DocumentCode :
576459
Title :
First results of quantifying nonlinear mixing effects in heterogeneous forests: A modeling approach
Author :
Tits, L. ; Delabastita, W. ; Somers, B. ; Farifteh, J. ; Coppin, P.
Author_Institution :
Dept. of Biosyst., K.U. Leuven, Leuven, Belgium
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
7185
Lastpage :
7188
Abstract :
Mixed satellite signals are traditionally modeled as linear combinations of the spectral signatures of its constituent components. Although nonlinearity has been shown to be significant for a variety of vegetation types, it is assumed to be negligible for most applications. We aim to assess the validity of the linear modeling assumption by making a quantitative analysis of the nature of multiple scattering effects in mixed forests. The effects of the spectral properties of the different species, structural differences and differences in tree height are evaluated. Virtual forest scenes and simulated hyperspectral satellite data were created through ray-tracing modeling using the Physically Based Ray-Tracer (PBRT) model. Results showed that both structure and the spectral properties influenced the nonlinear mixing behaviour, indicating that nonlinear unmixing models might be needed for forest cover mapping in heterogeneous forests.
Keywords :
geophysical signal processing; ray tracing; vegetation; vegetation mapping; forest cover mapping; heterogeneous forests; hyperspectral satellite data; linear modeling assumption; mixed forests; mixed satellite signals; multiple scattering effects; nonlinear mixing behaviour; nonlinear mixing effects; nonlinear unmixing models; physically based ray-tracer model; quantitative analysis; ray-tracing modeling; spectral properties; spectral signatures; structural differences; tree height; vegetation types; virtual forest scenes; Atmospheric modeling; Biological system modeling; Data models; Ray tracing; Remote sensing; Scattering; Vegetation; forest; hyperspectral; multiple scattering; ray-tracing; spectral mixture analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352005
Filename :
6352005
Link To Document :
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