A UAS lidar case study in the archaeological landscape of ancient Halos, Greece

This paper presents the technical, methodological, and preliminary archaeological results of the Unmanned Aerial System (UAS) lidar experiments at the archaeological landscape of ancient Halos. The main elements of this landscape consist of various archaeological remains related to human burial, habitation, fortification, and related infrastructure, from the Neolithic onwards, with a current research focus on the Late Bronze/Early Iron Age up to the Classical/Hellenistic period. The dimensions, preservation, diversity, richness, and connectedness of archaeological features in the area render UAS remote sensing an important complement to more traditional fieldwork methods such as survey and excavation for studying the archaeological landscape. In this context, various Unmanned Aerial Systems (UAS)-based data collection campaigns have been organized, both using more traditional methods and sensors as well as doing experimental research with less established technologies, such as beyond-visible-light spectrometry. This paper focuses on the collection of lidar data from various parts of the area. We critically evaluate the relatively low-budget approach in terms of its efficiency, approaches to data acquisition, comparison with other methods, and data processing workflow. In addition, we share and discuss several preliminary observations and their impact on the archaeological-historical understanding of the area. The results show that the utilization of UAS lidar in the archaeological landscape of ancient Halos has demonstrated significant utility for both technical and methodological investigations, as well as for the generation of valuable archaeological insights. Nonetheless, it is apparent that considerable opportunities remain for further refinement of the data acquisition, processing, and analytical workflows, as well as the development of further comparative frameworks that incorporate various UAS lidar configurations, alongside lidar datasets obtained from alternative platforms, such as aircraft. In this context, promoting interdisciplinary dialogue, facilitating the exchange of expertise, and sharing data—including the publication of findings and the archiving of both raw and metadata—are crucial for advancing the field.