Abstract
Settlement research in the Maya lowlands has struggled to reconcile its goals to model a tropical forest civilization in ecological terms with the logistical constraints imposed by the forest itself. In this paper, we argue that the methodological challenges facing settlement research in this tropical lowland setting limited researchers’ confidence in the representativeness of their data, nudging the discipline toward community-scale analysis and away from quantitative macro-scale settlement pattern research. As a result, many basic facts of human geography have remained unsettled. These challenges can now be overcome thanks to advances in remote sensing. Here, we use lidar-derived settlement and topographic data from the Corona-Achiotal region of northwestern Guatemala to develop a settlement suitability model that reveals patterns in the distribution of archaeological remains vis-à-vis landforms. Applying this model to a much larger published settlement dataset, we demonstrate how it is not only widely applicable in the interior Maya Lowlands, but also capable of identifying historical contingencies in the distribution of settlement, namely the crowding of less-suitable areas of the landscape, linked to urban densification.
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