Surface visibility and the validity of settlement patterns in legacy survey datasets

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Abstract

The ground visibility of the terrain that is surveyed has a clear impact on detecting archaeological finds. Because the resulting distortions may influence the quality of the interpretation of single settlements and settlement patterns, various checks of the terrain and the collected data are needed. Therefore, in current survey projects different types of tests and data filtering are increasingly implemented both in the field and in the laboratory as a part of their methodology. However, some of the most important archaeological landscape projects were initiated long before an agreement on a standard methodology for field survey was reached. As a result, legacy datasets have been deemed to be of little value to present-day scholarship due to the current research standards. In this paper, we examine if legacy data can be useful to contemporary research by performing a study comparing legacy data collected by the Forma Italiae survey project to contemporary data collected by the LERC project. The Forma Italiae survey project was carried out in the late 20th century and produced a large dataset of archaeological sites in the area around the ancient town of Venusia (located in Southern Italy). We first analyzed the relationship between surface visibility and the density of identified Hellenistic-period sites by means of a statistical analysis, and then tested the reliability of the legacy site patterns by comparing them with new data recovered from the field in a recent re-survey of this region by our team as a part of the LERC project. We thus assessed the compatibility of the clustered pattern of sites detected by the Forma Italiae and the new LERC field surveys. At odds with more pessimistic estimations, we conclude that on the regional level and coarse scale of analysis the legacy survey data is representative and offers significant evidence to current scholarship for the study of ancient settlement patterns
Original languageEnglish
Number of pages13
JournalFasti Online Documents and Research
Volume17
Publication statusPublished - 2021

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