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Titien Bartette from ICONEM gives a brief review of key technologies used in remote site monitoring to prevent looting and document endangered sites, assessing their contributions, unique features, and applicability.
The preservation of archaeological sites is vital for understanding our shared history, yet these sites frequently face threats from looting and illicit activities. To address this, modern technologies provide advanced methods for monitoring, detecting, characterizing, and interpreting disturbances at these sites. This review explores the key technologies used in remote site monitoring to prevent looting and document endangered archaeological sites. We will assess the contribution, unique features, and applicability of each technology, and emphasize their complementarity to highlight the significance of these technological advancements for preserving global heritage. By embracing these technologies, the archaeological community can better protect our cultural heritage from the dangers of looting and illicit trafficking.
Photogrammetry
Description: Photogrammetry involves creating detailed 3D models of archaeological sites using photographs taken from various angles. This method allows for high-resolution documentation of site conditions over time, facilitating the detection of even minor changes. By capturing the physical state of sites before and after suspected looting activities, photogrammetry can reveal disturbances and unauthorized excavations.
Pertinence: Photogrammetry is particularly effective for producing accurate and detailed records that can be compared over time to identify changes. Its ability to document precise site conditions makes it invaluable for tracking and analyzing looting incidents.
Complementarity: This method complements other technologies like satellite imagery by providing detailed ground-level views that can corroborate larger-scale data.
Example of a remote analysis by Iconem of a looted site using photogrammetry and Earth Observation (EO): the Palace of Khorsabad in Iraq (UNESCO - Japanese Funds-in-Trust - Iconem).
LiDAR (Light Detection and Ranging)
Description: LiDAR uses laser scanning to create precise, high-resolution topographic maps. By emitting laser pulses and measuring the reflected signals, LiDAR can detect surface variations and disruptions. This technology is particularly useful in identifying subtle changes in terrain that may indicate looting activities, such as trenches or pits that are not immediately visible.
Pertinence: LiDAR's ability to penetrate vegetation and detect fine topographic changes makes it a powerful tool for monitoring sites in forested or otherwise covered areas. Its high precision aids in identifying small-scale disturbances that might go unnoticed with other methods.
Complementarity: LiDAR data can be integrated with photogrammetric models and GIS to provide a comprehensive view of site conditions and disturbances.
Satellite Imagery
Description: Satellite imagery involves capturing images of the Earth's surface from orbiting satellites. High-resolution satellite images allow for the monitoring of archaeological sites over large areas, making it possible to detect changes and anomalies indicative of looting activities. Techniques such as multi-temporal analysis enable the tracking of site conditions over time.
Pertinence: Satellite imagery provides extensive coverage and the ability to monitor remote or inaccessible sites. The frequent revisits by satellites allow for regular updates on site conditions, making it possible to quickly identify and respond to looting.
Complementarity: This technology works well with ground-based methods like photogrammetry and LiDAR, providing a broad overview that can be followed up with more detailed local investigations.
Spatial Archival photopositioning (declassified military photos, aerial coverage, archival collections from archaeological campaigns...)
Description: This method uses historical photographs, often taken for military or archaeological purposes, to compare past and present conditions of archaeological sites. By analyzing these photos, researchers can identify changes and signs of looting over time.
Pertinence: Archive photography is a valuable resource for understanding the long-term changes at archaeological sites. It helps in establishing a historical baseline against which recent activities can be measured.
Complementarity: These historical records provide context and background, enhancing the interpretation of current data from photogrammetry, LiDAR, and satellite imagery.
Machine Learning and Artificial Intelligence
Description: AI and machine learning algorithms process and analyze large datasets to identify patterns and anomalies associated with looting. These technologies can automatically detect and classify features in satellite images, photogrammetric models, and other data sources, improving the speed and accuracy of monitoring efforts.
Pertinence: Machine learning and AI are crucial for handling the vast amounts of data generated by modern remote sensing technologies. They enhance the ability to detect looting quickly and with high precision, making it possible to respond more effectively.
Complementarity: These algorithms can integrate data from various sources, including photogrammetry, LiDAR, and satellite imagery, to provide comprehensive and actionable insights.
Geographic Information Systems (GIS)
Description: GIS integrates spatial data from various sources to analyze and visualize archaeological sites. This technology allows for the comprehensive management of site information, including historical data, current conditions, and potential risks.
Pertinence: GIS is essential for mapping and analyzing spatial relationships, helping to identify areas at risk of looting. It provides a platform for combining and analyzing data from different technologies, enhancing the overall understanding of site conditions.
Complementarity: GIS acts as a central hub, integrating data from photogrammetry, LiDAR, satellite imagery, and other methods to create a complete picture of archaeological sites.
Case Studies and Recent Projects
The Afghan Heritage Mapping Project (AHMP):
Coordinator: Institute for the Study of Ancient Cultures - The University of Chicago. Andrew Wright (Project Manager)
Objectives: Document all archaeological sites in Afghanistan using GIS, monitor looting, and integrate heritage protection into development projects.
Technologies Used: Satellite imagery, GIS-based documentation, and remote sensing.
Identification of Looting Activities on Earth Observation Data & Detection of Archaeological Sites on Earth Observation Data :
Coordinator: Centre for Cultural Heritage Technology (CCHT@Ca' Foscari) of the Italian Institute of Technology (IIT)
Example: Project aiming to develop self-supervised deep learning methods to automatically identify sub-surface cultural heritage sites and semi-supervised techniques to detect illegal looting activities.
Technologies Used: Earth Observcation (EO), GIS-based information, Self-supervised deep learning architectures, and change detection.
Iconem's Approach in the Anchise Project:
Focus: Combining satellite imagery and 3D surveys to monitor and protect archaeological sites. Providing a platform that enables advanced visualisation and data analysis of both 3D point clouds and satellite data, advancing interoperability between them and creating a synergistic approach that leverages the strengths of both technologies.
Methods: Multiscale 3D digitization, earth observation technologies, integrated analytical documentation, on-site capacity building.
References:
Altaweel, M., Khelifi, A., & Shana’ah, M. M. (2024). Monitoring Looting at Cultural Heritage Sites: Applying Deep Learning on Optical Unmanned Aerial Vehicles Data as a Solution. Social Science Computer Review, 42(2), 480-495. https://doi.org/10.1177/08944393231188471
Boyoğlu, C. S., Balz, T., and Sultanbekova, A.: Assessing Looting Holes by Using SAR Simulation, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 31–36, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-31-2024, 2024
Carvajal-Ramírez, F., Navarro, A. D., Agüera-Vega, F., Martínez-Carricondo, P., Mancini, F. : Virtual Reconstruction of Damaged Archaeological Sites based on Unmanned Aerial Vehicle Photogrammetry and 3D Modelling. Study Case of a Southeastern Iberia Production Area in the Bronze Age. Measurement. 136. 225-236. https://doi.org/10.1016/j.measurement.2018.12.092, 2019.
Kersel, M.M. and Hill, A. (Chad): The (W)Hole Picture: Responses to a Looted Landscape, International Journal of Cultural Property, 26(3), pp. 305–329. https://doi.org/10.1017/S0940739119000195, 2019.
Lasaponara, R., Leucci, G., Masini, N., Persico, R.: Investigating archaeological looting using satellite images and GEORADAR: The experience in Lambayeque in North Peru. Journal of Archaeological Science. 42. 216–230, https://doi.org/10.1016/j.jas.2013.10.032, 2014.
Richason III, B.: Techniques of detecting and delineating archaeological site destruction using high resolution satellite imagery: An iraq case study. American Society for Photogrammetry and Remote Sensing Annual Conference 2011. 426-436, 2011.
Tapete D, Cigna F. Detection of Archaeological Looting from Space: Methods, Achievements and Challenges. Remote Sensing. 2019; 11(20):2389. https://doi.org/10.3390/rs11202389
Vavulin, M., Chugunov, K., Zaitceva, O., Vodyasov, E., Pushkarev, A.: UAV-based photogrammetry: Assessing the application potential and effectiveness for archaeological monitoring and surveying in the research on the ‘Valley of the Kings’ (Tuva, Russia). Digital Applications in Archaeology and Cultural Heritage. 20. e00172, https://doi.org/10.1016/j.daach.2021.e00172, 2021.
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