Machine learning-ready remote sensing data for Maya archaeology.

In our study, we set out to collect a multimodal annotated dataset for remote sensing of Maya archaeology, that is suitable for deep learning. The dataset covers the area around Chactún, one of the largest ancient Maya urban centres in the central Yucatán Peninsula. The dataset includes five types of data records: raster visualisations and canopy height model from airborne laser scanning (ALS) data, Sentinel-1 and Sentinel-2 satellite data, and manual data annotations.

Archaeological landscape, settlement dynamics, and sociopolitical organization in the Chactún area of the central Maya Lowlands.

Until recently, an extensive area in the central lowlands of the Yucatán peninsula was completely unexplored archaeologically. In 2013 and 2014, during initial surveys in the northern part of the uninhabited Calakmul Biosphere Reserve in eastern Campeche, Mexico, we located Chactún, Tamchén and Lagunita, three major Maya centers with some unexpected characteristics. Lidar data, acquired in 2016 for a larger area of 240 km2, revealed a thoroughly modified and undisturbed archaeological landscape with a remarkably large number of residential clusters and widespread modifications related to water management and agriculture.