Radiocarbon ((14)C) provides a way to date material that contains carbon with an age up to ~50,000 years and is also an important tracer of the global carbon cycle. However, the lack of a comprehensive record reflecting atmospheric (14)C prior to 12.5 thousand years before the present (kyr B.P.) has limited the application of radiocarbon dating of samples from the Last Glacial period. Here, we report (14)C results from Lake Suigetsu, Japan (35°35'N, 135°53'E), which provide a comprehensive record of terrestrial radiocarbon to the present limit of the (14)C method. The time scale we present in this work allows direct comparison of Lake Suigetsu paleoclimatic data with other terrestrial climatic records and gives information on the connection between global atmospheric and regional marine radiocarbon levels.

Highlights:  First detailed Holocene cryptotephra study in a productive volcanic arc setting  Integrated Holocene tephrostratigraphic record of key East Asian isochrons  Improved chronology of many widespread Holocene tephra layers  New constraints on volcanism from back-arc volcanoes (Changbaishan & Ulleungdo)  Reveals isochrons than can be used to synchronise to the SG14 record

Abstract:The successful analysis of LiDAR data for archaeological research requires an evaluation of effects of different vegetation types and the use of adequate visualization techniques for the identification of archaeological features. The Ceibal-Petexbatun Archaeological Project conducted a LiDAR survey of an area of 20 × 20 km around the Maya site of Ceibal, Guatemala, which comprises diverse vegetation classes, including rainforest, secondary vegetation, agricultural fields, and pastures. We developed a classification of vegetation through object-based image analysis (OBIA), primarily using LiDAR-derived datasets, and evaluated various visualization techniques of LiDAR data. We then compared probable archaeological features identified in the LiDAR data with the archaeological map produced by Harvard University in the 1960s and conducted ground-truthing in sample areas. This study demonstrates the effectiveness of the OBIA approach to vegetation classification in archaeological applications, and suggests that the Red Relief Image Map (RRIM) aids the efficient identification of subtle archaeological features. LiDAR functioned reasonably well for the thick rainforest in this high precipitation region, but the densest parts of foliage appear to create patches with no or few ground points, which make the identification of small structures problematic.

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