Seafaring and Modelling

Abstract Seafaring modeling is still a developing science, and there have been many approaches taken to evaluating human sea-based mobility in the past by researchers focused on different regions and time periods. Many models utilize similar processes or data inputs, including climate models, vessel technology studies, and human capabilities. However, being able to decide on the right approach can be difficult, and often relates to the technological know-how of the researcher, access to data on which the model can be based, and a discussion of what information is necessary coming out of the research to answer the initial question posed. This paper details and compares these various methodologies to help provide a foundation for developing future models or applying existing techniques to new areas. The authors, who have used a wide array of methods in their collective research, identify different data types that form inputs for models, describe the development of models, and consider the ways in which researchers can assess the appropriateness of models and data for their research questions. The models discussed in this paper include agent-based modeling, least cost path/route optimization analysis, drift modeling, isochrone analysis, and alternative forms of mapping. This paper provides case studies from different regions and time periods for each of these models. Finally, the authors discuss the relationship between computational models and the archaeological record. We aim for this work to provide a guide to those interested in using computational seafaring models in their research and to serve as a point of comparison for the effectiveness and possible application of current methods and research in future works.

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Publication Details

Journal
Journal of Maritime Archaeology
Published
2025-08-18
DOI
https://doi.org/10.1007/s11457-025-09455-5
Citations
2
Primary Topic
Oil Spill Detection and Mitigation
Type
article
Field-Weighted Citation Impact
1.01

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article

Seafaring and Modelling

Crystal El Safadi, Sara Zaia, Karl Smith-Byrne, Emma Slayton et al.
2 citations
Journal of Maritime Archaeology
Oil Spill Detection and Mitigation
1.01
article

Seafaring and Modelling

Crystal El Safadi, Sara Zaia, Karl Smith-Byrne, Emma Slayton, Katherine Jarriel, Álvaro Montenegro
article en
2 citations

Abstract

Abstract Seafaring modeling is still a developing science, and there have been many approaches taken to evaluating human sea-based mobility in the past by researchers focused on different regions and time periods. Many models utilize similar processes or data inputs, including climate models, vessel technology studies, and human capabilities. However, being able to decide on the right approach can be difficult, and often relates to the technological know-how of the researcher, access to data on which the model can be based, and a discussion of what information is necessary coming out of the research to answer the initial question posed. This paper details and compares these various methodologies to help provide a foundation for developing future models or applying existing techniques to new areas. The authors, who have used a wide array of methods in their collective research, identify different data types that form inputs for models, describe the development of models, and consider the ways in which researchers can assess the appropriateness of models and data for their research questions. The models discussed in this paper include agent-based modeling, least cost path/route optimization analysis, drift modeling, isochrone analysis, and alternative forms of mapping. This paper provides case studies from different regions and time periods for each of these models. Finally, the authors discuss the relationship between computational models and the archaeological record. We aim for this work to provide a guide to those interested in using computational seafaring models in their research and to serve as a point of comparison for the effectiveness and possible application of current methods and research in future works.

Journal of Maritime ArchaeologyVol. 20(3)
Purdue University West Lafayette (US), Harvard University Press (US), University of Oxford (GB), University of Southampton (GB), The Ohio State University (US), Carnegie Mellon University (US)
Carnegie Mellon University
Openalex Percentile: Top 24%
Oil Spill Detection and Mitigation
1.01
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