ABSTRACT
Integration of spatial statistical analysis and geographic information systems (GIS) is an important next step in the development of spatial analysis technologies. The strength of GIS lies in its ability to maintain absolute and relative spatial location information about geographic phenomena. This chapter explains how spatial statistics can support GIS analyses, and vice versa. It explains the importance of efforts to further integrate the technologies, by presenting a spatial statistical analysis performed with data stored in a GIS database on societal and environmental characteristics of Rwanda, Central Africa. The log-likelihood and Akaike Information Criterion are presented for comparison with the spatial statistical models. In the Rwanda example a fairly strong relationship is demonstrated between the net migration rate and population pressure, land availability, and socioeconomic push and pull factors. Population pressure, as it affects land availability, among other things, appears to be one of the driving forces in the internal migration in Rwanda.
