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

作　　者：陈睿华 王怡婧 张俊华[3] 丁启东 贾科利[1] 许鑫杰 CHEN Ruihua;WANG Yijing;ZHANG Junhua;DING Qidong;JIA Keli;XU Xinjie(College of Geography and Planning,Ningxia University,Yinchuan 750021,China;Xi’an Meihang Remote Sensing Information Co.Ltd.Xi’an 710199 China;Breeding Base for Sate Key Laboratory of Land Degradation and Ecological Restoration in Northwest China,Ningxia University,Yinchuan 750021,China;The Key Laboratory of Polymer Processing Engineering of the Ministry of Education,South China University of Technology,Guanghou 510641,China)

机构地区：[1]宁夏大学地理科学与规划学院,银川750021 [2]西安煤航遥感信息有限公司,西安710199 [3]宁夏大学西北土地退化与生态恢复国家重点实验室培育基地,银川750021 [4]华南理工大学聚合物成型加工工程教育部重点实验室,广州510641

出　　处：《农业工程学报》2023年第19期122-130,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家重点研发计划项目(2021YFD1900602);国家自然科学基金项目(42067003,42061047);宁夏科技创新领军人才(2022GKLRLX02)。

摘　　要：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 rem

关 键 词：土壤 盐分 水分 野外高光谱 一阶微分 正交信号校正 支持向量机 反距离权重法 

分 类 号：S127[农业科学—农业基础科学] S153.6