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Remote Sensing
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Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing
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Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (5 March 2023) | Viewed by 35586

Special Issue Editors

Prof. Dr. Bruno Fabio

E-Mail Website
Guest Editor
University of Calabria, Italy
Interests: underwater imaging; underwater robotics; 3D recording and modelling; virtual & augmented reality
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Maria Geraga

E-Mail Website
Guest Editor
Oceanus-Lab, Laboratory of Marine Geology and Physical Oceanography, Department of Geology, University of Patras, 26504 Patras, Greece
Interests: marine geology; palaeoclimatology; paleoceanography; marine remote sensing techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Oceans, lakes and rivers preserve a huge Cultural Heritage (CH) that includes a wide variety of artefacts spanning from the remains of prehistoric structures and settlements up to the wrecks of ships and aircrafts of the modern era.

Remote Sensing technologies and methods are non-destructive fundamental means of documenting and monitoring Underwater CH (UCH) through the creation of accurate and detailed 2D/3D maps of the cultural assets.

Since the environmental conditions of the underwater cultural sites are very diverse (from shallow water up to thousands of meters depths, close to the coastline or in the middle of the ocean and from crystal clear waters to high turbidity waters) also the sensors, the techniques and eventually the vehicles used for data acquisition are manifold.

This special issue is launched to collect original contributions that describe state-of-the art and innovative applications of Remote Sensing for the documentation and monitoring of UCH. Contributions are expected on all the topics related to this context and in particular on:

  • Sensor and data fusion approaches for opto-acoustic imaging;
  • Low cost and easy-to-use solutions that help the adoption of Remote Sensing technologies;
  • Innovative underwater robotics;
  • Case studies on deep sea archaeology;
  • Case studies in shallow waters and coastal environment;
  • Multidisciplinary case-studies;
  • Virtual and Augmented Reality for the public dissemination

Prof. Dr. Bruno Fabio
Dr. Maria Geraga
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Underwater Cultural Heritage
  • Underwater Archaeology
  • Underwater imaging
  • Photogrammetry
  • LIDAR
  • Side Scan Sonar
  • Multibeam Echosounder
  • Sub-Bottom Profiler
  • ROV (Remotely Operated Vehicle)
  • AUV (Autonomous Underwater Vehicle)
  • USV (Unmanned Surface Vehicle)
  • Marine Magnetometer

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

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Research

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14 pages, 2757 KiB  
Communication
Underwater 3D Scanning System for Cultural Heritage Documentation
by Christian Bräuer-Burchardt, Christoph Munkelt, Michael Bleier, Matthias Heinze, Ingo Gebhart, Peter Kühmstedt and Gunther Notni
Remote Sens. 2023, 15(7), 1864; https://doi.org/10.3390/rs15071864 - 31 Mar 2023
Cited by 13 | Viewed by 3558
Abstract
Three-dimensional capturing of underwater archeological sites or sunken shipwrecks can support important documentation purposes. In this study, a novel 3D scanning system based on structured illumination is introduced, which supports cultural heritage documentation and measurement tasks in underwater environments. The newly developed system [...] Read more.
Three-dimensional capturing of underwater archeological sites or sunken shipwrecks can support important documentation purposes. In this study, a novel 3D scanning system based on structured illumination is introduced, which supports cultural heritage documentation and measurement tasks in underwater environments. The newly developed system consists of two monochrome measurement cameras, a projection unit that produces aperiodic sinusoidal fringe patterns, two flashlights, a color camera, an inertial measurement unit (IMU), and an electronic control box. The opportunities and limitations of the measurement principles of the 3D scanning system are discussed and compared to other 3D recording methods such as laser scanning, ultrasound, and photogrammetry, in the context of underwater applications. Some possible operational scenarios concerning cultural heritage documentation are introduced and discussed. A report on application activities in water basins and offshore environments including measurement examples and results of the accuracy measurements is given. The study shows that the new 3D scanning system can be used for both the topographic documentation of underwater sites and to generate detailed true-scale 3D models including the texture and color information of objects that must remain under water. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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17 pages, 7720 KiB  
Article
A Settlement Landscape Reconstruction Approach Using GIS Analysis with Integrated Terrain Data of Land and Water: A Case Study of the Panlongcheng Site in the Shang Dynasty (Wuhan, China)
by Jianfeng Liu, Qiushi Zou, Qingwu Hu and Changping Zhang
Remote Sens. 2021, 13(24), 5087; https://doi.org/10.3390/rs13245087 - 14 Dec 2021
Cited by 3 | Viewed by 3502
Abstract
The landscape of ancient sites has changed greatly with the passage of time. Among all of the factors, human activities and the change in natural environment are the main factors leading to the change in site landscape. The Panlongcheng site, which is located [...] Read more.
The landscape of ancient sites has changed greatly with the passage of time. Among all of the factors, human activities and the change in natural environment are the main factors leading to the change in site landscape. The Panlongcheng site, which is located in Hubei Province, China, has a history of 3500 years with the most abundant relics in the Yangtze River Basin during the Shang Dynasty. As a near-water site, the landscape of the Panlongcheng site is greatly affected by water level changes and water conservancy activities. In this paper, by using spatial information technology, the data obtained from land and underwater archaeological exploration were integrated to restore landscapes of Panlongcheng sites in different periods. After removing modern artificial features and topsoil, the landscapes of the sites before the Shang Dynasty, in the Shang Dynasty and modern time were reconstructed. Combining historical records of water level changes, the landscape and water–land distribution of the Panlongcheng site were compared. The analysis results reflect the interaction between water level changes and human activities in this region for thousands of years, and support the archaeological findings in the near-water area of the Panlongcheng site, which provides a new idea for the landscape reconstruction and analysis of near-water sites. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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24 pages, 19382 KiB  
Article
A Multidisciplinary Approach for the Mapping, Automatic Detection and Morphometric Analysis of Ancient Submerged Coastal Installations: The Case Study of the Ancient Aegina Harbour Complex
by Nikos Georgiou, Xenophon Dimas, Elias Fakiris, Dimitris Christodoulou, Maria Geraga, Despina Koutsoumpa, Kalliopi Baika, Pari Kalamara, George Ferentinos and George Papatheodorou
Remote Sens. 2021, 13(21), 4462; https://doi.org/10.3390/rs13214462 - 6 Nov 2021
Cited by 6 | Viewed by 3629
Abstract
The documentation of underwater cultural heritage (UCH) is the basis for sustainable maritime development including its protection, preservation, and incorporation in coastal zone management plans. In this study, we present a multidisciplinary, non-intrusive downscale approach for the documentation of UCH implemented on the [...] Read more.
The documentation of underwater cultural heritage (UCH) is the basis for sustainable maritime development including its protection, preservation, and incorporation in coastal zone management plans. In this study, we present a multidisciplinary, non-intrusive downscale approach for the documentation of UCH implemented on the coastal area of Aegina Island, Greece, where a unique submerged harbour complex is preserved. This approach succeeded in obtaining information that serves both geomorphological and archaeological purposes in a time- and cost-effective way, while obtaining information of centimeters to millimeters scale. The geomorphology of the area was mapped in detail through marine geophysical means while ancient submerged conical rubble structures and breakwaters were documented using automatic seafloor segmentation techniques, revealing previously unknown sites of archaeological interest. The structures’ parameters were extracted from the acoustic data to analyze their morphometry, while photogrammetry was realized using a Remotely Operated Vehicle to expose their micro-structure. The spatial distribution of the structures revealed the construction of a well-planned harbour complex with multiple passages and different possible functionalities. Finally, through the structures’ morphometric analysis (geometry and terrain statistical parameters) their preservation status was revealed, demonstrating the anthropogenic impact on the submerged ancient structures due to the modern harbor activity. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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21 pages, 175800 KiB  
Article
The Battle of Lepanto Search and Survey Mission (1971–1972) by Throckmorton, Edgerton and Yalouris: Following Their Traces Half a Century Later Using Marine Geophysics
by George Papatheodorou, Maria Geraga, Dimitris Christodoulou, Elias Fakiris, Margarita Iatrou, Nikos Georgiou, Xenophon Dimas and George Ferentinos
Remote Sens. 2021, 13(16), 3292; https://doi.org/10.3390/rs13163292 - 20 Aug 2021
Cited by 6 | Viewed by 3542
Abstract
A series of marine remote sensing and ground-truth surveys were carried out at NW Gulf of Patras (W. Greece). The same area was surveyed in 1971 by Throckmorton, Edgerton and Yalouris, who are among the pioneers in the application of remote sensing techniques [...] Read more.
A series of marine remote sensing and ground-truth surveys were carried out at NW Gulf of Patras (W. Greece). The same area was surveyed in 1971 by Throckmorton, Edgerton and Yalouris, who are among the pioneers in the application of remote sensing techniques to underwater archaeology. The researchers conducted a surface reconnaissance survey to locate the site where the Battle of Lepanto took place on 7 October 1571. Their remote sensing surveying resulted in a map of two “target” areas that showed promise as possible remnants of wrecks from that battle and proposed a ground truth survey for their identification and in the detection of two modern shipwrecks. The ground truth survey was never fulfilled. The objectives of our repeat surveys, which were completed 50 years later, were to relocate the findings of this pioneer survey with higher spatial and vertical resolution, to ground-truth the targets, fulfilling their investigation, and to interpret the newly collected data in the light of modern developments in marine geosciences. Our repeat surveys detected mound clusters and individual mounds referred to “target” areas. These mounds could be interpreted as the surface expression of mud and fluid expulsion from the underlying deformed soft sediments. The ground truth survey demonstrated that the tops of mounds represent biogenic mounds. The ROV survey did not show any indication of wreck remnants of the Battle of Lepanto within the two survey areas. The site formation processes of the two modern shipwrecks were also studied in detail. Two noticeable seafloor morphological features were detected around the wreck sites; field of small-sized pockmarks and seafloor depressions. We would like to dedicate this work to the memory of Peter Throckmorton and Harold E. Edgerton, who are among the pioneers in the formative years of underwater archaeology in Greece. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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17 pages, 12308 KiB  
Article
An Underwater Pathfinding Algorithm for Optimised Planning of Survey Dives
by Marino Mangeruga, Alessandro Casavola, Francesco Pupo and Fabio Bruno
Remote Sens. 2020, 12(23), 3974; https://doi.org/10.3390/rs12233974 - 4 Dec 2020
Cited by 9 | Viewed by 3125
Abstract
In scientific and technical diving, the survey of unknown or partially unexplored areas is a common task that requires an accurate planning for ensuring the optimal use of resources and the divers’ safety. In particular, in any kind of diving activity, it is [...] Read more.
In scientific and technical diving, the survey of unknown or partially unexplored areas is a common task that requires an accurate planning for ensuring the optimal use of resources and the divers’ safety. In particular, in any kind of diving activity, it is essential to foresee the “dive profile” that represents the diver’s exposure to pressure over time, ensuring that the dive plan complies with the specific safety rules that have to be applied in accordance with the diver’s qualification and the environmental conditions. This paper presents a novel approach to dive planning based on an original underwater pathfinding algorithm that computes the best 3D path to follow during the dive in order to be able to maximise the number of points of interest (POIs) visited, while taking into account the safety limitations. The proposed approach, for the first time, considers the morphology of the 3D space in which the dive takes place to compute the best path, taking into account the decompression limits and avoiding the obstacles through the analysis of a 3D map of the site. Moreover, three different cost functions are proposed and evaluated to identify the one that could suit the divers’ needs better. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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Other

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13 pages, 1392 KiB  
Technical Note
A Comparative Study of Different CNN Models and Transfer Learning Effect for Underwater Object Classification in Side-Scan Sonar Images
by Xing Du, Yongfu Sun, Yupeng Song, Huifeng Sun and Lei Yang
Remote Sens. 2023, 15(3), 593; https://doi.org/10.3390/rs15030593 - 18 Jan 2023
Cited by 21 | Viewed by 7185
Abstract
With the development of deep learning techniques, convolutional neural networks (CNN) are increasingly being used in image recognition for marine surveys and underwater object classification. Automatic recognition of targets on side-scan sonar (SSS) images using CNN can improve recognition accuracy and efficiency. However, [...] Read more.
With the development of deep learning techniques, convolutional neural networks (CNN) are increasingly being used in image recognition for marine surveys and underwater object classification. Automatic recognition of targets on side-scan sonar (SSS) images using CNN can improve recognition accuracy and efficiency. However, the vast selection of CNN models makes it challenging to select models for target recognition in SSS images. Therefore, this paper aims to compare different CNN models’ prediction accuracy and computational performance comprehensively. First, four traditional CNN models were applied to train and predict the same submarine SSS dataset using both the original model and models with transfer learning methods. Then, we examined and studied the prediction accuracy and computation performance of four CNN models. Results showed that transfer learning enhances the accuracy of all CNN models, with lesser improvements for AlexNet and VGG-16 and greater improvements for GoogleNet and ResNet101. GoogleNet has the highest prediction of accuracy (100% in the train dataset and 94.27% in the test dataset) and good computational difficulty. The findings of this work are useful for future model selection in target recognition in SSS images. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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23 pages, 31018 KiB  
Technical Note
Using Remote Sensing Techniques to Document and Identify the Largest Underwater Object of the Baltic Sea: Case Study of the Only German Aircraft Carrier, Graf Zeppelin
by Artur Grządziel
Remote Sens. 2020, 12(24), 4076; https://doi.org/10.3390/rs12244076 - 12 Dec 2020
Cited by 8 | Viewed by 9059
Abstract
New shipwrecks are usually found during other work at sea. In 2006, the research vessel St. Barbara discovered probably the most massive wreck that lies on the bottom of the Baltic Sea. Its identity was unknown, and the Arctowski was sent to conduct [...] Read more.
New shipwrecks are usually found during other work at sea. In 2006, the research vessel St. Barbara discovered probably the most massive wreck that lies on the bottom of the Baltic Sea. Its identity was unknown, and the Arctowski was sent to conduct research. In this study, the author describes how an adequately selected research methodology using remote sensing technology can lead to obtaining precious and accurate measurement data. The article proposes an appropriate approach to identifying the most massive underwater object in the Baltic Sea. The results of bathymetric and sonar tests are presented. Unconventional use of scanning sonar, which was undoubtedly not foreseen by the manufacturer, was also proposed. The article also shows how some remote sensing techniques support and complement each other when verifying objects on the bottom. Moreover, this paper addresses the impact of sonar frequency and survey methodology on image resolution and data quality. If imaged under the right conditions, side-scan sonar can deliver records based on which shipwreck identification is possible. The wreck of the aircraft carrier lies at the bottom of the Baltic Sea at a depth of about 90 m. Some difficulties in measurements were caused by the lack of a depressor, the use of a light cable line, or the lack of a standard side-scan sonar winch. However, these limitations did not significantly affect the quality of the recorded data. The research results prove that the proposed methodology for using side-scan sonar (SSS) or scanning sonar is correct, and the obtained measurement data make it possible to identify the detected object at the level of 99%. Full article
(This article belongs to the Special Issue Documenting and Monitoring Underwater Cultural Heritage Using Remote Sensing)
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