Simulating Urban Sprawl in China Based on the Artificial Neural Network-Cellular Automata-Markov Model
文献类型：期刊论文
| 作者 | Zhang, Xueru2; Zhou, Jie1; Song, Wei3
|
| 刊名 | SUSTAINABILITY
 |
| 出版日期 | 2020-06-01 |
| 卷号 | 12期号:11页码:13 |
| 关键词 | land use change urban sprawl simulation ANN-CA-Markov model night light data China |
| DOI | 10.3390/su12114341 |
| 通讯作者 | Song, Wei(songw@igsnrr.ac.cn) |
| 英文摘要 | In recent years, China's urbanization rate has been increasing rapidly, reaching 59.58% in 2018. Urbanization drives rural-to-urban migration, and inevitably promotes urban sprawl. With the development of remote sensing and geographic information technologies, the monitoring technology for urban sprawl has been constantly innovated. In particular, the emergence of night light data has greatly promoted monitoring research of large-scale and long-time-series urban sprawl. In this paper, the urban sprawl in China in 1992, 1997, 2002, 2007, 2012, and 2017 was identified via night light data, and the Artificial Neural Network-Cellular Automata-Markov (ANN-CA-Markov) model was developed to simulate the future urban sprawl in China. The results show that the suitability of urban sprawl based on the ANN model is as high as 0.864, indicating that the ANN model is very suitable for the simulation of urban sprawl. The Kappa coefficient of simulation results was 0.78, indicating that the ANN-CA-Markov model has a high simulation accuracy on urban sprawl. In the future, the hotspot areas of urban sprawl in China will change over time. Although the urban sprawl in the Beijing-Tianjin-Hebei region, the Yangtze River delta, and the Pearl River delta will still be considerable, the urban sprawl in the Chengdu-Chongqing city cluster, the Guanzhong Plain city cluster, the central plains city cluster, and the middle reaches of the Yangtze River will be more prominent. Overall, China's urban sprawl will be concentrated in the east of Hu's line in the future. |
| WOS关键词 | FUTURE LAND-USE ; CA-MARKOV ; POPULATION ; EXPANSION ; AREA |
| 资助项目 | National Natural Science Foundation of China[41501202] ; National Natural Science Foundation of China[41701100] ; Research Fund of Hebei University of Economics and Business[2019ZD06] ; Program of the Humanities and Social Sciences Research of Ministry of Education of China[17YJCZH192] |
| WOS研究方向 | Science & Technology - Other Topics ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000543391800004 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; Research Fund of Hebei University of Economics and Business ; Program of the Humanities and Social Sciences Research of Ministry of Education of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/162386]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Song, Wei |
| 作者单位 | 1.Sichuan Met Geol Prospecting Bur, Six Six Teams 0, Chengdu 611730, Peoples R China 2.Hebei Univ Econ & Business, Sch Publ Adm, Shijiazhuang 050061, Hebei, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Xueru,Zhou, Jie,Song, Wei. Simulating Urban Sprawl in China Based on the Artificial Neural Network-Cellular Automata-Markov Model[J]. SUSTAINABILITY,2020,12(11):13. |
| APA | Zhang, Xueru,Zhou, Jie,&Song, Wei.(2020).Simulating Urban Sprawl in China Based on the Artificial Neural Network-Cellular Automata-Markov Model.SUSTAINABILITY,12(11),13. |
| MLA | Zhang, Xueru,et al."Simulating Urban Sprawl in China Based on the Artificial Neural Network-Cellular Automata-Markov Model".SUSTAINABILITY 12.11(2020):13. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
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。