Towards a multi-approach system for uncertain spatio-temporal knowledge discovery in satellite imagery
Résumé
Exploiting images coming from different sensors is an important challenge in the remote sensing field. Integration of new knowledge is crucial to help the user interpret satellite images and track their spatio-temporal changes over time. Thus, we propose a new approach to process multi-date satellite images. Our approach combines knowledge discovery from satellite image databases, and fusion methods in order to find out new and relevant knowledge useful to create decision making and prevision models. The choice of the proposed architecture is motivated by two reasons. First, we need to process imperfection related to the knowledge discovery and interpretation processes. Second, we should integrate new, valid, potentially useful and ultimately understandable knowledge hidden in databases. Our work is based on three concepts (multi-agent systems, case based reasoning and rule based reasoning) and is validated through the use of two optical satellite images coming from Landsat 7 representing the region of Matmata (South of Tunisia)