Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm
文献类型：期刊论文
| 作者 | Zhang, Xueyan1,2 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2020-06-01 |
| 卷号 | 9期号:6页码:14 |
| 关键词 | rural homestead household survey U-net UAV China |
| DOI | 10.3390/ijgi9060403 |
| 通讯作者 | Zhang, Xueyan(xyzhang@igsnrr.ac.cn) |
| 英文摘要 | China's rural population has declined markedly with the acceleration of urbanization and industrialization, but the area under rural homesteads has continued to expand. Proper rural land use and management require large-scale, efficient, and low-cost rural residential surveys; however, such surveys are time-consuming and difficult to accomplish. Unmanned aerial vehicle (UAV) technology coupled with a deep learning architecture and 3D modelling can provide a potential alternative to traditional surveys for gathering rural homestead information. In this study, a method to estimate the village-level homestead area, a 3D-based building height model (BHM), and the number of building floors based on UAV imagery and the U-net algorithm was developed, and the respective estimation accuracies were found to be 0.92, 0.99, and 0.89. This method is rapid and inexpensive compared to the traditional time-consuming and costly household surveys, and, thus, it is of great significance to the ongoing use and management of rural homestead information, especially with regards to the confirmation of homestead property rights in China. Further, the proposed combination of UAV imagery and U-net technology may have a broader application in rural household surveys, as it can provide more information for decision-makers to grasp the current state of the rural socio-economic environment. |
| WOS关键词 | RURAL HOMESTEADS ; CRACK DETECTION ; LAND-USE ; CHINA ; POLICY ; WILLINGNESS |
| 资助项目 | National Key R&D Program of China[2018YFC1508805] ; National Key R&D Program of China[2016YFC0500508] ; National Natural Science Foundation of China[31600351] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA20010302] |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000551693400001 |
| 出版者 | MDPI |
| 资助机构 | National Key R&D Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/158310]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Xueyan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Ctr Chinese Agr Policy, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Xueyan. Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2020,9(6):14. |
| APA | Zhang, Xueyan.(2020).Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,9(6),14. |
| MLA | Zhang, Xueyan."Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 9.6(2020):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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