D geometric survey of cultural heritage by UAV in inaccessible coastal or shallow aquatic environments
Bibliographic Data
Cultural heritage in coastal or shallow aquatic environments is often located in areas where access is difficult or where accurate survey and documentation may not always be possible with terrestrial or aquatic equipment. The combination of photogrammetry and unmanned aerial vehicles (UAVs) generates a range of possibilities across multiple sectors, including history, ethnography and cultural heritage studies. Additionally, these methods can be used to prospect new archaeological sites. This article presents three case studies that use UAV techniques and Structure from Motion and Multiview Stereo (SfM‐MVS) photogrammetry to conduct topographic and geometric registrations of archaeological, historical and ethnographic sites (some of which are classified as cultural heritage sites). These examples are located in coastal or shallow aquatic environments that are difficult to survey with traditional methods. The results show that it is possible to carry out detailed geometric registration and heritage prospection over large coastal or shallow aquatic environments using a low‐cost UAV. Furthermore, the results of this work show great advantages in terms of cost and quality, even in cases where the seabed is below a shallow water column. Other particularities of SfM‐MVS application in aquatic environments are discussed. From an interdisciplinary perspective, this methodology will offer new possibilities for the study, restoration and conservation of archaeological, historical and ethnographic monuments
Archaeology · Citizen science · Cultural heritage · Documentation · Environmental resource management · Ethnography · Geography · Motion (physics · Perspective (graphical · Photogrammetry · Remote sensing · Structure from Motion · Work (physics · 3D Surveying and Cultural Heritage · Archaeological Research and Protection · Computer Science · Engineering · Environmental Science · Remote Sensing and LiDAR Applications · Artificial Intelligence · Geology
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| Citation velocity | historical |
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| Highly cited | No |