DocumentCode :
802009
Title :
On the effect of variable endmember spectra in the linear mixture model
Author :
Settle, Jeff
Author_Institution :
Environ. Syst. Sci. Centre, Univ. of Reading, UK
Volume :
44
Issue :
2
fYear :
2006
Firstpage :
389
Lastpage :
396
Abstract :
The linear mixture model is frequently used to characterize surface cover over land, to model the reflectance of heterogeneous surfaces, and, by inversion, to estimate fractional cover from a multispectral satellite signal. It is usually assumed that certain parameters of this model, namely the so-called endmember spectra, are fixed, and that the model residual - the difference between a signal and its expected value in terms of the linear model - is systematically independent of all other parameters. In a small number of studies the endmember spectra have been allowed to have random fluctuations, giving rise to a covariance matrix for the residual that depends on the underlying proportions, and two distinct models exist for this mixed-pixel covariance matrix. In this note the linear model for mixed pixels is examined with varying endmember spectra, and it is shown that under a simple set of models for the variability of both endmembers and abundance, the covariance matrix for the residual is a weighted sum of the two previously considered cases. Generally, the balance between the two limiting cases is determined by the length scale for changes in the reflectance of any given cover type, and the length scale for changes in surface cover itself; one or other of the two limit models is preferred when these lengths are very different.
Keywords :
geophysical signal processing; inverse problems; optical transfer function; reflectivity; spectral analysis; terrain mapping; vegetation mapping; heterogeneous surface reflectance; inverse problems; land surface cover characterization; linear mixture model; mixed-pixel covariance matrix; multispectral satellite signal; point spread function; random fluctuation; spatial response function; variable endmember spectra; Covariance matrix; Fluctuations; Image resolution; Image retrieval; Land surface; Pattern matching; Pixel; Reflectivity; Satellites; Spatial resolution; Linear mixture models; mixed pixels; point spread function; spatial response function; unmixing; variable endmembers;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2005.860983
Filename :
1580724
Link To Document :
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