A place in history: a guide to using GIS in historical research

CHAPTER 1: GIS AND ITS USES IN HISTORICAL RESEARCH

1.3 Uses of GIS

There are three basic categories of use that GIS can be put to: as a spatially referenced database; as a visualisation tool; and as an analytic tool. A spatially referenced database allows us to ask questions such as 'what is at this location?', 'where are these features found?', and 'what is near this feature?'. It also allows us to integrate data from a variety of disparate sources. For example to study the dataset on hospitals described above, we might also want to use census data on the population of the areas surrounding each hospital. Census data are published for districts that can be represented in the GIS using polygons as spatial data. As we have the coordinates of the hospitals and the coordinates of the district boundaries we can bring this data together to find out which district each hospital lay in, and then compare the attribute data of the hospitals with the attribute data from the census. We may also want to add other sorts of data to this: for example data on rivers represented by lines; or wells represented by points to give information about water quality. In this way information from many different sources can be brought together and interrelated through the use of location. This ability to integrate is one of the key advantages of GIS.

Once a GIS database has been created, mapping the data it contains is possible almost from the outset. This allows the researcher a completely new ability to explore spatial patterns in the data right from the start of the analysis process. As the maps are on-screen they can be zoomed in on and panned around. Shading schemes and classification methods can be changed, and data added or removed at will. This means that rather than being a product of finished research, the map now becomes an integral part of the research process. New ways of mapping data are also made possible, such as animations, fly-throughs of virtual landscapes, and so on. It is also worth noting the visualisation in GIS is not simply about mapping: other forms of output such as graphs and tables are equally valid ways of visualising data from GIS.

Although visualisation may answer some of the questions a researcher has about a dataset, more rigorous investigation is often required. Here again GIS can help. The combined spatial and attribute data model can be used to perform analyses that ask questions such as 'do cases of this disease cluster near each other?' in the case of a single dataset; or 'do cases of this disease cluster around sources of drinking water?' where more than one dataset is brought together. To date, this form of analysis has been well explored using social science approaches to quantitative GIS data. It has not been so well explored using humanities approaches to qualitative data, but this is one area where historians are driving forward the research agenda in GIS.