Plant and animal species, as well as the ecosystems they form, all have their own geographical or spatial ranges over which they are found. Similarly, different types of human economic activity are distributed about the globe in different spatial patterns. The sources and flows of environmental pollutants, as well as patterns of environmental change and damage, are also distributed unevenly through space over a continuum of scales. Geographical Information Systems (GIS) allow spatial data, such as these, to be handled and analysed using computers. This has many advantages over the static representations provided by traditional paper maps.
GIS tends to describe the software that enables spatial analysis, but the term also refers to the collection of digital spatial data that analyses are based on. It is these spatial databases that allow GIS to be used so effectively in environmental studies.
Databases not only store the geographical locations and geometries of spatial features (e.g. areas representing marine reserves, points representing industrial effluent outlets or lines representing river networks) but also links to the many attributes that may be associated with them (e.g. areas of marine reserves, concentrations of pollutants discharged at an outlet, or discharge of a river). Such databases can be used for inventory, and queries can be made of the data to answer questions of the type "what is at?" or "where is?" The former might involve pointing to a location on a digital map of elevation and finding out how high that location is, while the latter might query data on marine reserves to find where all of the reserves greater than a specified area are located.
The power of GIS does not come from interrogating individual layers of spatial data, but from the ability to combine many different spatial data layers. Spatial overlay allows many layers to be considered simultaneously, and combines the attribute data for these. This allows much more complex queries of the spatial data to be made, for example, "where are the effluent discharges to rivers that have flows below X entering marine reserves of Y km2?"
Because the data held by GIS are spatial, standard GIS software tends to allow data to be manipulated in terms of distances between features. Such proximity analysis allows the creation of buffer zones to be calculated around points or lines or areas. An example might be to find the area that is 100m on either side of a river. Distances between features can also be calculated, such as the distance between effluent outlets and the nearest water quality-monitoring site. In this example, the concept of distance would be dealt with using network analysis, and the distance would be measured by the GIS through the river network and not simply "as the crow flies". Network analysis can also be used to establish connectivity. For example, effluent can flow downstream, but not up, so parts of a river susceptible to a pollution incident should be identifiable.
GIS software comes with the facility to do many different statistical analyses. One of the most useful is spatial interpolation, whereby incomplete or unevenly sampled data is used to create a continuous or complete data layer. For example, if the value of an environmental variable such as rainfall is only known from a few meteorological stations, spatial interpolation algorithms would allow rainfall to be estimated elsewhere on the basis of information from the known sites.
The availability of large volumes of spatial data has only materialised over the past few years. As a result, the application of the many tools available in GIS to the spatial analysis of problems in the environment has only scratched the surface of the potential problems that may eventually be addressed by this developing technology.