Advanced Technologies in Geographic Process Modeling

Dear Colleagues,

The discipline of geography moved from a static to a process-oriented perspective about a hundred years ago. Its computational representation is still struggling. From the early days of linking GIS and process models to even recent approaches of capturing the complexity of geographic phenomena with agent-based models, we are hampered by the chasm between low-level ontological understanding (Reitsma 2005) and its translation into practical tools that go beyond the mere automatization of workflows (Hofer 2017). The current enthusiasm for geographic data science, in spite of all the benefits that can be derived from meshing up diverse data sources, still misses the point that these data represent a static snapshot that may allow for the derivation of movements but not for the understanding of process drivers.

We are inviting submissions that critically reflect on these constraints and point to novel approaches to overcome them. The preliminary paper topics beneath may provide some guidance to the kinds of papers we are seeking.

References cited:

Hofer, B., Mäs, S., Brauner, J., & Bernard, L. (2017). Towards a knowledge base to support geoprocessing workflow development. International Journal of Geographical Information Science, 31(4), 694-716. https://doi.org/10.1080/13658816.2016.1227441, https://doi.org/10.1080/13658816.2016.1227441

Reitsma, Femke & Albrecht, Jochen. (2005). Implementing a new data model for simulating processes. International Journal of Geographical Information Science. 19(10). 1073-1090. 10.1080/13658810500390943.

Prof. Dr. Jochen Albrecht
Guest Editor

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