Study on the spectral reconstruction of typical surface types based on spectral library and principal component analysis

Weizhen Hou; Yilan Mao; Chi Xu; Zhengqiang Li; Donghui Li; Yan Ma; Hua Xu

doi:10.1117/12.2521743

12 March 2019 Study on the spectral reconstruction of typical surface types based on spectral library and principal component analysis

Weizhen Hou, Yilan Mao, Chi Xu, Zhengqiang Li, Donghui Li, Yan Ma, Hua Xu

Author Affiliations +

Proceedings Volume 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application; 110232T (2019) https://doi.org/10.1117/12.2521743
Event: Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 2018, Xi'an, China

Abstract

To meet the demanding of spectral reconstruction in the visible and near-infrared wavelength, the spectral reconstruction method for typical surface types is discussed based on the USGS/ASTER spectral library and principal component analysis (PCA). A new spectral reconstructed model is proposed by the information of several typical bands instead of all of the wavelength bands, and a linear combination spectral reconstruction model is also discussed. By selecting 4 typical spectral datasets including green vegetation, bare soil, rangeland and concrete in the spectral range of 400−900 nm, the PCA results show that 6 principal components could characterized the spectral dataset, and the relative reconstructed errors are smaller than 2%. If only 6−7 selected typical bands are employed to spectral reconstruction for all the surface reflectance in 400−900 nm, except that the reconstructed error of green vegetation is about 3.3%, the relative errors of other 3 datasets are all smaller than 1.6%. The correlation coefficients of those 4 datasets are all larger than 0.99, which can effectively satisfy the needs of spectral reconstruction. In addition, based on the spectral library and the linear combination model of 4 common used bands of satellite remote sensing such as 490, 555, 670 and 865 nm, the reconstructed errors are smaller than 8.5% in high reflectance region and smaller than 1.5% in low reflectance region respectively, which basically meet the needs of spectral reconstruction. This study can provide a reference value for the surface reflectance processing and spectral reconstruction in satellite remote sensing research.

Citation Download Citation

Weizhen Hou, Yilan Mao, Chi Xu, Zhengqiang Li, Donghui Li, Yan Ma, and Hua Xu "Study on the spectral reconstruction of typical surface types based on spectral library and principal component analysis", Proc. SPIE 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 110232T (12 March 2019); https://doi.org/10.1117/12.2521743

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