Exploring the Attractiveness of Residential Areas for Human Activities Based on Shared E-Bike Trajectory Data
文献类型：期刊论文
| 作者 | Cheng, Xiaoqian1; Du, Weibing1,2; Li, Chengming1,3; Yang, Leiku1; Xu, Linjuan4 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2020-12-01 |
| 卷号 | 9期号:12页码:20 |
| 关键词 | shared e-bike trajectory commuting activity urban residential area machine learning urban hot spots |
| DOI | 10.3390/ijgi9120742 |
| 通讯作者 | Du, Weibing(dwb@hpu.edu.cn) |
| 英文摘要 | Human activities generate diverse and sophisticated functional areas and may impact the existing planning of functional areas. Understanding the relationship between human activities and functional areas is key to identifying the real-time urban functional areas based on trajectories. Few previous studies have analyzed the interactive information on humans and regions for functional area identification. The relationship between human activities and residential areas is the most representative for urban functional areas because residential areas cover a wide range and are closely connected with human life. The aim of this paper is to propose the CARA (Commuting Activity and Residential Area) model to quantify the correlation between human activities and urban residential areas. In this model, human activities are represented by hot spots extracted by the Gaussian Mixture Model algorithm while residential areas are represented by POI (point of interest) data. The model shows that human activities and residential areas present a logarithmic relationship. The CARA model is further assessed by retrieving urban residential areas in Tengzhou City from shared e-bike trajectories. Compared with the actual map, the accuracy reaches 83.3%, thus demonstrating the model's reliability and feasibility. This study provides a new method for functional areas identification based on trajectory data, which is helpful for formulating the urban people-oriented policies. |
| WOS关键词 | URBAN LAND USES ; TRAVEL BEHAVIOR ; ELECTRIC BIKES ; TAXI GPS ; PATTERNS ; REGIONS ; IMPACT |
| 资助项目 | National Natural Science Foundation of China[41975036] ; National Natural Science Foundation of China[51709123] ; National Key Research and Development Program[2018YFC0407403] ; Special Basic Research Fund for Central Public Research Institutes ; Doctoral Foundation of Henan Polytechnic University[B2016-11] |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000601984000001 |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program ; Special Basic Research Fund for Central Public Research Institutes ; Doctoral Foundation of Henan Polytechnic University |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/137512]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Du, Weibing |
| 作者单位 | 1.Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Henan, Peoples R China 2.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China 3.Chinese Acad Surveying & Mapping, Beijing 100830, Peoples R China 4.Chinese Acad Sci & Minist Water Resources, Key Lab Sediment, Yellow River Conservancy Commiss, Yellow River Inst Hydraul Res, Zhengzhou 450003, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cheng, Xiaoqian,Du, Weibing,Li, Chengming,et al. Exploring the Attractiveness of Residential Areas for Human Activities Based on Shared E-Bike Trajectory Data[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2020,9(12):20. |
| APA | Cheng, Xiaoqian,Du, Weibing,Li, Chengming,Yang, Leiku,&Xu, Linjuan.(2020).Exploring the Attractiveness of Residential Areas for Human Activities Based on Shared E-Bike Trajectory Data.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,9(12),20. |
| MLA | Cheng, Xiaoqian,et al."Exploring the Attractiveness of Residential Areas for Human Activities Based on Shared E-Bike Trajectory Data".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 9.12(2020):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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