Prediction model of salt content in salinized soil based on hyperspectral data
Spectral reflectance of typical salinized soil collected from Bayannur Sumu,Horqin Middle Banner of Inner Mongolia Autonomous Region was measured,and spectral characteristics of soil with different salinization degrees were analyzed.Original spec-tral reflectance was transformed into square root,logarithm,logarithmic reciprocal,reciprocal and its first and second order differential,and prediction model of soil salt content was established by using multiple stepwise linear regression analysis method.Results showed that,spectral curves of soil with different salt content were basically the same in morphological characteristics.The higher the salt con-tent,the greater the reflectivity.After mathematical transformation,positive and negative correlation between spectral reflectance and soil salt content was enhanced,especially after first-order and second-order differential transformation,correlation was significantly en-hanced.For soil samples with salt content less than 7 g/kg(non-saline soil),correlation between original spectral logarithmic first-or-der differential reflectance and salt content was the highest,and correlation coefficient was the highest at 1 490 nm,which was-0.5 898,while for soil samples with salt content greater than 7 g/kg(saline soil),correlation between original spectral logarithmic first-order dif-ferential reflectance and soil salt content was the highest,correlation coefficient was the highest at 727 nm,which was-0.5 591.In pre-diction model established by multiple stepwise linear regression,the second order differential model of original spectrum was the best for non-saline soil,and the R2 was 0.7 292.Logarithmic second order differential model was the best for saline soil,and the R2 was 0.8 718.It could be used for rapid determination of salt content in saline-alkali soil.
hyperspectralsoil salinitysalinized soilprediction modelstepwise multiple linear regression
万方数据
维普
