DocumentCode :
576646
Title :
Mining frequent substructures from deforestation objects
Author :
Maciel, Adeline M. ; Silva, Marcelino P S ; Escada, Maria Isabel S
Author_Institution :
Master´´s Program in Comput. Sci., Rio Grande do Norte State Univ., Mossoro, Brazil
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6745
Lastpage :
6748
Abstract :
The fight against deforestation is a priority for the environmental organizations, society and government. It demands the creation of methodologies and techniques that allow monitoring and intervening, efficiently and at reasonable costs, in areas susceptible to deforestation. Thus, the computational modeling of remote sensing data involves many challenges, including a large set of algorithms and techniques to extract strategic information contained in these data. This paper aims to employ graphs to represent relationships among deforestation objects captured from remote sensing data, and then extract patterns from them applying graph mining, that performs the search for frequent substructures using the FSG graph-based knowledge discovery algorithm, in order to identify frequent substructures among deforestation objects.
Keywords :
geophysical techniques; remote sensing; vegetation; FSG graph-based knowledge discovery algorithm; deforestation objects; environmental organizations; graph mining; mining frequent substructures; remote sensing data; Data mining; Databases; Educational institutions; Image segmentation; Remote sensing; Software; Data Mining; Deforestation Patterns; Frequent Substructures; Graph Mining; Remote Sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352557
Filename :
6352557
Link To Document :
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