Abstract: Large amounts of data of historical events have been accumulated for many years through the operations of the Urban Grid Management System. These events are spatially aggregated. By examining the spatial distribution of these events and measuring the corresponding aggregation levels, we can provide important support for making sound decisions on allocation and distribution of urban management resources. Spatial point pattern analysis studies the distribution patterns of geographical point entities or events, and has been widely used in various disciplines including criminal statistics, ecology and public health. In this paper, we investigated two major types of city management events in Jianghan District, Wuhan City, traffic-blocking stall and garbage disposal events, from January to August in 2011. The results show that: the number of hotspots with traffic-blocking stall events had a decreasing trend, while that of garbage disposal events had an increasing trend. Both types of events presented significant spatial aggregation with roughly the same spatial scale of 1000 m. The spatiotemporal aggregation index indicated strong spatiotemporal correlations for both types of events where the space difference is below 500 m and time difference below 3 hours. The research shows that: with the help of spatial point pattern analysis, we can provide city managers with efficient visual analytics tools to identify spatial aggregation patterns of the events, and a quantitative method to measure the degree of spatial aggregation, which also lays a foundation for further statistical modeling.

Key words: city management events, evolution, Jianghan District,Wuhan City, spatial distribution, spatial point pattern, visual analytics