Fifth Symposium on Novel Optoelectronic Detection Technology and Application 2019
DOI: 10.1117/12.2521743
|View full text |Cite
|
Sign up to set email alerts
|

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

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 vege… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 21 publications
0
2
0
Order By: Relevance
“…Spectral calculation relies on the assumption that the reflectances for soil and vegetation are correlated across the 240-4000 nm range and that a few spectral measurements in the visible and near-infrared provide sufficient information on the reflectance in the UV (below 400 nm) and shortwave infrared (from 2500 nm to 4000 nm) [1,[38][39][40]. That assumption is further supported by statistical analysis (results not presented here) of tens of spectra available from several databases, containing measured spectral reflectances from soil and vegetation samples (presented in Section 3.4.1).…”
Section: Spectral Modelingmentioning
confidence: 99%
“…Spectral calculation relies on the assumption that the reflectances for soil and vegetation are correlated across the 240-4000 nm range and that a few spectral measurements in the visible and near-infrared provide sufficient information on the reflectance in the UV (below 400 nm) and shortwave infrared (from 2500 nm to 4000 nm) [1,[38][39][40]. That assumption is further supported by statistical analysis (results not presented here) of tens of spectra available from several databases, containing measured spectral reflectances from soil and vegetation samples (presented in Section 3.4.1).…”
Section: Spectral Modelingmentioning
confidence: 99%
“…where 1,2 ( , ) represent the polarized component of the Fresnel reflection matrix, is the reflective index of the vegetative matter, means the half the phase angle, NDVI is the normalized difference vegetation index, and is the only free linear parameter (Maignan et al, 2009). In this paper, he parameters of the BRDF and BPDF of vegetated surface are chosen from the work of Litvinov et al (2011), which will not be discussed here anymore (Hou et al, 2019). 1 410 nm 2 410, 443 nm 3 410, 443, 490 nm 4 410, 443, 490, 555 nm 5 410, 443, 490, 555, 670 nm 6 410, 443, 490, 555, 670, 865 nm Table 1.…”
Section: Forward Simulations and Parameter Settingsmentioning
confidence: 99%