Airborne Lidar Survey, Density-Based Clustering, and Ancient Maya Settlement in the Upper Usumacinta River Region of Mexico and Guatemala

Remote Sensing · 2021 · 27 citations

• Archaeology
• Geography
• Physical geography

We present results from the archaeological analysis of 331 km2 of high-resolution airborne lidar data collected in the Upper Usumacinta River basin of Mexico and Guatemala. Multiple visualizations of the DEM and multi-spectral data from four lidar transects crossing the Classic period (AD 350–900) Maya kingdoms centered on the sites of Piedras Negras, La Mar, and Lacanja Tzeltal permitted the identification of ancient settlement and associated features of agricultural infrastructure. HDBSCAN (hierarchical density-based clustering of applications with noise) cluster analysis was applied to the distribution of ancient structures to define urban, peri-urban, sub-urban, and rural settlement zones. Interpretations of these remotely sensed data are informed by decades of ground-based archaeological survey and excavations, as well as a rich historical record drawn from inscribed stone monuments. Our results demonstrate that these neighboring kingdoms in three adjacent valleys exhibit divergent patterns of structure clustering and low-density urbanism, distributions of agricultural infrastructure, and economic practices during the Classic period. Beyond meeting basic subsistence needs, agricultural production in multiple areas permitted surpluses likely for the purposes of tribute, taxation, and marketing. More broadly, this research highlights the strengths of HDBSCAN to the archaeological study of settlement distributions when compared to more commonly applied methods of density-based cluster analysis.

UAV LiDAR Survey for Archaeological Documentation in Chiapas, Mexico

Remote Sensing · 2021 · 25 citations

• Computer Science
• Remote sensing
• Geography

Airborne laser scanning has proven useful for rapid and extensive documentation of historic cultural landscapes after years of applications mapping natural landscapes and the built environment. The recent integration of unoccupied aerial vehicles (UAVs) with LiDAR systems is potentially transformative and offers complementary data for mapping targeted areas with high precision and systematic study of coupled natural and human systems. We report the results of data capture, analysis, and processing of UAV LiDAR data collected in the Maya Lowlands of Chiapas, Mexico in 2019 for a comparative landscape study. Six areas of archaeological settlement and long-term land-use reflecting a diversity of environments, land cover, and archaeological features were studied. These missions were characterized by areas that were variably forested, rugged, or flat, and included pre-Hispanic settlements and agrarian landscapes. Our study confirms that UAV LiDAR systems have great potential for broader application in high-precision archaeological mapping applications. We also conclude that these studies offer an important opportunity for multi-disciplinary collaboration. UAV LiDAR offers high-precision information that is not only useful for mapping archaeological features, but also provides critical information about long-term land use and landscape change in the context of archaeological resources.

The lowland Maya settlement landscape: Environmental LiDAR and ecology

Journal of Archaeological Science Reports · 2020 · 37 citations

• Computer Science
• Ecology
• Geography

This paper presents the archaeological evaluation of 458 tiles of LiDAR collected by environmental scientists over southern Mexico using the G-LiHT system of NASA’s Goddard Space Flight Center. Specifically, this article describes the results of a full processing, inspection, and annotation of these data for the identification and baseline analysis of archaeological features. In this paper, we: 1) introduce the dataset and describe our efforts to systematically process and annotate archaeological features and 2) revisit the cultural and ecological context of the samples. The results presented here confirm some of the conclusions presented previously, including the benefit of mining large previously acquired digital data for archaeological information, the diversity of lowland settlement and features in between areas already well-documented, and the contribution to landscape archaeology of such transect samples when coupled to macro-environmental data sets. These data also fill in some details about the prehispanic Mesoamerican landscape, raising new questions about the relationship between past settlements and regional cultural, political, and ecological systems. Finally, these data offer important foundational inventories for discussing how to preserve and conserve archaeological resources across the lowlands, especially when these resources are not tied to monumental architecture.