文献类型：期刊文献

英文题名：Comparison of multivariate methods for estimating soil total nitrogen with visible/near-infrared spectroscopy

作者：Shi, Tiezhu[1,2] Cui, Lijuan[3] Wang, Junjie[1,2] Fei, Teng[1,2] Chen, Yiyun[1,2] Wu, Guofeng[1,2]

第一作者：Shi, Tiezhu

通信作者：Wu, GF[1]

机构：[1]Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China;[2]Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan 430079, Peoples R China;[3]Chinese Acad Forestry, Inst Wetland Res, Beijing 100091, Peoples R China

年份：2013

卷号：366

期号：1-2

起止页码：363-375

外文期刊名：PLANT AND SOIL

收录：;Scopus(收录号：2-s2.0-84876445486);WOS:【SCI-EXPANDED(收录号:WOS:000317988600026)】；

基金：This study was supported by the Special Foundation of the Ministry of Finance of China for Nonprofit Research of Forestry Industry (Grant No. 200904001) and the National Natural Science Foundation of China (Grant No. 41171290).

语种：英文

外文关键词：Organic matter; Spectral pre-processing; Stepwise multiple linear regression; Partial least squares regression; Support vector machine; Heterogeneous soils

摘要：This study aimed to compare stepwise multiple linear regression (SMLR), partial least squares regression (PLSR) and support vector machine regression (SVMR) for estimating soil total nitrogen (TN) contents with laboratory visible/near-infrared reflectance (Vis/NIR) of selected coarse and heterogeneous soils. Moreover, the effects of the first (1st) vs. second (2nd) derivative of spectral reflectance and the importance wavelengths were explored. The TN contents and the Vis/NIR were measured in the laboratory. Several methods were employed for Vis/NIR data pre-processing. The SMLR, PLSR and SVMR models were calibrated and validated using independent datasets. Results showed that the SVMR and the PLSR models had similar performances, and better performances than the SMLR. The spectral bands near 1450, 1850, 2250, 2330 and 2430 nm in the PLSR model were important wavelengths. In addition, the 1st derivative was more appropriate than the 2nd derivative for spectral data pre-processing. PLSR was the most suitable method for estimating TN contents in this study. SVMR may be a promising technique, and its potential needs to be further explored. Moreover, the future studies using outdoor and airborne/satellite hyperspectral data for estimating TN content are necessary for testing the findings.