Comparison between CBR and CA methods for estimating land use change in Dongguan, China | |
Du Y. Y. ; Ge Y. ; Lakhan V. C. ; Sun Y. R. ; Cao Feng(曹峰) | |
刊名 | Journal of Geographical Sciences
![]() |
2012 | |
卷号 | 22期号:4页码:716-736 |
关键词 | artificial intelligence Dongguan coastal region case-based reasoning China land use changes spatial relationship cellular automata cellular-automaton model urban-development san-francisco gis integration dynamics simulation patterns form area |
ISSN号 | 1009-637X |
通讯作者 | Du, YY |
英文摘要 | Many studies on land use change (LUC), using different approaches and models, have yielded good results. Applications of these methods have revealed both advantages and limitations. However, LUC is a complex problem due to influences of many factors, and variations in policy and natural conditions. Hence, the characteristics and regional suitability of different methods require further research, and comparison of typical approaches is required. Since the late 1980s, CA has been used to simulate urban growth, urban sprawl and land use evolution successfully. Nowadays it is very popular in resolving the LUC estimating problem. Case-based reasoning (CBR), as an artificial intelligence technology, has also been employed to study LUC by some researchers since the 2000s. More and more researchers used the CBR method in the study of LUC. The CA approach is a mathematical system constructed from many typical simple components, which together are capable of simulating complex behavior, while CBR is a problem-oriented analysis method to solve geographic problems, particularly when the driving mechanisms of geographic processes are not yet understood fully. These two methods were completely different in the LUC research. Thus, in this paper, based on the enhanced CBR model, which is proposed in our previous research (Du et al. 2009), a comparison between the CBR and CA approaches to assessing LUC is presented. LUC in Dongguan coastal region, China is investigated. Applications of the improved CBR and the cellular automata (CA) to the study area, produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR, and 70.7% accuracy from the CA. From the results, we can see 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. |
收录类别 | SCI |
资助信息 | National 863 High Technology Programs of China 2011BAH23B04;The State Key Laboratory of Resource and Environment Information System 088RA500KA;National Natural Science Foundation of China 41071250 |
公开日期 | 2012-09-04 |
内容类型 | 期刊论文 |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/26647] ![]() |
专题 | 地理科学与资源研究所_研究生部 |
推荐引用方式 GB/T 7714 | Du Y. Y.,Ge Y.,Lakhan V. C.,et al. Comparison between CBR and CA methods for estimating land use change in Dongguan, China[J]. Journal of Geographical Sciences,2012,22(4):716-736. |
APA | Du Y. Y.,Ge Y.,Lakhan V. C.,Sun Y. R.,&Cao Feng.(2012).Comparison between CBR and CA methods for estimating land use change in Dongguan, China.Journal of Geographical Sciences,22(4),716-736. |
MLA | Du Y. Y.,et al."Comparison between CBR and CA methods for estimating land use change in Dongguan, China".Journal of Geographical Sciences 22.4(2012):716-736. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论