Discovery of Frequent Correlations among Deforestation Objects Using Graph Mining
نویسندگان
چکیده
Nowadays, there is a rich diversity and huge volume of data from satellite sensors. Due to their attractiveness and singular characteristics, they are increasingly gaining importance in the research context. Concomitantly, the volume of remote sensing data is quickly growing. Thus, the computational modeling of such data involves many challenges, including a large set of algorithms and techniques to extract strategic information contained in these data. This paper applies a computational mathematical formalism (graphs) to represent deforestation data, in order to perform intelligent search of patterns (graph mining) to discover frequent correlations among deforestation objects.
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تاریخ انتشار 2012