Bridging the Gap Between GIS and Solid Spatial Statistics

Over the past few decades GIS and statistical spatial data analysis tools have been successfully applied in the fields of meteorology, environmental monitoring, ecological analysis, and mineral exploration (to name but a few). While these synergistic tools operate on spatial data, as yet they have not been incorporated into a single 'user-friendly' software environment. For this reason statistical methods remain somewhat of a mystery to mainstream GIS practitioners. To widen the use of spatial statistics, it is argued that software packages, such as SAS, SPLUS and GSLIB should incorporate three essential components that are provided by a GIS: a robust spatial database (with associated geographic coordinate systems), spatial models and visualization algorithms. An alternative solution is to incorporate statistical algorithms into GIS software. The Geostatistical Analyst, an extension to ESRI’s ArcGIS 8.1, is an example of the latter approach. This represents a new level of integration of geostatistical techniques within a GIS framework. The software provides a simple windows-based interface for users that are unfamiliar with spatial statistics.