Cutting-Edge Technologies Transforming Modern Archaeology
Dronícola digital twin of Neolithic arrowhead showing its wire-frame and full render views. Image by Dronícola

Cutting-Edge Technologies Transforming Modern Archaeology

Introduction

Archaeology, the study of human history through the excavation of sites and analysis of artifacts, has always been a discipline deeply rooted in manual labor and meticulous documentation. However, the advent of digital technologies has brought about a revolution in the field, helping archaeologists overcome numerous challenges. This article explores how both traditional and emerging digital technologies are transforming archaeology with recent real-life examples of successful implementation.

Geographic Information Systems (GIS)

Geographic Information Systems (GIS) are indispensable in modern archaeology. GIS technology facilitates the spatial analysis and visualization of archaeological sites, enabling researchers to manage and interpret large datasets related to site locations and artifact distributions. For instance, in Catamarca, Argentina, the use of mobile GIS has transformed field recording, allowing archaeologists to efficiently gather and analyze spatial data on-site (Fábrega-álvarez & Lynch, 2022 ).

Figure 6. Reviewing information in the QField app: navigation and editing tasks

Reality Capture

Reality capture technologies, including 3D modelling, photogrammetry, and LiDAR, are transforming how archaeologists document and analyze sites and artifacts.

Photogrammetry techniques like Structure from Motion (SfM) allow the creation of detailed 3D models from photographs. My team and I at Dronícola have created photogrammetry models of several important archeological assets in Spain including the Dolmen of Lácara and the Necropolis of Santa Maria de Tejuela .

Digital twin of the Dolmen of Lácara integrated into the GIS terrain model. Image by Dronícola.


LiDAR technology uses laser scanning to produce high-resolution topographic maps, even beneath vegetation cover. For instance, in the analysis of the Muaro Jambi site, a significant center of the ancient Sriwijaya civilization in Indonesia, airborne LiDAR data revealed previously undetected structures, providing valuable insights into the site's extent and organization (Haryuatmanto, G., 2023 )

Figure 11. Visualization of Kutomahligai; a) Aerial photo, b) DSM, c) DTM

Digital Archives and Databases

Digital archives and databases are critical for the storage, sharing, and analysis of archaeological data. These repositories facilitate collaborative research, ensure long-term preservation of data, and make archaeological information accessible to a wider audience.

At the Paliambela Kolindros Project in Greece, the integration of 3D digital documentation into long-term excavation archives has facilitated better data preservation and reprocessing. This project exemplifies how digital archives can enhance the documentation and accessibility of archaeological findings (Katsianis et al., 2021 ).

Fig. 10. Visualization of excavation data in 3D GIS

Artificial Intelligence (AI) and Machine Learning

Artificial Intelligence (AI) and machine learning are increasingly used in archaeology for pattern recognition, predictive modeling, and data analysis. An innovative example is the use of a deep-learning model for predictive archaeology and archaeological community detection. This model, developed by Resler et al. (2021), leverages AI to analyze large datasets, improving the identification and understanding of archaeological sites and communities. The model has demonstrated significant potential in enhancing archaeological surveys and research (Resler, Yeshurun, Natalio et al., 2021 ).

Fig. 1 A schematic representation of the machine learning-based workflow.

Unmanned Aerial Vehicles (UAVs)

Unmanned Aerial Vehicles (UAVs), or drones, equipped with cameras and sensors provide high-resolution aerial imagery and 3D mapping of archaeological sites. In Greece, the use of UAV photogrammetry at the Thessaloniki Toumba Excavation has produced accurate digital surface models and photo-realistic 3D outputs of archaeological trenches (Stamnas et al., 2021 ).

Figure 8. Overview of the GCPs and the aerial image data after image orientation.

Virtual Reality (VR) and Augmented Reality (AR)

Virtual Reality (VR) and Augmented Reality (AR) technologies create immersive experiences that allow researchers and the public to virtually explore archaeological sites and artifacts. The integration of these technologies in archaeology has been demonstrated in projects such as the scan-to-HBIM-to-XR method used for the Tomb of Caecilia Metella and Caetani Castle in Rome, Italy. This project combines 3D modeling, digital survey techniques, and extended reality (XR) development platforms to provide innovative and immersive learning experiences (Banfi et al., 2022 ).

Figure 10. The Scan-to-BIM model, reconstruction and XR experience of Caecilia Metella and Caetani Castrum

Remote Sensing and Satellite Imagery

Remote sensing and satellite imagery are essential for large-scale landscape archaeology. Integrating these technologies with UAVs and ground-based geophysics has proven effective in exploring pre-modern land use. A review of this integration in Northeastern Iraq highlighted how combining satellite remote sensing, UAVs, and geophysics can uncover significant details about past human activities and land use patterns (Laugier & Casana, 2021 ).

Figure 3. Systematic 1 km2 survey area of the Upper Diyala/Sirwan region.

Cloud Computing

Cloud computing platforms support the storage and analysis of large datasets, facilitating real-time data access and collaboration among researchers globally. An example is the ARK-BIM platform, an open-source cloud-based Historic Building Information Modelling (HBIM) solution for archaeology. This platform, based on the BIMData environment, enhances the management and exchange of archaeological data by providing tools for online documentation, collaboration, communication, and accessibility (Diara & Rinaudo, 2021 ).

Figure 3. ARK-BIM main framework idea.

Computational Photography

Computational photography techniques enhance archaeological documentation and analysis by capturing fine details and textures that are often invisible to the naked eye. For instance, high-resolution digital photography combined with image processing algorithms has been used at the Kaymak?? Archaeological Project (KAP) to document intricate details of artifacts, providing new insights into their craftsmanship and use (Scott et al., 2021 ).

Conclusion

The integration of traditional and emerging digital technologies is revolutionizing archaeology, helping to overcome numerous challenges in the field. From enhancing data management and analysis to improving public engagement and interdisciplinary collaboration, these technologies are making archaeology more efficient, accurate, and accessible.

As digital tools continue to evolve, they will undoubtedly open new horizons for archaeological research and discovery, making the field more efficient, accurate, and accessible. These technological advancements enrich our understanding of the past while ensuring that cultural heritage is preserved for future generations. The future of archaeology lies in the continued integration and innovation of digital technologies, fostering a deeper connection between humanity's history and its future.

References

Fábrega-álvarez, P., & Lynch, J. (2022). Archaeological Survey Supported by Mobile GIS: Low-Budget Strategies at the Hualfín Valley (Catamarca, Argentina). Advances in Archaeological Practice. https://doi.org/10.1017/aap.2022.2 .

Haryuatmanto, G. (2023). Analysis of Airborne LiDAR Data for Archaeology Study Case: Sriwijaya Muaro Jambi Site. IOP Conference Series: Earth and Environmental Science, 1127, 012012. https://doi.org/10.1088/1755-1315/1127/1/012012 .

Katsianis, M., Kotsakis, K., & Stefanou, F. (2021). Reconfiguring the 3D excavation archive. Technological shift and data remix in the archaeological project of Paliambela Kolindros, Greece. Journal of Archaeological Science: Reports, 36, 102857. https://doi.org/10.1016/j.jasrep.2021.102857 .

Resler, A., Yeshurun, R., Natalio, F. et al. A deep-learning model for predictive archaeology and archaeological community detection. Humanit Soc Sci Commun 8, 295 (2021). https://doi.org/10.1057/s41599-021-00970-z

Stamnas, A., Kaimaris, D., Georgiadis, C., & Patias, P. (2021). Comparing 3D Digital Technologies for Archaeological Fieldwork Documentation: The Case of Thessaloniki Toumba Excavation, Greece. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVI-M-1, 713-720. https://doi.org/10.5194/isprs-archives-XLVI-M-1-2021-713-2021 .

Banfi, F., Brumana, R., Roascio, S., Previtali, M., Roncoroni, F., Mandelli, A., & Stanga, C. (2022). 3D Heritage Reconstruction and Scan-to-HBIM-to-XR Project of the Tomb of Caecilia Metella and Caetani Castle, Rome, Italy. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVI-2/W1, 49-56. https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-49-2022 .

Laugier, E.J., & Casana, J. (2021). Integrating Satellite, UAV, and Ground-Based Remote Sensing in Archaeology: An Exploration of Pre-Modern Land Use in Northeastern Iraq. Remote Sensing, 13(24), 5119. https://doi.org/10.3390/rs13245119 .

Diara, F., & Rinaudo, F. (2021). ARK-BIM: Open-Source Cloud-Based HBIM Platform for Archaeology. Applied Sciences, 11(18), 8770. https://doi.org/10.3390/app11188770 .

Howland, M. D., & Kuester, F. (2021). Born-Digital Logistics: Impacts of 3D Recording on Archaeological Workflow, Training, and Interpretation. Heritage, 4(2), 832-847. https://doi.org/10.3390/heritage4020047 .



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