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GSV-L: A general spectral vector model for hyperspectral leaf spectra simulation

文献类型：期刊论文

作者Ma, Tian; Fang, Hongliang
刊名INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
出版日期2023-03-01
卷号117页码:103216
ISSN号1569-8432
关键词Leaf reflectance and transmittance spectra General spectral vector-leaf (GSV-L) model Spectral vectors PROSPECT LEAF-SIP Canopy radiative transfer model
DOI10.1016/j.jag.2023.103216
文献子类Article
英文摘要Leaf optical spectra determine vegetation canopy optical spectra. Physically based leaf models are relatively complicated as they require many biophysical and biochemical parameters that are usually difficult to obtain. The aim of this study is to develop a new empirical model, the general spectral vector-leaf (GSV-L) model using globally collected leaf spectra data. A global field-measured leaf spectra database, including 66,478 leaf reflectance and 3575 transmittance spectra in the wavelength range of 400-2400 nm, was first constructed. The singular value decomposition (SVD) method was applied to the field data matrix to derive the spectral vectors for leaf spectral modeling. The SVD method was also compared with the successive approximation (SA) and prin-cipal component analysis (PCA) methods using the same training and validation datasets, and the GSV-L model was compared with two other physical models, PROSPECT and LEAF-SIP. The GSV-L model can be used to simulate full leaf reflectance and transmittance spectra using a few wavelengths in different bands with very high R2 (0.99, 0.99), small RMSE (0.014, 0.014) and bias (0, 0.002) values. The model also performs better than the PROSPECT and LEAF-SIP models for leaf spectral simulation. The coefficients of the reflectance spectral vectors can be used to estimate leaf structure parameters, equivalent water thickness, and leaf biochemical contents. As an efficient and accurate approach for leaf hyperspectral modeling, GSV-L can also be integrated with various canopy reflectance and land surface models.
WOS关键词RETRIEVAL
WOS研究方向Remote Sensing
出版者ELSEVIER
WOS记录号WOS:000966223800001
源URL[http://ir.igsnrr.ac.cn/handle/311030/190534]  
专题资源与环境信息系统国家重点实验室_外文论文
作者单位Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, LREIS, Beijing 100101, Peoples R China; Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Ma, Tian,Fang, Hongliang. GSV-L: A general spectral vector model for hyperspectral leaf spectra simulation[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2023,117:103216.
APA Ma, Tian,&Fang, Hongliang.(2023).GSV-L: A general spectral vector model for hyperspectral leaf spectra simulation.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,117,103216.
MLA Ma, Tian,et al."GSV-L: A general spectral vector model for hyperspectral leaf spectra simulation".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 117(2023):103216.

入库方式： OAI收割

来源：地理科学与资源研究所

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