The Doganella Survey Project: The Multimodal Remote Sensing Survey of a Pre-Roman Etruscan Urban Center (15 min)
Presenters
Antonio LoPiano, Duke University
Abstract
During the summer and fall of
2022 a multimodal remote sensing survey was conducted at the Etruscan urban
center of Doganella in southern Tuscany, employing drone-based multispectral
imaging, GPR, and resistivity sensing. This paper presents the results of that
project and reviews the effectiveness of the methodology. The survey at
Doganella begins to fill a significant lacuna in the archaeological record of
central Italic cities, from the late-fifth to early third centuries B.C.E. Most
of what is known concerning this period of urbanization in central Italy is
derived from burials and sanctuaries. The general lack of evidence from urban
centers themselves makes it difficult to assess the nature of urban development
of this pivotal period prior to Roman regional control. Rome and its colonies
continue to dominate the scholarly dialogue around the chronology and diffusion
of orthogonal planning, civic structure, and monumental public spaces due to
their visibility, preservation, and extensive study.
Doganella is known through
field surveys to have gradually developed into a large urban center by the
fourth century B.C.E. before it was abandoned in the early third century. Its
chronology and lack of later Roman occupation make it a prime candidate to
assess the concepts of urban planning current in central Italy previous to the
spread of Roman colonies through Etruria. Indeed, the survey has discovered
traces of a large-scale orthogonal street network, walls, gates, and other
major urban structures. The implication of these early results is that
Doganella was a major center in its own right whose planning reflected the
monumentalization and regularization of Etruscan cities contemporary to those
processes taking place at Rome. While reviewing these results this paper also
discusses the utility of a multimodal approach to a remote-sensing survey as a
methodology to efficiently target transects and overcome geomorphological
particularities.
AIA-2B