(Article of periodic en Anglais - 2012)

Document title

Comparison between CBR and CA methods for estimating land use change in Dongguan, China

Authors(s) and Affiliation(s)

DU Y. (1) ; GE Y. (1) ; LAKHAN V.C. (2) ; SUN Y. (1) ; CAO F. (1) ;
(1) State Key Lab. of Resources and Environmental Information Systems, Inst. of Geographic Sciences and Natural Resources Research, CAS, Beijing, CHINE
(2) Dep. of Earth and Environmental Sciences, Univ., Windsor, CANADA


Applications of the improved case-based reasoning (CBR), as an artificial technology and the cellular automata (CA) to the Dongguan coastal region, produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR, and 70.7% accuracy from the CA. From the results, it is showed that the accuracies of the CA and CBR approaches are both >70%. Although CA method has the distinct advantage in predicting the urban type, CBR method has the obvious tendency in predicting non-urban type. Considering the entire analytical process, the preprocessing workload in CBR is less than that of the CA approach. As such, it could be concluded that the CBR approach is more flexible and practically useful than the CA approach for estimating land use change


Article of periodic

published at : Journal of geographical sciences. Acta geographica sinica / ISSN 1009-637X

Editor : CHINE

Millesime : 2012, vol. 22, no4 [pp. 716-736]



Digital Object Identifier

Go to electronic document thanks to its DOI : doi:10.1007/s11442-012-0958-6

Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI), 2012
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