Densham’s article reviews work on spatial decision support systems (SDSS), conceptualizing them as distinctive from the GIS of the time. Crucially, Densham problematizes the direct application of GIS to solving spatial decision problems, proposing instead that dedicated SDSS software incorporating specialized architecture and a modular code repository or model base management system (MBMS) be developed instead. Nonetheless, the author envisions a continued role for geographers in the informed decision process, in order to avoid “the selection of variables with inappropriate levels of resolution and geographical extent… ultimately result[ing] in solutions that are deemed unsatisfactory when evaluated in terms of the quality of the decision-making process that generated them” (p. 403).
Densham argues that “[c]urrent GIS fall short of providing GIA capabilities” because “their support of analytical modeling is lacking”, their display and reporting capabilities are limited, and they “are not flexible enough to accommodate variations in the either the context or the process of spatial decision making” (p. 405). There is no date on the paper, but its most recent citation is 1991, suggesting that when this article was published, the Soviet Union was still a thing and Apple products were at their first peak of popularity: has GIS today overcome the limitations of Densham’s era? I would argue it has. For starters, hardware and operating systems have made huge advances since the year of my birth, supporting greater data storage, graphical capabilities and computational power for analytical programs (even interpreted ones!). Meanwhile, the advent of the internet along with new, more user-friendly scripting languages like Python, has made implementing model capabilities within GIS’ DBMS framework and the existence of code libraries—both dismissed by Densham as not feasible—possible. These technological advances, along with improvements in graphical representation and user interfaces, have enabled GIS software to integrate decision support modules (such as the classic SDSS problem, location-allocation) directly into the software or as a plugin while retaining the potential for customization of decision models. Today, producers of GIS software packages aggressively market their products’ SDSS functionality.
GIS and its enabling technologies have made strides, but so have competing technologies in business information/intelligence systems/software (BIS) such as the impressive Tableau software package. Despite the increasing role of spatial data visualization, analytics and decision support in BIS, development of these tools tends to be the realm of computer scientists and not geographers. Even though tech has advanced considerably across the board, Densham’s argument that geographers are not obsolete still resonates today. As geographers, we need to assert our place at the spatial decision support table, both by advancing GIScience such that GIS remains relevant to (and if possible, ahead of) contemporary decision support analytics, and by reminding software developers and decision-makers of the importance of a nuanced understanding of spatial concepts and considerations.
-FischbobGeo