Visualizing the Complex World of 1492

Brandon Plewe, Brigham Young University

Historical Geography is complicated. For a variety of reasons, our knowledge of the past is incomplete and uncertain. Furthermore, many aspects of the pre-modern world were more conceptually unfamiliar and less standardized than they are today. How can we represent these issues in GIS and on maps in a way that is simple to enter and store, intellectually honest, and easy for a broad audience to understand? The political geography of 1492 presents an especially fruitful case for this. On the eve of European imperialism, the world was full of hundreds of states, with a variety of governmental systems from feudal hierarchies to bureaucratic republics to vast sultanates to simple chiefdoms. Even basic concepts of territoriality varied widely, making the presumption of clear boundaries impossible. In the coming decades, European powers would gradually dismantle this organic complexity and reconstruct it into what they viewed as a rational (i.e., imperial) world order. To create a map of the world at this "Pivot of History," a strategy was developed (based on multiple past experiences with historical GIS and cartography) to represent uncertainty and vagueness in a simple form in GIS. Most notably, boundaries were stored with a general sense of width, ranging from modern-looking, legally defined lines to broad frontier zones that were dozens or even hundreds of miles wide, that were only vaguely defined and/or only loosely controlled. Using an algorithm of GIS analysis tools, this dataset is automatically transformed into a fuzzy set estimation of Territoriality, then visualized cartographically so that each state (or even different portions of each state) appear more or less "fuzzy." The net effect is that map readers get a rather complete view of a pre-Eurocentric World, but also get a rather honest view of where we have more or less knowledge of that world.

No extended abstract or paper available

 Presented in Session 207. Advancing Spatial Methods