The development of universal public map service is the milestone for the coming of digital life and smart city. And how to detect the group-user access patterns and how to map the virtual access behaviors into real world behaviors precisely and quickly is the key to accelerate the development of the public map service and the construction of smart city. This paper researches the temporal and spatial characteristics of group-user access hotspots in public map service. Based on the massive user access logs and using three statistical methods of group analysis, time series analysis and three-dimensional visualization, the research results show the group-user access hotspots have the characteristics of week periodicity, and most hotspots appear constantly within one period. Moreover, the boxplots and density diagrams of access hotspots distance show that a large amount of the hotspots are gathered within short distance while much less hotspots are far apart. And the spacing distances distribution differs in different map layers. The temporal and spatial characteristics of hotspots in public map service reveal the behavioral intention behind the massive data of user access, it digitizes the real world behaviors, which improves the man-earth relationship in smart city.