Haklay et al’s article “So Go Downtown” describes an intricate model of pedestrian movement, STREETS. I began the article somewhat skeptical of the need for such a model (is it not good enough to simply collect enough data on pedestrians?) and the capacity of the model to think of everything; for example, agents deviating from their agenda, socioeconomic status, etc. Nearly every “but what about…” was answered in the article, and I was surprised by the complexity of the model and how much it takes into account. I also found the combination of raster, vector and network data to be fascinating: often in our education, these data models are taught as disparate and we do not use them in conjunction. This article started to give me an idea of the ways that these data models can, in fact, be used together.
One problem with the model that the authors raise is that the town is “spatially closed” – the town in the model is a bubble, with no competing towns or suburbs nearby. The authors recognize that adding further complexity by expanding what is a closed model would be an incredible task. It is difficult to place boundaries on what should and should not be included in a model – it requires making serious choices about what is significant enough to be included in the micro world of the model.
Clearly, there is room for expansion and improvement in the modeling and simulation realm of GIScience, as existing models are modified and new ones are created.
– denasaur