Polynomial expression for analysis of hyperspectral remote sensing data

Author

Liu, Qiang ; Liu, Qinhuo ; Menenti, Massimo

Author_Institution

Lab. of Remote Sensing Inf. Sci., Chinese Acad. of Sci., Beijing, China

Volume

6

fYear

2003

fDate

21-25 July 2003

Firstpage

3763

Abstract

Presents a new method to analyze the relation between canopy spectral reflectance and component spectral properties. The polynomial decomposition method differs from linear spectral unmixing because it takes into consideration the multiple scattering inside canopy. It is consistent with physical BRDF models and more flexible because it does not depend on certain assumption on canopy structure. This method is superior for some kinds of canopy whose structure is ambiguous between homogeneous and discrete. The output of the analysis is "angular-structural coefficients" which is possible to be related directly to canopy biophysical parameters.

Keywords

data analysis; polynomials; vegetation mapping; BRDF models; angular-structural coefficients; bidirectional reflectance distribution function; canopy biophysical parameters; canopy spectral reflectance; canopy structure; component spectral properties; hyperspectral remote sensing data analysis; linear spectral unmixing; multiple scattering; polynomial decomposition method; polynomial expression; Hyperspectral imaging; Hyperspectral sensors; Information science; Laboratories; Optoelectronic and photonic sensors; Polynomials; Reflectivity; Remote sensing; Soil; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International

Print_ISBN

0-7803-7929-2

Type

conf

DOI

10.1109/IGARSS.2003.1295262

Filename

1295262