利用正交信号校正消除水分影响的银川平原土壤盐分高光谱反演

Hyperspectral inversion of soil salinity after correcting moisture effect in Yinchuan Plain using orthogonal signals

高光谱遥感是监测土壤盐渍化的重要手段之一,但野外光谱反射率易受土壤水分的影响,导致盐分监测精度难以保证。为有效消除水分因素,提高土壤含盐量反演精度,该研究以银川平原盐渍化土壤为研究对象,以野外土壤光谱反射率(reflectance,Ref)和实测土壤含盐量为数据源,分析不同含水率的土壤光谱特征,将反射率经过一阶微分(first derivative of reflectance,FDR)、正交信号校正(orthogonal signal correction,OSC)和一阶微分-正交信号校正(first derivative of reflectance-orthogonal signal correction,FDR-OSC)变换,分析各光谱数据与含盐量、含水率的相关性,确定最佳“除水”方法,然后基于支持向量机(support vector machine,SVM)建立土壤含盐量反演模型。结果表明:1)含水率与土壤光谱反射率呈反比,光谱在1430、1950、2200 nm附近存在吸收带,1950 nm附近为最主要吸收波段,且存在向长波漂移的现象。2)光谱数据与含水率相关性由强到弱的顺序为:Ref、OSC、FDR、FDR-OSC;与含盐量相关性由强到弱的顺序为:FDR-OSC、FDR、OSC、Ref。3)基于FDR-OSC“除水”的SVM含盐量模型决定系数R_(c)^(2)、R_(p)^(2)和相对分析误差(relative prediction deviation,RPD)分别达到0.952、0.960和5.04,具有极强的拟合和反演能力。研究结果可为银川平原及同类地区土壤含盐量的精准监测提供科学依据。

Hyperspectral remote sensing has been one of the most important technologies to monitor soil salinization.However,soil moisture can also interfere with the acquisition of field spectral images and then the prediction of soil salinity.The aim of this study was to effectively eliminate the effect of soil moisture,thereby improving the inversion accuracy of soil salinity.Field spectral reflectance(Ref)was collected from the Yinchuan Plain of China.The soil salt content was then measured to analyze the spectral characteristics of soils with different moisture content.The first derivative of reflectance(FDR),orthogonal signal correction(OSC),and their combination(FDR-OSC)were also employed to transform the spectral data.A systematic evaluation was performed on the correlations of original and transformed spectral data with the soil salt and moisture content.A soil salt content inversion model with the support vector machine(SVM)was finally established after removing the moisture effect.The results showed that:1)The overall change in soil salt content was striking(0.30-14.98 g/kg),indicating a strong variability across the study area.Soil pH ranged from 7.82 to 9.58,with a small standard deviation and weak variability.Soil moisture content was ranged between 2.49%and 29.29%,representing a moderate variability.2)An inverse relationship emerged between soil moisture content and the original spectral reflectance,with the three absorption bands near 1430,1950,and 2200 nm,respectively.The principal absorption wavelength was near 1950 nm,indicating a long-wave drift pattern.The reflectance values were reduced for the better drift of the absorption valley using the OSC,compared with Ref.The bandwidth and depth of the three moisture absorption bands all converged,despite the lower differential reflectance values from the FDR transformation curve.3)The correlation between soil spectral data and moisture content was followed the descending order:Ref,OSC,FDR,FDR-OSC,indicating that FDR-OSC performed better than OSC and FDR to remove the moisture effect.The correlation between soil spectral data and soil salt content was followed the descending order:FDR-OSC,FDR,OSC,Ref,indicating that the highest sensitivity of spectral data was transformed by FDR-OSC to soil salinity.Only five bands in the 400-2400 nm wavelength range of Ref were selected as the sensitive bands(R^(2)≥0.50,P<0.05),much fewer than 11 and 18 sensitive bands of OSC and FDR,respectively.The highest number of sensitive bands was obtained by FDR-OSC,reaching 26.The increased sensitive bands of OSC,FDR,and FDR-OSC mainly comprised near-infrared long waves.4)Compared with the Refbased model,the soil salt content inversion model with FDR-OSC performed better fitting and inversion,as the modeling coefficient of determination(R_(c)^(2)),verification of coefficient of determination(R_(p)^(2)),and relative prediction deviation(RPD)were 0.952,0.960 and 5.04,respectively.5)Spatial interpolation by inverse distance weighting revealed that the slightly and moderately salinized soils covered 76.0%of the Yinchuan Plain,whereas the strongly salinity soil and salinity soils only accounted for 2.5%.The areas with the high soil salinity were concentrated mainly in the central and northwestern parts of the study area,with the low soil salinity in the northeastern and southern parts.In conclusion,the FDR-OSC can provide an effective way to eliminate the effect of soil moisture on spectral reflectance,thereby improving the inversion accuracy of soil salinity.The findings can also provide scientific evidence for the high-precision monitoring of soil salinization using hyperspectral remote sensing.