects, and used various spectral transforms to process the data with con- tinum removed methods, derivate spectra, reciprocal, first order differentia[ and root mean square etc, then analyzed the spec- trum features and decided the most sensitive band ranges most relevant to salinization, and used field hyperspectral vegetation in- dex, soil salinity index and measured synthetical spectral index to respectively establish hyperspectral quantitative models which could evaluate the soil salinization degrees. By comparing various spectral transformations of hyperspectral data the result showed that the first derivative of measured soil and vegetation hyperspectral were most sensitive to soil salinization degrees. The hyperspectral quantitative model based on measured synthetical spectral index could monitor soil salinization accurately and was better than the models simply based on vegetation index or soil salinity index The research provided some scientific basis with soil salinization detection.