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以新疆渭干河—库车河三角洲绿洲为例,利用实测得到的不同盐渍化程度的盐渍土高光谱数据和电磁感应数据(EM38)协同构建土壤高光谱盐分指数遥感监测模型,将该模型通过尺度效应转换用于校正传统的Landsat-TM多光谱遥感影像的土壤盐分光谱指数,用校正过的TM影像进行区域土壤盐分的反演,并利用实测土壤盐分数据对反演结果进行分析与验证。结果表明:将高光谱和电磁感应数据与多光谱遥感技术相结合进行区域土壤盐渍化信息的提取,其精度和反演效果(R2=0.799 3,p<0.01)明显优于传统多光谱遥感方法中单纯利用土壤盐分指数所建立的监测模型(R2=0.587 4,p<0.01),为今后更好地实现土壤盐渍化的高精度遥感动态监测研究提供了科学依据。
Taking the Weigan-Kuqa River delta oasis in Xinjiang as an example, the hyperspectral remote sensing model of soil hyperspectral salt index was established by using the measured salinized soil hyperspectral data and electromagnetic induction data (EM38) The model was used to calibrate the soil salinity index of the traditional Landsat-TM multispectral remote sensing image by scale effect conversion. The soil salinity was inverted with the corrected TM image. The results of the inversion were analyzed with the measured soil salinity data. verification. The results showed that the combination of hyperspectral and electromagnetic induction data with multispectral remote sensing technology could extract regional soil salinization information, and its accuracy and inversion effect (R2 = 0.799 3, p <0.01) was significantly better than that of traditional multispectral remote sensing In the method, the monitoring model (R2 = 0.587 4, p <0.01) established solely by the soil salinity index provided the scientific basis for the better realization of high-precision remote sensing dynamic monitoring of soil salinization in the future.