@article{(Open Science Index):https://publications.waset.org/pdf/14440,
	  title     = {Improving Spatiotemporal Change Detection: A High Level Fusion Approach for Discovering Uncertain Knowledge from Satellite Image Database},
	  author    = {Wadii Boulila and  Imed Riadh Farah and  Karim Saheb Ettabaa and  Basel Solaiman and  Henda Ben Ghezala},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {10},
	  year      = {2009},
	  pages     = {2341 - 2346},
	  ee        = {https://publications.waset.org/pdf/14440},
	  url   	= {https://publications.waset.org/vol/34},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 34, 2009},
	}