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土壤发射率光谱与土壤元素含量的关系研究
董雪1; 田静1; 张仁华1; 贺冬仙2; 陈庆美1
2017
Source Publication光谱学与光谱分析
ISSN1000-0593
Volume37Issue:2Pages:557
AbstractIn this paper, based on the measurements of soil elements content and infrared spectra of 26 soil samples collected in more than 10 places, the relationship between soil emissivity in mid-infrared bands and the content of 11 soil elements including organic matters such as NO3-N, P, K, Ca, Mg, Cu, Fe, Mn, Zn and pH are analyzed. The bands where the soil elements content are significantly correlated with emissivity are given. And soil elements content estimation method is established based on the soil emissivity spectra with the partial least squares regression model and multiple stepwise regression model. The results show that: (1) In 8 similar to 10 mu m, the correlation coefficient (R-2) between Ca and soil emissivity is the highest, followed by Mg, Mn and Fe, with the highest correlation coefficient of 0. 85 and the lowest, 0. 52. In the range of 6 similar to 8 mu m, the correlations between the contents of K, Fe, NO3-N, Zn and emissivity decrease gradually, with the highest correlation coefficient of 0. 75 and the lowest 0. 48. In 10 similar to 14 mu m, the correlation between soil elements contents and emissivity is the highest for Mn, followed successively by P and K. (2) The scatter plot of soil emissivity and pH value has a parabola relation basically. The emissivity is the highest when pH value is 7, while the emissivity decreases gradually with the gradual decrease of pH value. (3) The accuracy of the estimated soil elements content from the partial least squares regression method is higher than that from the multiple stepwise regression method. It is noted that R-2 between the measurements and the estimates for the elements of Cu, Fe and Ca from the partial least squares regression method are very high (larger than 0. 9). Additionally, using the simulated emissivity spectrum in the ASTER thermal infrared bands, modeling R-2 and validation R2 between the measurements and the estimates for the elements of Ca from the multiple stepwise regression method are high (0. 774 and 0. 892, respectively). Using the simulated emissivity spectrum in the MODIS infrared bands, modeling R-2 and validation R-2 for Ca and Fe are higher than 0. 85, and modeling R-2 and validation R-2 for Mg, K are higher than 0. 5. As a whole, the emissivity spectrum in ASTER band 10 and band 11 and MODIS bands 28, 29, 30 are more sensitive to soil elements content, and thus they are more suitable for the estimation of soil elements content.
Language英语
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/120594
Collection中国科学院地理科学与资源研究所
Affiliation1.中国科学院地理科学与资源研究所
2.中国农业大学
First Author Affilication中国科学院地理科学与资源研究所
Recommended Citation
GB/T 7714
董雪,田静,张仁华,等. 土壤发射率光谱与土壤元素含量的关系研究[J]. 光谱学与光谱分析,2017,37(2):557.
APA 董雪,田静,张仁华,贺冬仙,&陈庆美.(2017).土壤发射率光谱与土壤元素含量的关系研究.光谱学与光谱分析,37(2),557.
MLA 董雪,et al."土壤发射率光谱与土壤元素含量的关系研究".光谱学与光谱分析 37.2(2017):557.
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