Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Work on the excavations at the ancient Etruscan settlement of Marzabotto (Bologna) restarted in 1988. These excavations, as they were worked, brought to light a complete urban layout represented primarily by foundations, courtyards, roads and wells. The site has been the focus of intensive experimentation to assess the feasibility ofgeophysical remote sensing in exploration archaeology. Different geophysical techniques have been tested at this site: geoelectric, electromagnetic, magnetic, and seismic methods. One of the methods tested was geophysical seismic tomography. This method utilizes straightray algorithms to map subsurface properties by analyzing the first signal arrival time. Seismic tomography treats the problem of identifying a buried structure as a wave propagation process by inverting the linearized wave equation to compute the spatial distribution of the slowness of the velocity. The purpose of our tomographic study is to further test the method and to guide archaeologists in their future excavations by locating and identifying buried structures. In particular, analyses are performed on the geometries, signal characteristics, discretization of the area, and constraints of the inversion algorithm in order to enhance the effectiveness of the tomographic reconstruction process and to reduce costs. A controlled experiment is presented for a typical Marzabotto buried structure with which it is possible to verify the effectiveness of the applied technique. It is demonstrated how proper field measures and an inversion test can provide reliable information that can be used to guide excavation work.
Work on the excavations at the ancient Etruscan settlement of Marzabotto (Bologna) restarted in 1988. These excavations, as they were worked, brought to light a complete urban layout represented primarily by foundations, courtyards, roads and wells. The site has been the focus of intensive experimentation to assess the feasibility ofgeophysical remote sensing in exploration archaeology. Different geophysical techniques have been tested at this site: geoelectric, electromagnetic, magnetic, and seismic methods. One of the methods tested was geophysical seismic tomography. This method utilizes straightray algorithms to map subsurface properties by analyzing the first signal arrival time. Seismic tomography treats the problem of identifying a buried structure as a wave propagation process by inverting the linearized wave equation to compute the spatial distribution of the slowness of the velocity. The purpose of our tomographic study is to further test the method and to guide archaeologists in their future excavations by locating and identifying buried structures. In particular, analyses are performed on the geometries, signal characteristics, discretization of the area, and constraints of the inversion algorithm in order to enhance the effectiveness of the tomographic reconstruction process and to reduce costs. A controlled experiment is presented for a typical Marzabotto buried structure with which it is possible to verify the effectiveness of the applied technique. It is demonstrated how proper field measures and an inversion test can provide reliable information that can be used to guide excavation work.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.