The use of remote sensing in landscape and social reconstruction

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An interdisciplinary and international team of researchers, led by the University of Florida, will conduct research on the history of land use and landscape resilience under different land use regimes and settlement patterns in the Maya lowlands of southern Mexico. Specifically focused on terraced landscapes, the scientists will investigate how key cultural (e.g., population density), ecological (e.g., soil and topography), and climatological (e.g., annual precipitation) factors influence changing patterns of agrarian land use. Previous research has documented discrete systems of terracing in parts of the lowlands, importantly demonstrating that these landscapes were sometimes intensively curated and cultivated. Combining soil science, paleoethnobotany, remote sensing, and archaeology with existing "big environmental data" (LiDAR surveys of Above Ground Carbon Storage), the research will investigate these agrarian systems across ecologies and settlement patterns, critically evaluating the resilience of these systems across the Maya lowlands. Are terraces constructed only in response to population pressure? Why are terraces built in particular regions? Why do they endure in certain ecological settings and not in others? Does terracing in the lowlands increase local landscape resilience? Do communities maintain terrace systems once they are built? Throughout the world, questions of landscape resilience, especially related to smallholder agriculture are vitally important to address, so that we can better design, plan, organize and maintain systems that are resilient to cultural and ecological change. This project fosters international collaborations and provides research opportunities for enhancing student engagement.The project will investigate the long-term landscape impacts of increasing agricultural intensity in the Maya lowlands of southern Mexico. It will inventory and analyze remote sensing (LiDAR) transects extending from the states of Chiapas north to Yucatan and Quintana Roo. Originally collected for environmental purposes as part of the REDD+ carbon inventory of southern Mexico, these surveys offer a uniquely expansive survey of human modified landscapes and landscape resilience. Specifically, it will explore how the form and spatial distribution of Pre-Columbian intensive agricultural modifications of the landscape are influenced by settlement density. The research will also study the influence of local environmental variability on the form and distribution of terracing. To address these questions, the team will process, analyze, inventory, and annotate existing LiDAR transects from across the Maya lowlands. This information will be combined with regional environmental data, excavation, soil profiles, and new high precision UAV LiDAR field surveys in order to evaluate land use intensity and land use change. The project will develop new methods and metrics for studying agrarian systems and agrarian change through time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.