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Proceedings Paper

Automatic identification of end-members for the spectral decomposition of remotely sensed scenes
Author(s): Fabio Maselli; Maurizio Pieri; Claudio Conese
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Paper Abstract

Several methods have been proposed for the extraction of latent information from multispectral remotely sensed scenes based on the definition of indices and rotational transformations. A common drawback of these techniques is that they are ultimately based only on statistical relationships among pixel values rather than on physical characteristics of the scenes. Linear pixel unmixing is an alternative method which assumes that the pixel signal is the linear combination of some basic spectral components the fractions of which can be retrieved with good approximation. The method is straightforward and produces results which can be easily interpreted, but presents the problem of the identification of suitable end-members, which generally requires some external knowledge. In order to overcome this problem, in the present research a statistical method is developed for the automatic identification of end-members. This methodology is composed by several steps, that are describe and then applied to a case study with a Landsat 5 TM scene from Central Ethiopia (Africa). The results, evaluated in comparison with those of a more usual principal component transformation, indicate the good performance of the new procedure.

Paper Details

Date Published: 31 December 1996
PDF: 6 pages
Proc. SPIE 2960, Remote Sensing for Geography, Geology, Land Planning, and Cultural Heritage, (31 December 1996); doi: 10.1117/12.262456
Show Author Affiliations
Fabio Maselli, IATA/CNR (Italy)
Maurizio Pieri, Univ. degli Studi di Firenze (Italy)
Claudio Conese, IATA/CNR (Italy)

Published in SPIE Proceedings Vol. 2960:
Remote Sensing for Geography, Geology, Land Planning, and Cultural Heritage
Daniel Arroyo-Bishop; Roberto Carla; Joan B. Lurie; Carlo M. Marino; A. Panunzi; James J. Pearson; Eugenio Zilioli, Editor(s)

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