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Proceedings Paper

Calibration, regression models, and the Web
Author(s): Jan Smid; Brian L. Markham; Petr Svacek; Petr Volf
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Paper Abstract

The purpose of this paper is to provide a multifacetted approach to interactive analysis and modeling of time series, signals, and dynamical data sets. The models use statistical regression analysis and are built in an incremental way from a set of simple functional units. The analysis is supported by data visualization and on-line adaptive tutorials accessed on the World Wide Web. This work extends our results obtained for the Landsat-5 and Landsat-7 calibration data. The another objective is to educate the user about available mathematical models and also to allow the user to build those models interactively through applets prepared by the authors on a Web server. These models may be constructed for the user's own data set. The approach is illustrated using the calibration data sets for the Landsat sensors, we also discuss agent communication framework of regression models and calibration data. However, the same integrated approach can be used for other data domains. This type of approach is consistent with other recent activities regarding semantic web.

Paper Details

Date Published: 13 March 2003
PDF: 8 pages
Proc. SPIE 4885, Image and Signal Processing for Remote Sensing VIII, (13 March 2003); doi: 10.1117/12.463079
Show Author Affiliations
Jan Smid, Morgan State Univ. (United States)
Brian L. Markham, NASA Goddard Space Flight Ctr. (United States)
Petr Svacek, Czech Technical Univ. (Czech Republic)
Petr Volf, The Academy of Sciences of the Czech Republic (Czech Republic)


Published in SPIE Proceedings Vol. 4885:
Image and Signal Processing for Remote Sensing VIII
Sebastiano B. Serpico, Editor(s)

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