Evaluation of intensive urban land use based on an artificial neural network model: A case study of Nanjing City, China
文献类型：期刊论文
| 作者 | Qiao Weifeng1,2,3; Gao Junbo2,4; Liu Yansui2; Qin Yueheng3; Lu Cheng3; Ji Qingqing3 |
| 刊名 | CHINESE GEOGRAPHICAL SCIENCE
 |
| 出版日期 | 2017-10-01 |
| 卷号 | 27期号:5页码:735-746 |
| 关键词 | urban land intensive use functional area artificial neural network (ANN) model Nanjing City |
| ISSN号 | 1002-0063 |
| DOI | 10.1007/s11769-017-0905-7 |
| 通讯作者 | Liu Yansui(liuys@igsnrr.ac.cn) |
| 英文摘要 | In this paper, the artificial neural network (ANN) model was used to evaluate the degree of intensive urban land use in Nanjing City, China. The construction and application of the ANN model took into account the comprehensive, spatial and complex nature of urban land use. Through a preliminary calculation of the degree of intensive land use of the sample area, representative sample area selection and using the back propagation neural network model to train, the intensive land use level of each evaluation unit is finally determined in the study area. Results show that the method can effectively correct the errors caused by the limitations of the model itself and the determination of the ideal value and weights when the multifactor comprehensive evaluation is used alone. The ANN model can make the evaluation results more objective and practical. The evaluation results show a tendency of decreasing land use intensity from the core urban area to the periphery and the industrial functional area has relatively low land use intensity compared with other functional areas. Based on the evaluation results, some suggestions are put forward, such as transforming the mode of urban spatial expansion, strengthening the integration and potential exploitation of the land in the urban built-up area, and strengthening the control of the construction intensity of protected areas. |
| WOS关键词 | CELLULAR-AUTOMATA ; PREDICTION |
| 资助项目 | China Postdoctoral Science Foundation[2015T80127] ; China Postdoctoral Science Foundation[2014M561040] ; National Natural Science Foundation of China[41371172] ; National Natural Science Foundation of China[41401171] ; National Natural Science Foundation of China[41471143] ; Priority Academic Program Development of Jiangsu Higher Education Institutions[164320H101] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000410024000006 |
| 出版者 | SPRINGER |
| 资助机构 | China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; Priority Academic Program Development of Jiangsu Higher Education Institutions |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/61972]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu Yansui |
| 作者单位 | 1.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Nanjing Normal Univ, Sch Geog Sci, Nanjing 210023, Jiangsu, Peoples R China 4.Xinyang Normal Univ, Sch Geog Sci, Xinyang 464000, Henan, Peoples R China |
| 推荐引用方式 GB/T 7714 | Qiao Weifeng,Gao Junbo,Liu Yansui,et al. Evaluation of intensive urban land use based on an artificial neural network model: A case study of Nanjing City, China[J]. CHINESE GEOGRAPHICAL SCIENCE,2017,27(5):735-746. |
| APA | Qiao Weifeng,Gao Junbo,Liu Yansui,Qin Yueheng,Lu Cheng,&Ji Qingqing.(2017).Evaluation of intensive urban land use based on an artificial neural network model: A case study of Nanjing City, China.CHINESE GEOGRAPHICAL SCIENCE,27(5),735-746. |
| MLA | Qiao Weifeng,et al."Evaluation of intensive urban land use based on an artificial neural network model: A case study of Nanjing City, China".CHINESE GEOGRAPHICAL SCIENCE 27.5(2017):735-746. |
入库方式： OAI收割
来源：地理科学与资源研究所
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