基于贝叶斯时空模型的城管事件时空变化分析

城市管理事件具有显著的地域特征和周期性特征,挖掘城管事件中隐含的时空规律和潜在影响因子对城市管理具有重要指导意义。然而,目前针对城管事件时空变化及影响因素驱动效应的研究仍较为少见。本文基于贝叶斯时空模型,针对西北某地H市P区的街面秩序类、市容环境类以及宣传广告类城管事件在一周之中的时空演变特征进行建模分析,并探究了影响城管事件案发风险的潜在影响因子。研究发现:①在空间上,3类城管事件的相对风险分布存在差异,街面秩序类事件集中在城市的居住功能区和商业功能区,而市容环境类集中在城市的居住功能区,宣传广告类主要集中在城市的商业功能区,空间风险后验概率估计表明,以上2个区域是城管事件的热点区域。②在时间上,每逢周二、周五以及周六,城管事件的相对风险较为突出,但总体上没有明显的单调性。每天的8-10时和14-15时是城管事件高发的时段,其相对风险远高于其他时段。③城市建成环境对城管事件的潜在影响存在差异。研究区域内餐饮、交通、生活服务等城市基础设施与城管事件的关联最为紧密,且都表现为正相关。④城管事件的案发风险呈现出明显的时空异质性,渐进性的建模过程表明在分析城管事件数据时考虑空间与时间效应的影响是合理且有必要的。研究表明,贝叶斯时空模型的分析结果满足城管部门日常工作中关于城管事件智能分析与重点管控的需求。

Spatiotemporal Variability of Urban Management Events based on the Bayesian Spatiotemporal Model

Urban management events are regional and periodic. The spatiotemporal laws and potential impact factors implied in urban management events are vital for improving urban management. However, research on the temporal and spatial changes of urban management events and influencing factors are rare. In this paper, by using the Bayesian space-time model, we modeled and analyzed the temporal and spatial evolution characteristics of three types of city management events-street order, urban environment, and publicity advertising-in the P district of H city, Northwest China, and explored the impact of urban management events as well as the underlying impact factors. We found that: (1) There were spatial differences in the relative risk distribution of the three types of urban management events. The street order type was concentrated in the residential and commercial areas of the city, while the urban environment type was concentrated in the residential areas of the city. The advertising type was mainly concentrated in the commercial areas of the city. The spatial risk posterior probability estimate indicated that the above two regions are hotspots of urban management events. (2) The relative risks of urban management events were more prominent on Tuesdays, Fridays, and Saturdays, but there was no obvious monotony in general trends. Meanwhile, the hourly trends had irregular fluctuation, everyday from 8 to 10 and from 14 to 15, it was a period of the high incidence of urban management events, and its relative risk was much higher than other periods. (3) For different built environments, the potential impacts of these factors were quite different. The relative risk of urban management events was significantly associated with restaurants, transportation, and living services, all positively correlated. (4) The relative risk of urban management events presented obvious spatial and temporal heterogeneity. and it is reasonable and necessary to consider the impact of spatial and temporal effects when analyzing urban management events data. Our findings are meaningful for relavant government departments to make effective policies to control and reduce the relative risk of urban management events, especially for the study area.