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Proceedings Paper

Virtual environment for remote sensing data exploration
Author(s): Walter Di Carlo
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Paper Abstract

Remotely sensed images, data extracted by analytical models and other ancillary data are the main sources of information both in spatial and multi-dimensional space for Earth observation applications. In general, the visualization process, by means of graphic aids, may facilitate the understanding of these complex data sets. However, in many cases, a single visualization technique is not sufficient to extract all data properties or cannot be used to explore different types of data. In this context, a graphical tool, based on a virtual reality system, has been developed to assess the usefulness of visualization techniques for the exploration of remotely sensed data. Several different 3- dimensional representations of the same data, linked visually by a 'data brushing' technique, have been developed in order to understand in a more effective way the structures inherently present in the data. The objective of this study is to get more insight about the techniques employed in remote sensing image processing to extract sub-pixel information, such as those based on fuzzy classifiers and linear spectral unmixing, in order to improve image classification.

Paper Details

Date Published: 25 March 1999
PDF: 10 pages
Proc. SPIE 3643, Visual Data Exploration and Analysis VI, (25 March 1999); doi: 10.1117/12.342822
Show Author Affiliations
Walter Di Carlo, Joint Research Ctr. of Ispra (Italy)

Published in SPIE Proceedings Vol. 3643:
Visual Data Exploration and Analysis VI
Robert F. Erbacher; Philip C. Chen; Craig M. Wittenbrink, Editor(s)

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