Abstract

Mapping ancient roads is crucial to tell credible geospatial stories about where, how, or why different people might have travelled or transported materials within and between places in the distant past. Achieving this process is challenging and commonly accomplished by means of archaeological and GIS methods and materials. It is not uncommon for different experts employing these methods to generate inconsistent delineations of the same ancient roads, creating confusion about how to produce knowledge and decisions based on multiple geospatial perspectives. This yet to be adequately addressed problem motivates our desire to enrich existing literature on the nature and extents of these differences. We juxtapose GIS and archaeologically generated road maps for northern Etruria, a region of ancient Italy with a well-developed road network built by the Etruscans and Romans. We reveal map differences through a map comparison approach that integrates a broad set of qualitative and quantitative measures plus geospatial concepts and strategies. The differences are evident in route locations, sinuosities, lengths, and complexities of the terrains on which the routes were set as defined by subtle variations in elevation, slope, and ruggedness. They ranged from 11.2–34.4 km in road length, 0–65.7 m in road relief, 1.0–13.5% in mean road grade, 0.07–0.79 in detour indices and 0.19–3.08 for mean terrain roughness indices, all of which can be considerable depending on application. Taken together, the measures proved effective in furthering our understanding of the range of possible disagreements between ancient linear features mapped by different experts and methods and are extensible for other application areas. They point to the importance of explicitly acknowledging and maintaining all usable perspectives in geospatial databases as well as visualization and analysis processes, regardless of levels of disagreement, and especially where ground-truth informed assessments cannot be reliably performed.

Highlights

  • Roads are terrestrial pathways planned and built by humans since time long past [1]

  • In one of his writings in the first century BCE, Livy (39.2.5-7) credited the Romans for building the Via Flaminia Minor to connect Bononia and Arretium, following their military victories over the Ligurian Apuani in 187 BCE. This was the second Roman road constructed in northern Etruria, and the first in the eastern part of the Arno Valley, despite the Romans having been active in the region since at least the third century [22]

  • Least-cost path analysis (LCPA) pathways are drawn starting at destination and ending at origin points, which makes identifying these points based on characteristics such as functions, roles, and pull or push factors that cause unequal ‘two-way’ movement between settlements an important step (Figure 2) [32]

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Summary

Introduction

Roads are terrestrial pathways planned and built by humans since time long past [1]. These pathways make it easier to travel and move goods and people between locations that afford different senses of place [2]. Because all maps are made to be used, confusion arises when employing a map with several perspectives of the same feature or multiple maps displaying conflicting features, especially in the absence of clear guidance (e.g., confidence levels for mapping different routes or sections or roads) on how to process or decide on various inconsistencies Another piece of information that facilitates effective, appropriate, and ethical map use is metadata, which can include pointers to the quality of stories to be told, decisions to be made, or actions to be taken based on exploring and analyzing one or more maps [15]. We use northern Etruria, a region of ancient Italy with well-developed terrestrial pathways built and maintained by the Etruscans and Romans as study area for juxtaposing and revealing the differences between GIS and archaeologically produced maps of equivalent ancient roads routes

Study Area and Roads
Site A
Site B
Ancient Road Mapping Methods and Materials
Geospatial Datasets
GIS-Based Tools and Techniques
Conclusions
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