This paper (Panagiotidis et al. 2024) discusses the digital approach to the ‘digital storyline’ of the Monastery of Brontochion of Mystras, Peloponnese, Greece. Using drone and terrestrial photogrammetric recording techniques, their goal is to produce maps and 3D models that will be integrated in the overall study of the medieval city, as well as function as a comprehensive visualisation of the archaeological site throughout its history. This will take shape as a web application using ArcGIS Online that will be a valuable platform presenting interactive visual information to accompany written publications. In addition, the assets in the database will be available for further advanced purposes, such as suggested by the authors; xR applications, educational games or digital smart guides. The authors of the paper do a good job in describing the historical background of the site and the purpose of the digital documentation techniques, and the applied methods and the technical details of the produced models are dealt with in detail.

The paper presents a compelling case for an integrative approach to using digital recording techniques at an architectonically complex site for Cultural Heritage Management. It can be placed in a series of studies discussing how monumental sites can benefit from advanced digital recording techniques such as those presented in this paper (see for example Waagen and Wijngaarden 2024). The paper is recommended as an interesting read for all who are involved in this field.

References

Panagiotidis V. Vayia, Valantou Vasiliki, Kazolias Anastasios, and Zacharias Nikolaos. (2024). At the Edge of a City: The Digital Storyline of the Brontochion Monastery of Mystras. Zenodo, 8126952, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8126952

Waagen, J., and van Wijngaarden, G. J. (2024). Understanding Archaeological Site Topography: 3D Archaeology of Archaeology. Journal of Computer Applications in Archaeology, 7(1), 237–243. https://doi.org/10.5334/jcaa.157 

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“3Duewelsteene - A website for the 3D visualization of the megalithic passage grave Düwelsteene near Heiden in Westphalia, Germany” (Tharandt 2024) presents several 3-dimensional models of the Düwelsteene monument, along with contextual information about the grave and the process of creating the models. The website (https://3duewelsteene.github.io/) includes English and German versions, making it accessible to a wide audience. The website itself serves as the primary means of presenting the data, rather than as a supplement to a written text. This is an innovative and engaging way to present the research to a wider public.

Düwelsteene (“Devil’s Stones”) is a megalithic passage grave from the Funnel Beaker culture, dating to approximately 3300 BC. to 2600 BC. that was excavated in 1932. The website displays three separate 3-dimensional models. They ares shown in the 3D viewer software 3DHOP, which enables viewers to interact with the models in several ways, Annotations on the models display further information.

The first model was created by image-based modeling and shows the monument as it appears today.

A second model uses historical photographs and excavation data to reconstruct the grave as it appeared prior to the 1932 archaeological excavation. Restoration work following the excavation relocated many of the stones. Pre-1932 photographs collected from residents of the nearby town of Heiden were then used to create a model showing what the tomb looked like before the restoration work. It is commendable that a “certainty view” of the model shows the certainty with which the stones can be put at the reconstructed place. Gaps in the 3D models of stones that were caused by overlap with other stones have been filled with a rough mesh and marked as such, thereby differentiating between known and unknown parts of the stones.

The third model is the most imaginative and most interesting. As it shows as the grave as it might have appeared in approximately 3000 B.C., many aspects of this model are necessarily somewhat speculative. There is no direct evidence for exact size and shape of the capstones, the height of the mound, and other details. But enough is known about other similar constructions to allow these details to be inferred with some confidence. Again, care was taken to enable viewers to distinguish between the stones that are still in existence and those that were reconstructed.

A video on the home page of the website adds a nice touch. It starts with the model of the Düwelsteene as it currently appears then shows, in reverse order, the changes to the grave, ending with the inferred original state.

The 3D reconstructions are convincing and the methods well described. This project follows an open science approach and the FAIR principles, which is commendable and cutting edge in the field of Digital Archaeology. The preprint of the website hosted on zenodo includes all the photos, text, html files, and nine individual 3D model (.ply) files that are combined in the reconstructions exhibited on the website. A “readme.md” file includes details about building the models using CloudCompare and Blender, and modifications to the 3D viewer software (3DHOP) to get the website to improve the display of the reconstructions. We have to note that the link between the reconstructed models and the html page does not work when the files are downloaded from zenodo and opened offline. The html pages open in the browser, and the individual ply files work fine, but the 3D models do not display on the browser page when the html files are opened offline. The online version of the website is working perfectly.

The 3Düwelsteene website combines the presentation of archaeological domain knowledge to a lay audience as well as in-depths information on the reconstruction process to make it an interesting contribution for researchers. By providing data and code for the website it also models an Open Science approach, which enables other researchers to re-use these materials. We congratulate the author on a successful reconstruction of the megalithic tomb, an admirable presentation of the archaeological work and the thoughtful outreach to a broad audience.

Bibliography
Tharandt, L., 3Duewelsteene - A website for the 3D visualization of the megalithic passage grave Düwelsteene near Heiden in Westphalia, Germany, https://3duewelsteene.github.io/, Zenodo, 7948379, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7948379

This is a fascinating paper for anyone interested in network analysis or the chronology and cultures of the case study, namely the Late prehistoric burial sites in Dorset, for which the author’s approach allowed a new perspective over an already deeply studied area [1]. This paper's implementation of Similarity Network Fusion (SNF) is noteworthy. This method is typically utilized within genetic research but has yet to be employed in Archaeology. SNF has the potential to benefit Archaeology due to its unique capabilities and approach significantly. 

The author exhibits a deep and thorough understanding of previous investigations concerning material and similarity networks while emphasizing the innovative nature of this particular study. The SNF approach intends to improve a lack of the most used (in Archaeology) similarity coefficient, the Brainerd-Robinson, in certain situations, mainly in heterogenous and noisy datasets containing a small number of samples but a large number of measurements, scale differences, and collection biases, among other things. The SNF technique, demonstrated in the case study, effectively incorporates various similarity networks derived from different datatypes into one network. 

As shown during the Dorset case study, the SNF application has a great application in archaeology, even in already available data, allowing us to go further and bring new visions to the existing interpretations. As stated by the author, SNF shows its potential for other applications and fields in archaeology coping with similar datasets, such as archaeobotany or archaeozoology, and seems to complement different multivariate statistical approaches, such as correspondence or cluster analysis.

This paper has been subject to two excellent revisions, which the author mostly accepted. One of the revisions was more technical, improving the article in the metadata part, data availability and clarification, etc. Although the second revision was more conceptual and gave some excellent technical inputs, it focused more on complementary aspects that will allow the paper to reach a wider audience. I vividly recommend its publication.

References

[1] Geitlinger, T. (2024). Similarity Network Fusion: Understanding Patterns and their Spatial Significance in Archaeological Datasets. Zenodo, 7998239, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7998239

Diamanti et al. (2024) is a significant contribution to the field of underwater robotics and their use in archaeology, with an innovative approach to some major problems in the deployment of said technologies. It identifies issues when it comes to approaching Underwater Cultural Heritage (UCH) sites and does so through an interest in the combination of data, maneuverability, and the interpretation provided by the instruments that archaeologists operate. The article's motives are clear: it is not enough to find the means to reach these sites, but rather is fundamental to take a step forward in methodology and how we can safeguard certain aspects of data recovery with robust mission planning.

To this end, the article does not fail to highlight previous contributions, in an intertwined web of references that demonstrate the marked evolution of the use of Unmanned Underwater Vehicles (UUVs), Remote Operated Vehicles (ROVs), Autonomous Underwater Vehicles (AUVs) and Autonomous Surface Vehicles (ASVs), which are growing exponentially in use (see Kapetanović et al. 2020). It should be emphasized that the notion of ‘aquatic environment’ used here is quite broad and is not limited to oceanic or maritime environments, which allows for a larger perspective on distinct technologies that proliferate in underwater archaeology. There is also a relevant discussion on the typologies of sensors and how these autonomous vehicles obtain their data, where are debated Inertial Measurement Units (IMU) and LiDAR systems. 

Thus, the authors of this article propose the creation of a model that acquires data through simulations, which allows for a better understanding of what a real mission presupposes in the field. Their tripartite method - pre-mission planning; mission plan and post-mission plan - offers a performing algorithm that simplifies and provides reliability to all the parts of the intervention. The use of real cases to create simulation models allows for a substantial approximation to common practice in underwater environments. And yet, the article is at its most innovative status when it combines all the elements it sets out to explore. It could simply focus on the methodological or planning component, on obtaining data, or on theoretical problems. But it goes further, which makes this approach more complete and of interest to the archaeological community. By not taking any part as isolated, the problems and possible solutions arising from the course of the mission are carried over from one parameter to another, where details are worked upon and efficiency goals are set.

One of the most significant cases is the tuning of ocean optics in aquatic environments according to the idiosyncracies of real cases (Diamanti et al. 2024: 8), a complex endeavor but absolutely necessary in order to increase the informative potential of the simulation. The exploration of various data capture models is also welcome, for the purposes of comparison and adaptation on a case-by-case basis. The brief theoretical reflection offered at the end of the article dwells in all these points and problematizes the difference between terrestrial and aquatic archaeology. In fact, the distinction does not only exist in the technical component, as although it draws in theoretical elements from archaeology that is carried out on land (see Krieger 2012 for this matter), the problems and interpretations are shaped by different factors and therefore become unique (Diamanti et al 2024: 15). The future, according to the authors, lies in increasing the autonomy of these vehicles so that the human element does not have to make decisions in a systematic way. It is in that note, and in order for that path to become closer to reality, that we strongly recommend this article for publication, in conjunction with the comments of the reviewers. We hope that its integrated approach, which brings together methods, theories and reflections, can become a broader modus operandi within the field of underwater robotics applied to archaeology.

References:

Diamanti, E., Yip, M., Stahl, A. and Ødegård, Ø. (2024). Advancing data quality of marine archaeological documentation using underwater robotics: from simulation environments to real-world scenarios, Zenodo, 8305098, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8305098

Kapetanović, N., Vasilijević, A., Nađ, Đ., Zubčić, K., and Mišković, N. (2020). Marine Robots Mapping the Present and the Past: Unraveling the Secrets of the Deep. Remote Sensing, 12(23), 3902. MDPI AG. http://dx.doi.org/10.3390/rs12233902

Krieger, W. H. (2012). Theory, Locality, and Methodology in Archaeology: Just Add Water? HOPOS: The Journal of the International Society for the History of Philosophy of Science, 2(2), 243–257. https://doi.org/10.1086/666956

Anything related to underwater archaeology, either survey, excavation, or documentation processes, poses important challenges that were already once tackled and overcome in ground archaeology. While the archaeological and historical goals of researching the underwater heritage have already been defined and studied in the last decades, i.e. maritime economy, archaeology of harbour constructions, or life within ancient vessels, some of the methodological aspects that we consider normal in the surface are still a matter of concern for underwater archaeologists. Most of these issues are related to a general question: how to acquire geospatial data below the surface. That question related to the problem of acquiring spatial data with GPS data that could be analysed through established tools such as GIS. One could get spatial data with relative positions. However, it has to be inserted in a GIS using a projection.

Drones and GPS are one of the most significant archaeological documentation advances in the last decades. Both systems have become available due to the popularisation of affordable systems and software and the widespread use of GPS for civil uses. Recently, different scholars (Campana, 2017; Stek, 2016; Verhoeven et al., 2021; Waagen, 2019) have elaborated on the use of drones in (Mediterranean) archaeology and beyond. Nevertheless, once one starts working in a completely different setting as underwater archaeology, the need to answer the same methodological questions emerges one more time. How to create digital models of the (sea bottom) surface that could be useful to answer archaeological questions? Those questions could be posed in intra-site contexts (shipwrecks) of “submerged landscape” contexts, like a harbour context, an anchorage area, or a bay used through the past due to favourable conditions.

The paper by Diamanti and colleagues (2024) tackles these issues related to drone-based SfM in underwater archaeology. First, they introduced, albeit generally, drone imagery in archaeology to jump into the evolution of drone technology and its applications to marine archaeology. In this section, the main issues regarding the application of drones underwater are familiar to drone practitioners, such as payload capacity, portability, or affordability; other problems are mostly related to underwater devices, such as dive keep, real-time assessment or positioning using USBL (Ultra short baseline). 

Diamanti and colleagues present two study cases stemming from an ongoing project conducted in the Phournoi archipelago in the North Aegean Sea, Greece. The first study case is a Late Roman/ Early Byzantine shipwreck, and the second case study is an anchorage area. Both cases are relevant to the paper's overall scope and fit the reader's interest in how to apply underwater drone archaeology in a site context, the shipwreck, and in a broad context/ landscape, the anchorage point. The former a fascinating topic that has been tackled systematically in other areas of the Mediterranean sea (Quevedo et al., 2024)

I won’t explain both cases deeply, but both demonstrate the capabilities of drone-based SfM in underwater contexts. The authors use different devices with different cameras and make an interesting comparison with diver-based 3D models, perhaps the most used method to produce orthophotography of the sea-bottom surface for more than half a century (Drap, 2012; Yamafune et al., 2017). The authors lost a good opportunity to present a more exhaustive comparison of dive-based and drone-based SfM results besides the textual explanation. As a reviewer commented a summary table with camera characteristics and data from the processing results could have given way more depth to that interesting analysis. The authors present a workflow of the process when dealing with complex technological elements, starting with the hardware components such as drones, USBL, and cameras, and the software component of the process, from frame extraction to SfM. This addition contributes to the reproducibility of methodologies, as it is expected from methodological paper as this one. Kudos for that.

In general, Diamani et al.'s paper is a valuable contribution to understanding the impact of drone surveys underwater. It offers information about two relevant study cases that could be used as paradigms for upcoming innovation in underwater archaeology. The recommendation remains to elaborate further on the comparative perspective as the only way to make the research truly innovative.

References

Campana, S., 2017. Drones in Archaeology. State-of-the-art and Future Perspectives. Archaeol. Prospect. 24, 275–296. https://doi.org/10.1002/arp.1569

Diamanti, E., Ødegård, Ø., Mentogiannis, V. and Koutsouflakis, G. (2024) Underwater Drones as a Low-Cost, yet Powerful Tool for Underwater Archaeological Mapping: Case Studies from the Mediterranean. Zenodo, ver.3 peer-reviewed and recommended by PCI Archaeology https://doi.org/10.5281/zenodo.13460949

Drap, P., 2012. Underwater Photogrammetry for Archaeology, in: Special Applications of Photogrammetry. IntechOpen. https://doi.org/10.5772/33999

Quevedo, A., Aragón, E., de Dios Hernández García, J., Rodríguez Pandozi, J., Mukai, T., Segura, A., Bellviure, J. and Muñoz Yesares, R., 2024. Isla del Fraile. Reconstructing Coastal Dynamics in Southeastern Spain Through Underwater Archaeological Survey. Archaeol. Prospect. 31, 149–170. https://doi.org/10.1002/arp.1937

Stek, T., 2016. Drones over Mediterranean landscapes. The potential of small UAV’s (drones) for site detection and heritage management in archaeological survey projects: A case study from Le Pianelle in the Tappino Valley, Molise (Italy). J. Cult. Herit. 1066–1071. https://doi.org/10.1016/j.culher.2016.06.006

Verhoeven, G., Cowley, D. and Traviglia, A., 2021. Archaeological Remote Sensing in the 21st Century: (Re)Defining Practice and Theory. https://doi.org/10.3390/books978-3-0365-1376-8 

Waagen, J., 2019. New technology and archaeological practice. Improving the primary archaeological recording process in excavation by means of UAS photogrammetry. J. Archaeol. Sci. 101, 11–20. https://doi.org/10.1016/j.jas.2018.10.011

Yamafune, K., Torres, R. and Castro, F., 2017. Multi-Image Photogrammetry to Record and Reconstruct Underwater Shipwreck Sites. J. Archaeol. Method Theory 24, 703–725. https://doi.org/10.1007/s10816-016-9283-1