沙质土壤热红外高光谱特征及其含沙量预测研究

Characteristics of Thermal Infrared Hyperspectra and Prediction of Sand Content of Sandy Soil

为明确土壤热红外高光谱数据反演土壤含沙量的应用潜力,利用102F型便携式傅里叶变换红外光谱仪对沙质土壤进行测量,在进行相关分析和主成分分析的基础上,对土壤发射率光谱特征进行了分析,并采用偏最小二乘回归和主成分回归两种建模方法预测土壤含沙量。结果表明,沙质土壤发射率光谱中二氧化硅的Reststrahlen特征表现明显,在8.13和9.17μm附近具有不对称强二重谱带,并且在12～13μm区间还有两个吸收强度相对较小的发射谷;土壤发射率随着含沙量的增加而降低,尤其是8.2-9.5μm和9.5-10.4μm两个谱段对土壤沙含量变化敏感,相关系数分别达到0.65和0.5以上,这两个谱段对整体光谱变化具有84.07%的贡献率;不同的光谱变量和建模方法在反演精度上存在明显差异,偏最小二乘回归模型的一阶微分光谱反演精度最高,其建模和预测的RMSE分别为0.45和0.53,R2分别为0.960 7和0.943 6,表明热红外高光谱在土壤含沙量预测方面具有很大的应用潜力。

To explore the potential of thermal infrared hyperspecra for retrieving sand content in soil,the sandy soil was measured using a 102F Fourier Transform Infrared Spectroradiometer（FTIR）,and the characteristics of sandy soil＇s emissivity spectra were discussed based on correlation analysis and principal component analysis.Moreover,the sand contents were predicted using two modeling methods： Partial least squares regression（PLSR） and principal component regression（PCR）.The results show that the Reststrahlen feature（RF） of SiO2 is obvious in the emissivity spectra of sandy soil with two large asymmetrical absorption troughs near 8.13 and 9.17 μm and two small troughs in the region of 12~13 μm.Soil emissivity becomes lower when sand content increases,this trend is more evident especially in the regions of 8~9.5 μm and 9.5~10.4 μm of which correlation coefficients are above 0.65 and 0.5 respectively,and these two regions can account for 84.07% of total emissivity variance.Predictive precision varies significantly when sand content is predicted by different modeling methods or spectral variables.The PLSR model can achieve the highest predictive precision by using first-order derivative spectra,and it＇s RMSE of modeling and prediction is 0.45 and 0.53 respectively,and the R2,0.990 7 and 0.983 6,which means that the thermal hyperspectra has promising potential for retrieving sand content in soil.