The Kashmir conflict is a territorial conflict between India and Pakistan.
Maps have played a central role in conflicts and conflict resolutions for centuries. In recent periods, the rise of digital mapmaking and GIS specifically have at times complicated conflicts or gave alternative forms of settlement for conflicts.
Using GIS to Map Territories
One aspect of mapping using digital tools and GIS is that content now can be more easily varied or serve the interests of different actors using GIS layers, giving rise to many different voices in a conflict. This can serve to even complicate territorial conflict, as many voices might have to be present in any resolution. A recent study of the use of GIS in different land use planning conflicts has shown that GIS has increased the frequency of conflict between groups and has required more complex conflict resolution approaches in resolving territorial disputes because there are now more stakeholders to consider and different perspectives.[1]
GIS and digital tools have also played a positive role in major recent conflicts. Conflict over territory could be resolved more virtually using a variety of such tools. In the Daytona Accords negotiations that helped to end conflict in the former Yugoslavia, a 3D visualization tool that combined satellite and other imagery, called PowerScene, was used by the US delegation to indicate that a corridor should be given to Gorazde, a largely Muslim town, so as to avoid future conflict in that area.[2]
The perception has been that the use of GIS might be a relatively unbiased way at looking at conflict. However, GIS likely makes it easier for multiple sides to alter reality in conflict and may make it more difficult to determine exact circumstances. Selection bias and measurement validity become important issues to measure in the creation of maps that best represent conflict. For measurement validity, this can be overcome by only providing datasets that are easily measurable or can be empirically observed. For selection bias, analytical solutions could be used in place of empirical or spatial locations of borders. In this case, the analysis can be done or assessed without certain knowledge of where borders are. If bias is found, then that data are removed irrespective of the border locations that could be represented by an analytical set. This can be done using raster representation of borders, for instance.