Special Issue "Geocomputation Using Remote Sensing Data for Landscape Archaeology"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 1 September 2022.

Special Issue Editors

Dr. Geert J. Verhoeven
E-Mail Website
Guest Editor
Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology (LBI ArchPro), Ludwig Boltzmann Gesellschaft GmbH, Franz-Klein-Gasse 1, A-1190 Vienna, Austria
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
Dr. Edisa Lozić
E-Mail Website
Guest Editor
Institute of Classics, University of Graz, Universitätsplatz 3/II, 8010 Graz, Austria
Interests: archaeology; airborne laser scanning; classical archaeology
Dr. Christopher Sevara
E-Mail Website
Guest Editor
School of History, Classics and Archaeology, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
Interests: landscape archaeology; aerial archaeology; GIS and spatial analysis; remote sensing and geophysical prospection; image-based modelling
Dr. Benjamin Štular
E-Mail Website
Guest Editor
Znanstvenoraziskovalni center Slovenske akademije znanosti in umetnosti (Research Centre of the Slovenian Academy of Sciences and Arts), Inštitut za arheologijo (Institute of Archaeology), 1000 Ljubljana, Slovenia
Interests: archaeology; airborne laser scanning; landscape archaeology; digital archaeology

Special Issue Information

Dear Colleagues,

During the past three decades, landscape archaeology has become increasingly reliant on theoretical and practical approaches from the fields of geography and computation. Since the end of the 1990s, this application of computational methods to geographical data has become known as “geocomputation”. In addition to archaeology, geocomputation has become an essential part of geomatics, GIScience, and geoinformatics. Likewise, the fields of hydrology, biology, and soil science seek to leverage large sets of complex, geospatial data computationally. Rather than a scholarly field, geocomputation is thus an umbrella term encompassing any use of geographical data in a computationally intensive way for applied scientific work.

In line with the initial emphasis on the experimental and creative nature of geocomputational applications, this Special Issue seeks papers that cover novel, out-of-the-box computing approaches to practically and theoretically deal with data within the context of landscape archaeology. Rather than just any data, this Special Issue aims to leverage the potential of remote sensing data (and its derivatives) within geocomputation. Approaches include but are not limited to data mining and visualisation, spatiotemporal or agent-based modelling, machine learning, simulation, spatial statistics, and uncertainty modelling. Since good scientific practice entails reproducibility and falsifiability, sharing of source code or algorithmic details is highly encouraged.

All authors are expected to consider the following points to ensure the consistency of the papers in this Special Issue:

  • Authors must discuss how their work fits in the broader context of practice and theory in landscape archaeology;
  • Authors must discuss the settings (archaeological, environmental, and theoretical) in which their approach would not work;
  • Papers involving remote sensing data-facilitated geocomputation should present existing methods with a new applicational edge or focus on novel geocomputational techniques. However, authors must show that their approach delivers a demonstrable advance in the understanding of archaeological landscapes, providing new information that cannot be attained in any other way;
  • Authors must focus on reproducible results and methods that others can easily adopt. To that end, freely sharing source code is encouraged;
  • All papers must include applied archaeological examples with interpretation, clearly showcasing the benefits for landscape archaeology;
  • Finally, authors are also invited to consider and discuss the use of additional data sources that can strengthen, improve, or falsify their remote sensing and geocomputation-based interpretations.

Dr. Geert J. Verhoeven
Dr. Edisa Lozić
Dr. Christopher Sevara
Dr. Benjamin Štular
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 papers will be 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 2400 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.


  • Archaeology
  • Landscape archaeology
  • Remote sensing
  • Spaceborne imaging
  • Airborne imaging
  • Geocomputation
  • GIS
  • Spatial analysis
  • Machine learning
  • Data mining
  • Data visualisation
  • Spatiotemporal modelling
  • Agent-based modelling
  • Simulation
  • Spatial statistics
  • Uncertainty modelling
  • Parallel computing

Published Papers (1 paper)

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Airborne LiDAR Point Cloud Processing for Archaeology. Pipeline and QGIS Toolbox
Remote Sens. 2021, 13(16), 3225; https://doi.org/10.3390/rs13163225 - 13 Aug 2021
Cited by 3 | Viewed by 1198
The use of topographic airborne LiDAR data has become an essential part of archaeological prospection. However, as a step towards theoretically aware, impactful, and reproducible research, a more rigorous and transparent method of data processing is required. To this end, we set out [...] Read more.
The use of topographic airborne LiDAR data has become an essential part of archaeological prospection. However, as a step towards theoretically aware, impactful, and reproducible research, a more rigorous and transparent method of data processing is required. To this end, we set out to create a processing pipeline for archaeology-specific point cloud processing and derivation of products that are optimized for general-purpose data. The proposed pipeline improves on ground and building point cloud classification. The main area of innovation in the proposed pipeline is raster grid interpolation. We have improved the state-of-the-art by introducing a hybrid interpolation technique that combines inverse distance weighting with a triangulated irregular network with linear interpolation. State-of-the-art solutions for enhanced visualizations are included and essential metadata and paradata are also generated. In addition, we have introduced a QGIS plug-in that implements the pipeline as a one-step process. It reduces the manual workload by 75 to 90 percent and requires no special skills other than a general familiarity with the QGIS environment. It is intended that the pipeline and tool will contribute to the white-boxing of archaeology-specific airborne LiDAR data processing. In discussion, the role of data processing in the knowledge production process is explored. Full article
(This article belongs to the Special Issue Geocomputation Using Remote Sensing Data for Landscape Archaeology)
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