Abstract
This paper demonstrates how knowledge driven methods and the associated data analysis algorithms are changing the paradigms of user-data interactions, providing an easier and wider access to the Earth Observation data. Some information theory based algorithms are proposed for anomaly and change detection on SPOT images, relative to a widespread humanitarian crisis scenario: floods. The outcomes of these algorithms define an informational representation of the image, revealing the spatial distribution of a particular theme. Using image analysis and interpretation, the multitude of features from a scene are classified into meaningful classes to create sematic maps.
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References
Datcu, M., Daschiel, H., Pelizzari, A., Quartulli, M., Galoppo, A., Colapocchioni, A., Pastori, M., Seidel, K., Marchetti, P.G., D’Elia, S.: Information Mining in Remote Sensing Image Archive - Part A: System concepts. IEEE Transaction on Geoscience and Remote sensing 41, 2923–2936 (2003)
Ming, L., Chen, X., Bin, M., Vitányi, P.M.B.: The similarity metric. IEEE Transaction on Information Theory 50, 3250–3264 (2004)
Faur, D., Gavat, I., Datcu, M.: Mutual information based measures for image content characterization. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds.) CAEPIA 2005. LNCS (LNAI), vol. 4177, pp. 342–349. Springer, Heidelberg (2006)
Schröder, M., Rehrauer, H., Seidel, K., Datcu, M.: Interactive learning and probabilistic image retrieval in remote sensing image archives, vol. 38, pp. 2288–2298 (2000)
Faur, D., Gavat, I., Datcu, M.: Use of knowledge driven information mining for Earth Observation images assessment to support sustainable humanitarian crisis management. In: Workshop Proceedings of ESA-EUSC 2006: Image Information Mining for Security and Intelligence (2006)
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© 2008 Springer-Verlag Berlin Heidelberg
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Vaduva, C., Faur, D., Popescu, A., Gavat, I., Datcu, M. (2008). Semantic Map Generation from Satellite Images for Humanitarian Scenarios Applications. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_73
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DOI: https://doi.org/10.1007/978-3-540-88458-3_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88457-6
Online ISBN: 978-3-540-88458-3
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