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城市街景环境与社会安全事件的空间关系研究*
引用本文:蒋耀,胡啸峰,吴建松.城市街景环境与社会安全事件的空间关系研究*[J].中国安全生产科学技术,2022,18(8):24-29.
作者姓名:蒋耀  胡啸峰  吴建松
作者单位:(1.中国人民公安大学 信息网络安全学院,北京 100038;2.中国矿业大学(北京) 应急管理与安全工程学院,北京 100083)
基金项目:* 基金项目: 国家自然科学基金项目(72174203)
摘    要:为研究城市街景环境与社会安全事件之间的空间关系,提出融合语义分割技术与地理加权回归方法,基于国内典型城市街景环境数据和社会安全事件数据,验证方法的可行性。研究结果表明:模型校正拟合因子R2在0.744~0.841之间,拟合效果较好,街景环境要素指标与社会安全事件存在显著空间相关性;绿视指数和天空开阔指数与社会安全事件在大部分区域呈显著负相关关系,交通信号指数、汽车指数和人群聚集指数与社会安全事件呈显著正相关关系,研究结果可为城市安全规划和社会安全风险防控提供决策支持。

关 键 词:街景图像  语义分割  社会安全事件  地理加权回归

Research on spatial relationship between urban streetscape environment and societal security events
JIANG Yao,HU Xiaofeng,WU Jiansong.Research on spatial relationship between urban streetscape environment and societal security events[J].Journal of Safety Science and Technology,2022,18(8):24-29.
Authors:JIANG Yao  HU Xiaofeng  WU Jiansong
Institution:(1.School of Information and Cyber Security,People’s Public Security University of China,Beijing 100038,China;2.School of Emergency Management and Safety Engineering,China University of Mining and Technology (Beijing),Beijing 100083,China)
Abstract:In order to study the spatial relationship between the urban streetscape environment and societal security events,an analysis method coupled semantic segmentation technology with geographically weighted regression was proposed,which was validated by using the streetscape environment data and societal security events data in a typical city of China.The results showed that the correction fitting factor R2 of this model was between 0.744 and 0.841,which indicated a good fitting performance.Furthermore,it was found that there existed a significant spatial correlation between the streetscape environment element indexes and the societal security events.Specifically,the Green View Index and Sky Openness Index presented a significant negative correlation to the societal security events in most regions,while the Traffic Light Index,Car Index and People Gathering Index presented a significant positive correlation to the societal security events.The results can provide decision-making support for the urban security planning and the societal security risk prevention and control.
Keywords:streetscape image  semantic segmentation  societal security event  geographically weighted regression
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