Name
Abstract | ||
|---|---|---|
Land-use/cover change, climate change, sea level evolution are examples of application that are associated with change detection. Actually, we use satellite image time series to monitor the change where entities are often dynamic along time. Moreover, knowledge associated to these spatio-temporal objects can evolve when changes occur. Thus, for modeling this kind of knowledge it is necessary to deal with four aspects: spectral, spatial, temporal and semantic. Such approach can be modeled by ontologies in many levels. Thereby, a shared ontology can be an ontology or a combination of some ontologies based on some mechanisms of linking. Such link process should maintain consistency between represented knowledge. In this paper, we propose a multi-level ontological approach for monitoring dynamics in remote sensing images. The proposed methodology aims to link our domain ontology to an upper level ontology thus enabling to represent existing change processes. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.5220/0005642204350440 | KEOD |
Field | DocType | Citations |
Ontology (information science),Data mining,Ontology-based data integration,Ontology,Climate change,Change detection,Process ontology,Computer science,Satellite Image Time Series,Upper ontology | Conference | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fethi Ghazouani | 1 | 0 | 1.35 |
| Wassim Messaoudi | 2 | 0 | 0.34 |
| Imed Riadh Farah | 3 | 86 | 26.16 |