@inproceedings{a72b456d620d40d4a53cf02073fb3b68,
title = "VHR Satellite Image Time Series analysis using expert knowledge modeling and user assistance",
abstract = "In this paper, we address land cover regions monitoring issue by introducing prior knowledge about the studied scene. Actually, remote sensing data growing volumes lead to increase the complexity of direct images interpretation. So, we attempt to overcome this problem by formalizing expert knowledge. The proposed method extends an expert knowledge formalism and temporal evolution graph representation to handle sub-graphs similarity. For this purpose, a user interaction through the proposition of a time window and concepts evolution is introduced. Hence, the proposed approach extracts the most similar temporal evolution to user request over the generated SITS subgraphs. Experiments are performed on synthesized and real STIS and compared to previously presented approaches for STIS analysis.",
keywords = "Spatio-temporal analysis, VHR-SITS, knowledge modeling, semantic, sub-graph, user assistance",
author = "S. Rejichi and F. Chaabane and F. Tupin",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7730348",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5173--5176",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
}