Analytical Operations in GIS

Geographic information systems (GIS) have grown to be big and somewhat unwieldy software packages with hundreds, sometimes thousands, of functions. The majority of these are, however, devoted to facilitating data input/output and general data management. Only a small fraction is devoted to what arguably distinguishes a GIS from other software packages, the set of analytical operations. A practical definition of “analytic” in the context of this entry is an operation that fully supports the “I” in GIS. In other words, an analytical GIS operation creates new information beyond what has explicitly been stored in the database.

Based on this definition, a database query is not an analytical GIS operation because it merely retrieves what has been stored before, though possibly in a different organizational structure. The boundary between analytical and other GIS operations is not always clear-cut because complex query operations can be expanded to be analytical operations proper. The litmus test in the end is whether the operation results in new data that did not exist before.

A classic example is the overlay operation. As opposed to conditional queries or recoding operations, the overlay results in the creation of new geometries not previously stored in the database, and these new geometries inherit their attributes from their parent geometries according to user- or system-specified rules (Figure 1).

The logic of this overlay operation is typically based on Boolean operands such as AND, OR, NOT, or XOR. Together with its cousin, the buffer operation, this analytical operation is responsible for more than half of the generally used analytical capabilities of GIS. Following an often cited characterization by Mike Goodchild, we can use the data model underlying the input [Page 72]and/or output to develop a hierarchy of ever more complex analytical GIS operations. On the object-centered side of analytical operations, one may (a) just describe point patterns, (b) create new geometries and attributes as in our overlay example, (c) perform some rather involved operations on transportation or hydrological networks, or (d) model the interaction between two or more objects. If we follow the field perspective of geospatial data, then we have the whole range of Map Algebra operations that truly get us into the modeling of geographic phenomena.

Figure 1 Schematic overlay operation illustrating the combination of new area definitions and attribute value calculations for a flood damage scenario

Source: Author.

Jochen Albrecht generated a list of 20 so-called universal GIS operations from a user interface perspective that encompass a wide range of GIS tasks. Although this list seems surprisingly short and already contains a few exotic or rarely used examples, it has been shown that it covers most of what a wide range of GIS users actually want to see in a GIS. The question then arises, What makes analytical GIS operations so important? And the answer lies not in their quantity but in their overwhelming usefulness once they become part of a larger geoprocessing workflow.

While originally developed for desktop GIS, this set of data model-independent analytical GIS operations is now the focus of numerous endeavors to standardize the analytical component of GIS Web services. In both cases, there is a need for well-specified operations that can be concatenated to workflows and larger models in support of spatial decision making. The description of analytical GIS operations is hence not aimed anymore at improving GIS user interfaces but at the automatic generation of scripts that allow clients to create mashups for Web-based GIS applications that range from object-based image analysis and environmental model integration to geocollaboration and multicriteria decision support. Well-defined analytical GIS operations also form the building blocks for libraries, not of data but of models that help us analyze data and that can be shared or sold. These model libraries will eventually capture geographic knowledge and serve the electronic central role that the discipline of geography plays in the orchestra of sciences. But it all starts with a small number of analytical GIS operations.

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