CAJ | 학술논문

利用傅立叶热红外光谱仪探测煤田土壤的光谱数据和土壤有机质含量数据，分析了原始光谱发射率的特征，求算原始发射率的一阶、二阶导数，分别建立原始发射率、一阶导数、二阶导数与有机质之间的模型，检验和评价了每个模型的适用性。结果表明：①土壤的有机质含量随着地表地物类型和周边环境的不同而存在明显差异；②无论有机质含量存在多大的差异，热红外光谱发射率随波长的增加而变化的趋势不变；但土壤热红外光谱的发射率在8～11．5μm范围内最敏感，有机质含量的大小会对其敏感性产生影响；③一阶导数、二阶导数的发射率与有机质的相关性明显优于原始发射率数据，发射率数据的导数处理能够有效的增强与有机质之间的相关性，且在该研究区发射率数据的二阶导数与有机质含量相关性最高；④一阶导数和二阶导数的热红外光谱发射率与有机质含量之间的拟合函数效果均较为良好，尤其二阶导数发射率的指数函数效果最佳；一阶导数的多元逐步回归拟合模型预测能力略优于线性函数模型。
이용부립협열홍외광보의탐측매전토양적광보수거화토양유궤질함량수거，분석료원시광보발사솔적특정，구산원시발사솔적일계、이계도수，분별건립원시발사솔、일계도수、이계도수여유궤질지간적모형，검험화평개료매개모형적괄용성。결과표명：①토양적유궤질함량수착지표지물류형화주변배경적불동이존재명현차이；②무론유궤질함량존재다대적차이，열홍외광보발사솔수파장적증가이변화적추세불변；단토양열홍외광보적발사솔재8～11．5μm범위내최민감，유궤질함량적대소회대기민감성산생영향；③일계도수、이계도수적발사솔여유궤질적상관성명현우우원시발사솔수거，발사솔수거적도수처리능구유효적증강여유궤질지간적상관성，차재해연구구발사솔수거적이계도수여유궤질함량상관성최고；④일계도수화이계도수적열홍외광보발사솔여유궤질함량지간적의합함수효과균교위량호，우기이계도수발사솔적지수함수효과최가；일계도수적다원축보회귀의합모형예측능력략우우선성함수모형。
In this paper ,Fourier thermal infrared spectrograph was used to detect the soil spectroscopic data and organic content in arid region .Analyzing the characteristics of the original spectral emissivity ,we obtained the first and second derivative of the original emissivity ,built the models between organic matter and the original emissivity ,the first derivative ,second derivative respectively .The applicability of the models were examined and evaluated .The results showed that :① the soil organic content differed apparently , because of the different surface feature types and surroundings .② The change trend of thermal infrared spectral emissivity with the increase of the wavelength stayed the same .Soil thermal infrared spectral emissivity within 8~11 .5 um was most sensitive to the organic content .③ The emissivity of the first and second derivative was superior to the original emissivity apparently .Differentiating of emissivity can effectively enhance the correlation with organic matter and the second derivative of emissivity had the highest correlation with organic matter in the study area .④ The fitting functions of organic content with the first and second derivative of the thermal infrared spectral emissivity fitted well ,especially the second derivative .The multivariate stepwise regression fitting model of the first derivative had slightly stronger predictive ability than linear function model .