3D-GIS as a Platform for Visual Analysis : Investigating a Pompeian House
Author
Summary, in English
The aim of the present work is to introduce an innovative framework for employing 3D-GIS as an exploratory platform to perform visual analysis. Such a methodology is aimed at detecting patterns of visibility to simulate the past human perception of specific categories of artifacts placed inside a virtually reconstructed three-dimensional space. As a case study, the house of Caecilius Iucundus in Pompeii (regio V, insula 1, entrances 23 and 26) was chosen and two media of visual communication, a painting and a graffito were tested to make an assessment of their visual impact on hypothetical observers. The approach consists of a vector-based line-of-sight (LOS) analysis, now available as an integral component of the 3D-analyst toolkit of the ESRI ArcGIS 10.x software package. This toolkit allowed us to perform the entire process inside a GIS environment, without splitting the tasks among different software platforms.
It was thus possible to detect a significant difference in terms of visibility among the observed objects.
It was thus possible to detect a significant difference in terms of visibility among the observed objects.
Department/s
- Department of Archaeology and Ancient History
- Digital Archaeology Laboratory DARK Lab
- Archaeology
- Classical archaeology and ancient history
Publishing year
2016
Language
English
Pages
103-113
Publication/Series
Journal of Archaeological Science
Volume
65
Links
Document type
Journal article
Publisher
Academic Press
Topic
- Archaeology
Keywords
- Visualscape analysis
- 3D GIS
- GIS
- Classical Archaeology
- Archaeology
- Digital Archaeology
Status
Published
Project
- 3D GIS: a Research Platform for the Development of New Research Methodologies for the Documentation and Analysis of Archaeological Sites.
- Exploring Pompeian Graffiti in 3D Space
- Space and Movement in a Pompeian house: the contribution of 3D GIS
Research group
- Updating Pompeii-HT_760
- Digital Archaeology Laboratory DARK Lab
ISBN/ISSN/Other
- ISSN: 1095-9238