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A Multi-source Data Based Analysis Framework for Urban Greenway Safety

机译:城市绿道安全的多源数据分析框架

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As a green lining open space, greenways are closely related to the life of urban residents. At present, reports of crimes occurring in greenways are emerging in an endless stream. In order to explore the factors affecting greenway safety, this study, under the guidance of CPTED theory, conducts research by means of big geodata. Three representative greenways in Beijing urban area—the Northwest Tucheng greenway, Second Ring Road greenway and the Three Mountains and Five Gardens greenway—are taken as the research objects. Through the utilization of big geodata information from each platform, including street view analysis, POI analysis, and sports activity data analysis, four factors including space boundary, maintenance, public surveillance and activity support are considered comprehensively, and important influencing factors are selected to construct the analysis framework for urban greenway safety. The results showed that the greenway with high safety has the characteristics of low density of arbor shrubs, low enclosure degree of walls, low distribution density of various buildings, high traffic flow and high frequency of use. The feasibility of the analysis framework is verified by the current situation of greenway safety, so as to provide scientific and reasonable technical support for the construction of safe urban greenways.
机译:作为一个绿色衬砌的开放空间,Greenways与城市居民的生活密切相关。目前,在绿道中发生的犯罪报告正在出现在无休止的流中。为了探讨影响绿道安全的因素,本研究根据Cppted理论的指导,通过大地理数据进行研究。北京市地区三大代表团 - 西北地区绿道,二环道绿道和三山和五大花园绿道 - 被视为研究对象。通过利用来自每个平台的大地理数据信息,包括街道视图分析,POI分析和体育活动数据分析,全面考虑了四种因素,包括空间边界,维护,公共监控和活动支持,并选择了重要的影响因素来构建城市绿道安全分析框架。结果表明,高安全性的绿道具有乔木灌木密度低,墙壁低,分布密度低,各种建筑物的低,流量高,使用寿命高。通过绿道安全现状验证了分析框架的可行性,为安全城市绿道建设提供科学合理的技术支持。

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