Census data is not only useful for the whole country,but also valuable to the local levelsFK(W25。40ZQand even to the private sectors.If we use some advanced information technologies in the 5th National Census,we will make the Census information more valuable and useful.Now,GIS technology is commended to deal with demographic problems in China.We are very familiar with GIS technology,but we did little in Census area.We should do some application research on Census GIS immediately. Firstly,this paper introduces the application background of Census GIS around the world.Now,there are many successful systems in developed countries,such as TIGER in USA,HMSO in England,etc.All these systems are very helpful for us to develop our own Census GIS.In recent years,information technology has been widely used in China,and many cities have prepared abundant digital information,such as digital maps,Orthophotos,data on industry,etc.There are good conditions to develop Census GIS in many cities,especially in metropolises in our country. Secondly,a three-layer structure for Census GIS designing is proposed,which are the data layer,the management layer,and the application layer.As a typical example,Guangzhou city is picked up in this paper.①The data layer in Guangzhou Census GIS includes some typical integrated urban data (about Census,industry,terrain,etc.).②Census database and data warehouse based on integrated data are comprised in the management layer.③Four application systems (for integrated application,for demographic task,for decision support,and for information distribution based on Internet) are included in the third layer. Finally,three issues on Census GIS implementing are discussed in brief.①Be sure to find an efficient way to manage the integrated data,be sure to choose a uniform geographic coordinate system and an effective geocoding method.②To build a data warehouse based on integrated urban data,then develop a decision support system (DSS) based on the data warehouse.③To use some useful analysis tools such as on-line analysis process (OLAP),data mining (DM),and spatial analysis,etc.