Seen from the perspective of the scientist or the policy maker, analytical techniques are a means to an end: for the scientist the development of rigorous, scientifically based understanding of events and processes; for the policy maker the strategic and tactical deployment of resources informed by the application of scientific method and understanding. This chapter describes various areas that raise questions calling for the analysis of spatial data.

The chapter is organized as follows. Section 1.1, identifies how location and spatial relationships enter generically into scientific explanation and section 1.2 briefly discusses how they enter into questions in selected thematic areas of science and general scientific problem solving. Section 1.3 considers the ways in which geography and spatial relationships are important in the area of policy making. Section 1.4 gives some examples of how problems and misinterpretations can arise in analysing spatial data.

Spatial data analysis in science

All events have space and time co-ordinates attached to them – they happen somewhere at sometime. In many areas of experimental science, the exact spatial co-ordinates of where experiments are performed do not usually need to enter the database. Such information is not of any material importance in analysing the outcomes because all information relevant to the outcome is carried by the explanatory variables. The individual experiments are independent and any case indexing could, without loss of information relevant to explaining the outcomes, be exchanged across the set of cases.