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Research at the Selin Farm site in northeastern Honduras examined changing cultural landscapes in a region whose prehistory is poorly understood. Low-impact field methods and radiocarbon dates reveal how this cultural landscape changed in response to shifting priorities among its inhabitants from a.d. 300–1000. We found evidence for rapid accumulation of deposits beginning around a.d. 600, when the site nearly doubled in size over the span of just decades, before retracting again within a few centuries. Although it was caught up in some of the broader social and political changes that began around a.d. 600 throughout northern Honduras and southern Mesoamerica, the longevity of this site suggests stability of the cultural and ecological systems in which it was embedded until the final centuries of occupation. Well-preserved, long-term deposits make Selin Farm an ideal location in which to explore entangled processes of environmental and social change in the little-known small-scale societies of Central America. 

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. 

We report on a large area of ancient Maya wetland field systems in Belize, Central America, based on airborne lidar survey coupled with multiple proxies and radiocarbon dates that reveal ancient field uses and chronology. The lidar survey indicated four main areas of wetland complexes, including the Birds of Paradise wetland field complex that is five times larger than earlier remote and ground survey had indicated, and revealed a previously unknown wetland field complex that is even larger. The field systems date mainly to the Maya Late and Terminal Classic (∼1,400–1,000 y ago), but with evidence from as early as the Late Preclassic (∼1,800 y ago) and as late as the Early Postclassic (∼900 y ago). Previous study showed that these were polycultural systems that grew typical ancient Maya crops including maize, arrowroot, squash, avocado, and other fruits and harvested fauna. The wetland fields were active at a time of population expansion, landscape alteration, and droughts and could have been adaptations to all of these major shifts in Maya civilization. These wetland-farming systems add to the evidence for early and extensive human impacts on the global tropics. Broader evidence suggests a wide distribution of wetland agroecosystems across the Maya Lowlands and Americas, and we hypothesize the increase of atmospheric carbon dioxide and methane from burning, preparing, and maintaining these field systems contributed to the Early Anthropocene. 

Abstract Surface rupture from the 2019 Ridgecrest earthquake sequence, initially associated with the Mw 6.4 foreshock, occurred on 4 July on a ∼17  km long, northeast–southwest-oriented, left-lateral zone of faulting. Following the Mw 7.1 mainshock on 5 July (local time), extensive northwest–southeast-oriented, right-lateral faulting was then also mapped along a ∼50  km long zone of faults, including subparallel splays in several areas. The largest slip was observed in the epicentral area and crossing the dry lakebed of China Lake to the southeast. Surface fault rupture mapping by a large team, reported elsewhere, was used to guide the airborne data acquisition reported here. Rapid rupture mapping allowed for accurate and efficient flight line planning for the high-resolution light detection and ranging (lidar) and aerial photography. Flight line planning trade-offs were considered to allocate the medium (25 pulses per square meter [ppsm]) and high-resolution (80 ppsm) lidar data collection polygons. The National Center for Airborne Laser Mapping acquired the airborne imagery with a Titan multispectral lidar system and Digital Modular Aerial Camera (DiMAC) aerial digital camera, and U.S. Geological Survey acquired Global Positioning System ground control data. This effort required extensive coordination with the Navy as much of the airborne data acquisition occurred within their restricted airspace at the China Lake ranges. 

Este trabajo propone un método de muestreo a fin de contrastar en el terreno los datos obtenidos a partir de imágenes LiDAR, que permitan al investigador verificar y/o predecir la precisión de los resultados sobre un área mayor. El estudio de caso aquí presentado se centra en el sitio de Yaxnohcah, ubicado en la Meseta Cárstica Central de la península de Yucatán. Está área se caracteriza por presentar una variedad de densos bosques tropicales húmedos y zonas de vegetación de humedal con pocos accesos de caminos y brechas. Para este estudio se seleccionaron veintiún bloques de 100 por 100 metros del área, que comprendió una muestra estratificada del 10 por ciento, e incluyeron ejemplos de varias zonas de vegetación distinta. Se realizó un recorrido de superficie por transectos a lo largo de los bloques, registrándose dos tipos de errores. Los Errores del Tipo 1 consisten de rasgos culturales identificados en campo, pero que no aparecen en el los Modelos Digital de Elevación (MDE) o en el Modelo de Superficie Digital (MSE). Los Errores de Tipo 2 consisten en rasgos que parecen culturales en el MDE o MSE, pero que en realidad son causadas por diferentes tipos de vegetación. De manera concurrente, realizamos un extenso reconocimiento de la vegetación en cada bloque, identificando las principales especies presentes, las diferentes alturas de dosel, así como las características generales de la topografía y los suelos. Los resultados del método de contrastación en el terreno demuestran que los datos lidar son sumamente confiables y es posible utilizar una muestra a fin de evaluar la precisión, la veracidad y la certidumbre de los datos sobre un área mayor.