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Study on the Relationship between Soil Emissivity Spectra and Content of Soil Elements
Dong Xue1,2; Tian Jing1; Zhang Ren-hua1; He Dong-xian3; Chen Qing-mei1
2017-02-01
Source PublicationSPECTROSCOPY AND SPECTRAL ANALYSIS
ISSN1000-0593
Volume37Issue:2Pages:557-565
Corresponding AuthorTian Jing(tianj.04b@igsnrr.ac.cn)
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.
KeywordSoil emissivity Mid-infrared spectra Soil elements Partial least squares regression Multiple stepwise regression ASTER MODIS
DOI10.3964/j.issn.1000-0593(2017)02-0557-09
WOS KeywordDIFFUSE-REFLECTANCE SPECTROSCOPY
Indexed BySCI
Language英语
WOS Research AreaSpectroscopy
WOS SubjectSpectroscopy
WOS IDWOS:000393847200043
PublisherOFFICE SPECTROSCOPY & SPECTRAL ANALYSIS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64908
Collection中国科学院地理科学与资源研究所
Corresponding AuthorTian Jing
Affiliation1.Chinese Acad Sci, IGSNRR, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.China Agr Univ, Minist Agr, Key Lab Agr Engn Struct & Environm, Beijing 100083, Peoples R China
Recommended Citation
GB/T 7714
Dong Xue,Tian Jing,Zhang Ren-hua,et al. Study on the Relationship between Soil Emissivity Spectra and Content of Soil Elements[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2017,37(2):557-565.
APA Dong Xue,Tian Jing,Zhang Ren-hua,He Dong-xian,&Chen Qing-mei.(2017).Study on the Relationship between Soil Emissivity Spectra and Content of Soil Elements.SPECTROSCOPY AND SPECTRAL ANALYSIS,37(2),557-565.
MLA Dong Xue,et al."Study on the Relationship between Soil Emissivity Spectra and Content of Soil Elements".SPECTROSCOPY AND SPECTRAL ANALYSIS 37.2(2017):557-565.
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