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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.

Constructed landscapes are composed of diverse communities, representing different social strata and perspectives of a place. In turn, the risks associated with inhabiting unpredictable environments are disproportionately felt across urban and rural landscapes. The mitigation and management of risks often fall on farming and smallholder communities, influencing decentralized strategies. These themes are explored in an archaeological context surrounding the confluence of the Upper Usumacinta and Lacantún Rivers in the neotropical Maya lowlands of Chiapas, Mexico. LiDAR data collected recently with the GatorEye unoccupied aerial vehicle (UAV) and NASA’s GLiHT system have aided in the mapping of the archaeological urban centre of Benemérito de las Américas, Primera Sección and the surrounding landscape. These data have revealed coupled settlement with land management, in the form of wetland fields, reservoirs, and riverways, emphasizing the interconnectivity of household practice and land use in the region.

En este trabajo describimos los resultados del uso de tecnología lidar en drones en el área Maya entre junio del 2017 y 2018. Nuestro objetivo es desarrollar métodos, procedimientos y estándares apropiados para el uso de lidar en drones en el mapeo de asentamientos antiguos. Se sobrevolaron tres sitios dentro de la región superior del río Usumacinta: Piedras Negras en Guatemala, Budsilha y El Infiernito en México. Estos sitios representan una gama de contextos naturales y culturales ideales para evaluar las aplicaciones de la tecnología lidar en el campo. Los modelos de elevación digital y de superficie digital muestran la utilidad del uso de drones en el área Maya. Esta tecnología es apropiada y rentable para el trabajo de campo, pero aún requiere de una detallada planificación y evaluación de las muestras. Futuros estudios evaluarán métodos y técnicas para filtrar y procesar estos datos.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.