Abstract
This paper proposes a method to solve the selection problem in GIS generalization by leveraging the rough sets theory for attribute reduction. In specific, by taking into account the special characteristics of the GIS spatial data, our method can be outlined as follows. First, we discretize the continuous-valued attributes through unsupervised discretization method; Second, we classify in a fuzzy manner the spatial objects, whose result will then serve as the decisional attributes; Third, we evaluate the respective importance of these attributes through the attribute reduction method borrowed from the rough sets theory and consequently we conduct a dynamic sorting according to the resulting importance values. Through experimentation results, the effectiveness performance of our proposed method is validated.
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© 2011 Springer-Verlag Berlin Heidelberg
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Li, W., Qiu, J., Wu, Z., Lin, Z., Li, S. (2011). Application of Rough Sets in GIS Generalization. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds) Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(), vol 6954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24425-4_45
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DOI: https://doi.org/10.1007/978-3-642-24425-4_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24424-7
Online ISBN: 978-3-642-24425-4
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