Multi-scale geo-spatial data integration, which is one key issue of geo-spatial data integration, is the combining, integrating and decomposing processes in which boundary of spatial feature are processed. The authors divide geo-spatial data integration into spatial multi-scale data integration and temporal multi-scale data integration, and analyse the scientific foundation and popular methods of the two kinds of geo-spatial data integration.
Multi-scale geo-spatial data integration is necessary because the same spatial entity and geo-processes have different property in multi-scale geo-spaces, and geo-spatial data based applications always deal with spatial scale change. The authors analyze several multi-scale geo-spatial data integration types such as data
generalization, data detailing, data extracting, data updating and explain geo-spatial data integration methods in each type in detail.
The temporal scale indicates the period of geo-processes existing,the same entities or geo-processes have different characteristics in variation temporal scale, for some time sensitive geo-spatial data based applications, temporal multi-scale geo-spatial data integration can not be avoided. Based on the time characteristic analysis on geo-spatial data, the authors describe some temporal multi-scale geo-spatial data integration methods, such as weight analysis, time serial analysis method, data combining method, indirect correlation method.