CAJ | 학술논문

探明土壤盐渍化的高光谱遥感监测机理，对改善高光谱遥感监测精度具有重要意义。以南疆地区温宿县、和田县、拜城县的水稻土为研究对象，通过分析土样的高光谱数据和室内测定的盐分与电导率数据，研究了耕作土壤含盐量与电导率的关系，并比较了含盐量和电导率与不同光谱指标的相关性以及二者高光谱反演的精度。结果表明，南疆水稻土的含盐量与电导率的相关性较低，二者之间的关系因地区差异而有较大的变化；含盐量与反射率、一阶微分、连续统去除之间的相关性要优于电导率，特别在一些土壤盐渍化的敏感波段尤为突出；以含盐量建立的多元线性回归、主成分回归、偏最小二乘回归模型的决定系数和相对分析误差均高于电导率。研究表明高光谱信息对土壤含盐量的响应比电导率更敏感，以含盐量为监测指标的高光谱反演精度明显要优于电导率。该结果可为提高土壤盐渍化高光谱遥感监测精度提供理论依据。
탐명토양염지화적고광보요감감측궤리，대개선고광보요감감측정도구유중요의의。이남강지구온숙현、화전현、배성현적수도토위연구대상，통과분석토양적고광보수거화실내측정적염분여전도솔수거，연구료경작토양함염량여전도솔적관계，병비교료함염량화전도솔여불동광보지표적상관성이급이자고광보반연적정도。결과표명，남강수도토적함염량여전도솔적상관성교저，이자지간적관계인지구차이이유교대적변화；함염량여반사솔、일계미분、련속통거제지간적상관성요우우전도솔，특별재일사토양염지화적민감파단우위돌출；이함염량건립적다원선성회귀、주성분회귀、편최소이승회귀모형적결정계수화상대분석오차균고우전도솔。연구표명고광보신식대토양함염량적향응비전도솔경민감，이함염량위감측지표적고광보반연정도명현요우우전도솔。해결과가위제고토양염지화고광보요감감측정도제공이론의거。
The objective of the present article is to ascertain the mechanism of hyperspectral remote sensing monitoring for soil salinization ,which is of great importance for improving the accuracy of hyperspectral remote sensing monitoring .Paddy soils in Wensu ,Hetian and Baicheng counties of the southern Xinjiang were selected .Hyperspectral data of soils were obtained .Soil salt content (St ) an electrical conductivity of 1∶5 soil-to-water extracts (EC1∶5 ) were determined .Relationships between St and EC1∶5 were studied .Correlations between hyperspectral indices and St ,and EC1∶5 were analyzed .The inversion accuracy of St using hyperspectral technique was compared with that of EC 1∶5 .Results showed that :significant (p<0 .01) relationships were found between St and EC1∶5 for soils in Wensu and Hetian counties ,and correlation coefficients were 0 .86 and 0 .45 ,respective-ly ;there was no significant relationship between St and EC1∶5 for soils in Baicheng county .Therefore ,the correlations between St and EC1∶5 varied with studied sites .St and EC1∶5 were significantly related with spectral reflectance ,first derivative reflec-tance and continuum-removed reflectance ,respectively ;but correlation coefficients between St and spectral indices were higher than those between EC1∶5 and spectral indices ,which was obvious in some sensitive bands for soil salinization such as 660 ,35 , 1 229 ,1 414 ,1 721 ,1 738 ,1 772 ,2 309 nm ,and so on .Prediction equations of St and EC1∶5 were established using multivari-ate linear regression ,principal component regression and partial least-squares regression methods ,respectively .Coefficients of determination ,determination coefficients of prediction ,and relative analytical errors of these equations were analyzed .Coeffi-cients of determination and relative analytical errors of equations between St and spectral indices were higher than those of equa-tions between EC1∶5 and spectral indices .Therefore ,the responses of high spectral information to St were more sensitive than those of high spectral information to EC1∶5 .Accuracy of St predicted from high spectral data was higher than that of EC 1∶5 esti-mated from high spectral data .The results of this study can provide a theoretical basis to improve hyperspectral remote sensing monitoring accuracy of soil salinization .