I enjoyed reading this article and see many parallels between the author’s arguments and the goals of critical GIS. Couclelis argue that planning has lost its future-oriented approach and is absorbed by operational and managerial tasks. She urges planners and modelers to incorporate scenario writing, visioning and storytelling into PSS. Although I understand the gist of PSS, it would have been helpful if the author had offered a description of what the system consists of. How is it different for conventional GIS software? Are there functionalities that allow easy integration of scenarios?
The 3 methods advocated in the articles are qualitative in nature. “Models are based on science; planning is about policy” (1359) indicate a tension between quantitative and qualitative approaches. This exact tension experienced by GIS practitioners and social theorist is what gave rise to Critical GIS. Large amounts of work is being done in Qualitative GIS with the goal to incorporate different types of data into GIS, such as in-depth interviews, ethnography studies, emotions and even sounds. Some researchers have also employed mixed methods, that is, using quantitative and more personal qualitative datasets. I will refrain from saying too much here because I will be taking about it tomorrow. This are in Critical GIS is definitely promising for scenario writing, visioning and storytelling.
On another notes, Couclelis writes, “Land-use and land-cover change are themselves issues spanning the local-to-global spectrum so that changes at one geographic scale may have significant repercussions at several other scales and times” (1358). This idea of events having effects for multiple scales was brought up during the lecture on “Scale” [Figure 1]. To be able to define and visualize these inter-scale interactions in GIS will be increasingly important as the world becomes more connected. This capability will allow us to get a more complete picture of consequences from a certain disturbance/event. For example how “open” is the city of Longueuil to changes in immigration trends from Asia? Or from changes from consumer preferences living in Germany? Analysis like these cannot be easily carried out in GIS because the system requires all the layers to be in the same scale. When will GIS be able connect places on two different map that do not match in scale?