Title :
The Physics of spectral invariants
Author_Institution :
University of Helsinki, Department of Geosciences and Geography
Abstract :
To make full use of the increased possibilities of imaging spectroscopy (compared with the traditional multispectral instruments) for remote sensing of vegetation canopies, physically-based models should be used. The problem of retrieving the large number of model parameters from remotely sensed reflectance data is an ill-posed and under-determined one. The physically-based spectral invariants approach may, in some cases, seem a lucrative alternative. However, the various formulations presented in literature are sometimes difficult to compare qualitatively or quantitatively. To develop a robust spectral-invariant based algorithm for vegetation remote sensing, empirical, mathematical and physical understanding of the problem has to be reached. We present connections between the photon recollision probability and the largest eigenvalue of the radiative transfer equation. Based on simple mathematical principles, the basic requirements set by the remote sensing process to a successful spectral invariant theory are presented.
Keywords :
atmospheric boundary layer; eigenvalues and eigenfunctions; geophysical techniques; radiative transfer; vegetation mapping; canopy reflectance model; eigenvalue; imaging spectroscopy; model parameters; multispectral instruments; photon recollision probability; radiative transfer equation; reflectance data; spectral invariant theory; vegetation canopies; vegetation remote sensing; Biological system modeling; Eigenvalues and eigenfunctions; Mathematical model; Photonics; Remote sensing; Scattering; Vegetation; canopy reflectance model; photon recollision probability; spectral invariants;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on
Conference_Location :
Reykjavik
Print_ISBN :
978-1-4244-8906-0
Electronic_ISBN :
978-1-4244-8907-7
DOI :
10.1109/WHISPERS.2010.5594910