DocumentCode :
143314
Title :
Knowledge-based approach for VHR satellite image time series analysis
Author :
Rejichi, S. ; Chaabane, F.
Author_Institution :
COSIM Lab., Carthage Univ., Tunis, Tunisia
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
2177
Lastpage :
2180
Abstract :
As satellite data volumes are growing thanks to technological evolution, there are more needs to automatic approaches for Satellite Image Time Series (SITS) analysis. In this article, we propose a new approach based on experts knowledge for land cover monitoring. This approach helps geoscientists to overcome direct interpretation difficulties by modeling expert knowledge. As a first step, using predefined nomenclature and a prior information, concepts are set. Then, each SITS region temporal evolution, represented by a graph, is assigned to the most similar reference one in the knowledge database using the marginalized graph kernel similarity measure.
Keywords :
geophysical image processing; land cover; time series; SITS analysis automatic approach; SITS region temporal evolution; VHR satellite image time series analysis; direct interpretation difficulty; knowledge database; knowledge-based approach; land cover monitoring; marginalized graph kernel similarity measure; modeling expert knowledge; predefined nomenclature; satellite data volume; satellite image time series analysis; technological evolution; Image segmentation; Kernel; Knowledge based systems; Monitoring; Satellites; Semantics; Time series analysis; Spatio-temporal analysis; Very High Resolution Satellite Image Time Series VHR-SITS; graph kernel; knowledge modeling; semantic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6946899
Filename :
6946899
Link To Document :
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