| 结合空间位置和语义匹配的多源房屋灾害数据融合 |
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| 引用本文： | 倪慧珠,万术海,司涵,冯思园,任晓磊,李正强,卢涛.结合空间位置和语义匹配的多源房屋灾害数据融合[J].测绘通报,2022,0(11):118-122. |
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| 作者姓名： | 倪慧珠 万术海 司涵 冯思园 任晓磊 李正强 卢涛 |
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| 作者单位： | 1. 浙江省测绘科学技术研究院, 浙江 杭州 311100;2. 桐庐广隶土地勘测规划设计有限公司, 浙江 杭州 311599 |
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| 摘 要： | 自然灾害综合风险普查工作中,房屋灾害信息数据来源众多,为调查底库快速建库带来很大挑战。本文针对多源房屋数据难以快速提取融合的问题,基于地理空间位置的信息匹配和基于地理空间语义的信息匹配等技术,通过空间数据提取、房屋建筑增补绘、属性信息匹配、属性信息选择,实现了房屋建筑多源信息快速自动融合,为自然灾害普查工作提供了可靠翔实的房屋建筑数据底板。实践证明,该技术成果数据准确可靠,可有效提升自然灾害风险普查工作效率,大量降低人工成本。
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| 关 键 词： | 灾害普查 空间数据提取 属性信息匹配 地理空间语义 多源数据融合 |
| 收稿时间： | 2021-11-29 |
| 修稿时间： | 2022-08-26 |
Multi-source building disaster information fusion based on spatial and semantic matching |
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| NI Huizhu,WAN Shuhai,SI Han,FENG Siyuan,REN Xiaolei,LI Zhengqiang,LU Tao.Multi-source building disaster information fusion based on spatial and semantic matching[J].Bulletin of Surveying and Mapping,2022,0(11):118-122. |
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| Authors: | NI Huizhu WAN Shuhai SI Han FENG Siyuan REN Xiaolei LI Zhengqiang LU Tao |
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| Institution: | 1. Zhejiang Academy of Surveying and Mapping Science and Technology, Hangzhou 311100, China;2. Tonglu Guangli Land Survey Planning and Design Co., Ltd., Hangzhou 311599, China |
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| Abstract: | In the national survey on natural disaster risks, there are many sources of house disaster information data, which brings great challenges to the rapid construction of the investigation base database. In order to extract and fuse multi-source house data quickly, this paper realizes the rapid and automatic fusion and reliability evaluation of multi-source house information through the operations of basic data preprocessing, spatial data extraction and automatic fusion of attribute information by using technologies such as information matching based on geospatial location and information matching based on geospatial semantics. On this basis, the natural disaster census database building system is developed to provide reliable and detailed housing construction data for natural disaster census. Practice had proved that the platform results were accurate and reliable, which could effectively improve the efficiency of natural disaster risk survey and greatly reduce labor costs. |
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| Keywords: | natural disaster census spatial data extraction attribute information matching geospatial semantic multi-source data fusion |
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