Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization.

The peoples of southern Mesoamerica, including the Classic period Maya, are often claimed to exhibit a distinct type of spatial organization relative to contemporary urban systems. Here, we use the settlement scaling framework and properties of settlements recorded in systematic, full-coverage surveys to examine ways in which southern Mesoamerican settlement systems were both similar to and different from contemporary systems. We find that the population-area relationship in these settlements differs greatly from that reported for other agrarian settlement systems, but that more typical patterns emerge when one considers a site epicenter as the relevant social interaction area, and the population administered from a given center as the relevant interacting population. Our results imply that southern Mesoamerican populations mixed socially at a slower temporal rhythm than is typical of contemporary systems. Residential locations reflected the need to balance energetic and transport costs of farming with lower-frequency costs of commuting to central places. Nevertheless, increasing returns in activities such as civic construction were still realized through lower-frequency social mixing. These findings suggest that the primary difference between low-density urbanism and contemporary urban systems lies in the spatial and temporal rhythms of social mixing.

Inequality is present to varying degrees in all human societies, pre-modern and contemporary. For archaeological contexts, variation in house size reflects differences in labor investments and serves as a robust means to assess wealth across populations small and large. The Gini coefficient, which measures the degree of concentration in the distribution of units within a population, has been employed as a standardized metric to evaluate the extent of inequality. Here, we employ Gini coefficients to assess wealth inequality at four nested socio-spatial scales–the micro-region, the polity, the district, and the neighborhood–at two medium size, peripheral Classic Maya polities located in southern Belize. We then compare our findings to Gini coefficients for other Classic Maya polities in the Maya heartland and to contemporaneous polities across Mesoamerica. We see the patterning of wealth inequality across the polities as a consequence of variable access to networks of exchange. Different forms of governance played a role in the degree of wealth inequality in Mesoamerica. More autocratic Classic Maya polities, where principals exercised degrees of control over exclusionary exchange networks, maintained high degrees of wealth inequality compared to most other Mesoamerican states, which generally are characterized by more collective forms of governance. We examine how household wealth inequality was reproduced at peripheral Classic Maya polities, and illustrate that economic inequity trickled down to local socio-spatial units in this prehispanic context.

In the past decade, Light Detection and Ranging (lidar) has fundamentally changed our ability to remotely detect archaeological features and deepen our understanding of past human-environment interactions, settlement systems, agricultural practices, and monumental constructions. Across archaeological contexts, lidar relief visualization techniques test how local environments impact archaeological prospection. This study used a 132 km² lidar dataset to assess three relief visualization techniques—sky-view factor (SVF), topographic position index (TPI), and simple local relief model (SLRM)—and object-based image analysis (OBIA) on a slope model for the non-automated visual detection of small hinterland Classic (250–800 CE) Maya settlements near the polities of Uxbenká and Ix Kuku’il in Southern Belize. Pedestrian survey in the study area identified 315 plazuelas across a 35 km² area; the remaining 90 km² in the lidar dataset is yet to be surveyed. The previously surveyed plazuelas were compared to the plazuelas visually identified on the TPI and SLRM. In total, an additional 563 new possible plazuelas were visually identified across the lidar dataset, using TPI and SLRM. Larger plazuelas, and especially plazuelas located in disturbed environments, are often more likely to be detected in a visual assessment of the TPI and SLRM. These findings emphasize the extent and density of Classic Maya settlements and highlight the continued need for pedestrian survey to ground-truth remotely identified archaeological features and the impact of modern anthropogenic behaviors for archaeological prospection. Remote sensing and lidar have deepened our understanding of past human settlement systems and low-density urbanism, processes that we experience today as humans residing in modern cities.

Long-entrenched grand narratives have tied inequality in large human aggregations to generally linear trends, a direct outcome of domestication, then fostered by population growth and/or stepped scalar transitions in the hierarchical complexity of human institutions. This general pattern has been argued to short-circuit or reverse only in the context of cataclysmic disasters or societal breakdowns. Yet, for the most part, these universal deterministic frameworks have been constructed from historical or ethnographic snapshots in time and afford little systematic attention to human institutions or agency. Here, we leverage quantitative, temporally defined archaeological, and ethnographic data from a suite of global regions, most of which transitioned through the process of urbanism and complex hierarchy formation, to examine shifts in degrees of inequality over time. Although broad temporal patterns are evidenced, the regional trends in inequality are neither linear, uniform, nor triggered immediately or mechanically by Malthusian dynamics or scalar increases.