Optimizing distribution of droneports for emergency monitoring of flood disasters in China
文献类型：期刊论文
| 作者 | Lu, Ming2,3; Liao, Xiaohan3; Yue, Huanyin3,4; Huang, Yaohuan3; Ye, Huping3,4; Xu, Chenchen3,4; Huang, Shifeng1 |
| 刊名 | JOURNAL OF FLOOD RISK MANAGEMENT
 |
| 出版日期 | 2020-01-10 |
| 页码 | 11 |
| 关键词 | droneports facility location problem flood rescue UAV remote sensing observation network |
| ISSN号 | 1753-318X |
| DOI | 10.1111/jfr3.12593 |
| 通讯作者 | Liao, Xiaohan(liaoxh@igsnrr.ac.cn) |
| 英文摘要 | Floods occur frequently, impacting large areas, displacing thousands of people and causing great losses. Unmanned Aerial Vehicle (UAV) remote sensing is easy to obtain high-resolution image that is immensely helpful to timely assess the flood situation and provide scientific decision-making for emergency rescue. The important roles of UAV remote sensing have been widely recognized. However, the sudden onset of floods and lack of UAV resources deployed nearby have restricted rapid response of UAVs in emergency rescue. A UAV remote sensing observation network on a regional scale has been proposed to deal with these emergencies. However, how to build this UAV network and where to deploy UAV resources are still mysterious. In this study, the Maximum Covering Location Problem (MCLP) model was improved to distribute a series number of droneports in China. Finally, 81 droneports were selected from 268 potential facility points, which covered 61.84% risk of total demand area. Droneports have been allocated near flood-prone areas and most floods in China can be monitored within 2 hours, which is critical for saving lives and reducing losses. The construction of UAV airport networks will surely contribute to an integrated disaster emergency observation system combining satellite, airplane, UAV, and ground observations in China. |
| WOS关键词 | LOCATION ; RISK |
| 资助项目 | China Postdoctoral Science Foundation[2018M640170] ; National Key Research and Development Program of China[2017YFB0503005] ; National Natural Science Foundation of China[41771388] |
| WOS研究方向 | Environmental Sciences & Ecology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000506483700001 |
| 出版者 | WILEY |
| 资助机构 | China Postdoctoral Science Foundation ; National Key Research and Development Program of China ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/131432]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liao, Xiaohan |
| 作者单位 | 1.Minist Water Resources Peoples Republ China, China Inst Water Resources & Hydropower Res, Beijing, Peoples R China 2.China Acad Space Technol, Qian Xuesen Lab Space Technol, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Tianjin Inst Applicat & Res Unmanned Aerial Vehic, Tianjin, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Ming,Liao, Xiaohan,Yue, Huanyin,et al. Optimizing distribution of droneports for emergency monitoring of flood disasters in China[J]. JOURNAL OF FLOOD RISK MANAGEMENT,2020:11. |
| APA | Lu, Ming.,Liao, Xiaohan.,Yue, Huanyin.,Huang, Yaohuan.,Ye, Huping.,...&Huang, Shifeng.(2020).Optimizing distribution of droneports for emergency monitoring of flood disasters in China.JOURNAL OF FLOOD RISK MANAGEMENT,11. |
| MLA | Lu, Ming,et al."Optimizing distribution of droneports for emergency monitoring of flood disasters in China".JOURNAL OF FLOOD RISK MANAGEMENT (2020):11. |
入库方式： OAI收割
来源：地理科学与资源研究所
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