The study used data of residential burglary in Daan District from Jan. 2007 to Jun. 2009, and tried to explore issues of spatial distribution and clustering of burglary hotspots in different spatial levels of ”village area”, ”police station district”, and ”virtual area” by using GIS crime mapping and aggregate data spatial analysis as major methods, in order to propose and simplify efficiency crime prevention policies for police organizations with their capacity. The results showed that aggregate data spatial analysis of different parameters setting can produce thematic maps which display spatial clustering of crime hotspots/ coldspots significantly. We then discovered that the residential burglaries were not randomly distributed, but significantly concentrated in certain areas of different area levels of Da-an District. Further, analysis of different spatial levels helps the police mastering spatial distribution of crime hotspots more and correctly, and the spatial clustering analysis in ”virtual area” level is more close to real spatial distribution of crime hotspots than in ”police station district” and ”village area” level for practice of crime prevention.