(Re)Defining the Archaeological Use of UAVs
A special issue of Drones (ISSN 2504-446X).
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 45045
Special Issue Editor
Interests: terrestrial and airborne photography plus multi- and hyperspectral imaging; image-based 3D modelling; image fusion; scientific visualisations; digital archaeology; landscape archaeology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Unmanned Aerial Vehicles/Systems (UAVs/UASs), also referred to as Remotely Piloted Airborne Systems (RPASs) or drones, have been used in archaeological research for at least three decades. However, ongoing research in the fields of robotics and geomatics, the proliferation of multicopters and flying wings, hardware price reductions and the miniaturization of various (imaging) sensors have significantly increased and improved the application of these platforms in the fields of archaeology and cultural heritage. From their use as prospection devices (to find out what lurks below the ground) to their application as cost-effective and highly maneuverable documentation platforms (for photographing or scanning difficult to access locations), UAVs have indeed altered and democratized many aspects of archaeological geospatial data collection in the past decades. However, this does not automatically mean that these high-tech tools are increasingly revolutionizing archaeology, as is often claimed. Many projects still use drones merely as convenient bird’s-eye view devices for the occasional collection of snapshots, potentially driven by the need to follow current trends in digital archaeology and digital humanities. In addition to these rather theoretical concerns, many practical issues and potential obstacles remain. For example, the rise of UAVs as flexible sensing platforms has in turn brought about safety and privacy concerns. Moreover, the non-expert’s perception of UAV-driven applications still balances somewhere between the controversy surrounding military drones and the fascination for pizza-delivering unmanned aircrafts.
This Special Issue of Drones seeks exceptional papers that explore and illustrate the breadth of avenues for UAVs in archaeological research, presenting appropriate theoretical and practical assessments, as well as recent original research of archaeological drone usage. Rather than another contribution on basic 3D surface model extraction from a collection of drone images, authors are encouraged to submit innovative papers showcasing how these unmanned motorized airborne platforms can currently transform the acquisition of archaeological knowledge. In this way, this Special Issue of Drones will compile a collection of high-impact papers that delineate the remote sensing potential and unique applications of UAVs in archaeology. Such a volume will not only (re)define the state-of-the-art in the archaeologically-relevant use of any type of unmanned motorized airborne platform, it also holds the potential to pave the way for furthering accurate, realistic, reliable, and relevant research in the nascent field of drone-based archaeological sensing.
Dr. Geert J. Verhoeven
Guest Editor
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.
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Keywords
- Archaeology
- Ancient monuments
- Landscape archaeology
- Heritage documentation
- Airborne remote sensing
- Airborne geophysics
- Monochromatic, multi- and hyper-spectral reflectance and thermal imaging
- Data fusion
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