Alejandro Güimil-Fariña *

César Parcero-Oubiña **§

* Laboratorio de Patrimonio, Paleoambiente e Paisaxe (LPPP), Universidade de Santiago

de Compostela (USC)

Edificio Monte da Condesa, s/n; Campus Sur; 15782 Santiago de Compostela (Spain)

alejandro.guimil.farina@usc.es

** Instituto de Ciencias del Patrimonio (Incipit), Consejo Superior de Investigaciones

Científicas (CSIC)

San Roque, 2; 15704 Santiago de Compostela; Spain

cesar.parcero-oubina@incipit.csic.es §

Corresponding author

The use of GIS tools to explore questions related to movement in archaeological contexts

has been common in the last years. Least Cost Paths (LCP) have been especially

successful among them, most often with the objective of predicting or reconstructing the

layout of ancient routes. In this paper we propose an alternate use of those tools, aimed at

trying to identify the main locations taken into account when defining the routes, rather

than at predicting or reconstructing them. Through a rather simple and straightforward

methodological sequence, based on the successive testing of very explicit hypotheses, we

show how this approach can produce significant new knowledge while dodging some

typical issues of LCP analysis. We illustrate the approach with the case study of the

Roman roads in the north-west Iberian Peninsula.

GIS; Least Cost Paths; Ancient Roads; Route Layout Factors; Roman Roads; NW Iberian

Peninsula

The study of movement remains a major subject in the analysis of any archaeological

context. In the recent years, the spreading of digital tools such as GIS has opened the way

for new approaches that have proved fruitful (Llobera 2000, Posluschny 2010, Bevan

2011, Llobera et al 2012, Murrieta-Flores 2012, Verhagen 2013). Among these

approaches, the use of least cost paths (LCP) has been especially widespread (Fairén

2004, Rahn 2005, Howey 2007, Fábrega-Álvarez and Parcero-Oubiña 2007, Newhard

2008, Ruestes 2008, Lock and Pouncett 2010, Taliaferro et al 2010, Herzog and

Posluschny 2011, White and Barber 2012, White and Surface-Evans 2012, Herzog 2013).

When archaeologically approaching the analysis of movement from a GIS-based

perspective, the complexity and formality of the context under analysis have conditioned

to a great extent the perspective taken. In the case of complex and highly formal

archaeological contexts, where obvious material remains of road networks are preserved,

the most common approach has consisted of using LCP as a way to predict, and in some

cases reconstruct, the original route of ancient roads (Bell et al 2002, Ejstrud 2005, Batten

2007, Matsumoto 2008, Siart et al 2008, Stanish et al 2010, Bödőcs 2011, Contreras 2011,

Verhagen and Jeneson 2012, White and Barber 2012). Those can be described as “joining

the dots” approaches, where two or more places are joined with a LCP and the results

compared with the distribution of known nodes of the original road network in order to

assess the archaeological reliability of the predicted paths.

In contrast with those, in complex archaeological contexts there has been a limited use of

digital tools as a way to analytically explore the logics of mobility. Although good

examples exist of the use of digital simulations to explore the role of potential mobility in

Prehistoric contexts (Llobera 2000, Chapman 2003, Wheatley et al 2010), where traces of

actual paths or roads are typically scarce, few examples exist of similar approaches to

better understand the role of mobility in the shaping of politically complex landscapes

(see for instance Richards-Rissetto and Landau 2014). Although the availability of more

abundant data for those complex contexts would allow a fruitful exploration of the logics

behind the development of specific networks of paths and roads, such as identifying the

main nodes of the network, most of the focus has been put on where the roads may be, or

have been, rather than on why they are where they actually are.

In this paper we will explore the possibilities of an analytical, non-reconstructive use of

GIS for the analysis of formal and stable networks of roads, using the Roman roads in the

NW Iberian Peninsula as a case study. Rather than using LCP to “fill the voids” and

discovering the itineraries of the road sections we do not know about, we will focus on

understanding why the remains we do know about follow the routes we still see today.

Rather than asking where a road might have been, we propose asking why the known

remains of a road are where they are: how, in terms of mobility within the territory, we

can grasp the meaning of the known sections of ancient roads within a given geographic

area.

The study of Roman roads is a topic with a long tradition in archaeology. Most often they

have been studied from the formal perspective of the elements involved in their

construction, such as bridges or milestones, the construction techniques and tools, or their

economic use. On the other hand, the search for their remains and the reconstruction of

their likely routes has been a widespread field of research, where digital tools have proved

helpful (Tsokas et al. 2009), including LCP-based approaches, as was abovementioned

(Bödőcs 2008, Ejstrud 2005, Verhagen et al. 2012) or approaches based on network

analysis (Carreras and De Soto 2013).

The selected study area, the north-west of the Iberian Peninsula, shows a rather

impressive number of archaeological elements related to Roman roads, essentially a large

number of milestones. To a great extent, their layout indicates quite obviously the original

route of the roads in many areas of the region (Figure 1), though some significant voids

also exist. For that reason, and as elsewhere, the study of Roman roads has focused

mostly on reconstructing the routes, using a combination of different data: classical

written sources, epigraphy and milestones, remains of sections of the roads in the

landscape, or place names (Roldán Hervás 1975, Caamaño Gesto 1984, Peña Santos

1990-1, Franco Maside 2000, 2001, Rodríguez Colmenero et al 2004, Pérez Losada 2002,

Moralejo Álvarez 2009). As a result, a number of proposals exist about the probable

routes of the Roman roads, which, as expected, diverge mostly in those areas where direct

archaeological evidence is absent.

Figure 1. Study area. Location of material elements directly related to the Roman roads.

These approaches have led to significant progress in identifying the network of overland

routes that existed in Roman times in what was known as the province of Gallaecia,

despite some controversy regarding their chronology and the changes that may have been

made to the routes over time. To sum up, there were four main Roman roads in the region,

numbered as XVII, XVIII, XIX and XX in the Antonine Itinerary, joining the three main

administrative towns, plus a number of secondary and local roads. Despite the fact that

some routes are better known than others, there is some consensus regarding the

itineraries of the main ones, especially in those parts with plenty of direct evidence

(Figure 2).

Figure 2. Map of suggested routes of the Roman roads (adapted from Rodríguez Colmenero et al 2004). According to these authors, the road XX would be partially a maritime route.

As presented in the introductory section, our aim here is to use a GIS-based approach to

identify the places that would have operated and the main nodes for the construction of

the network of Roman roads. To a great extent, this approach can be presented as a

problem of locational analysis (Barnes 2003): why the Roman roads, represented by the

preserved remains, were located there?

More specifically, our approach tries to explore the question as to what extent the Roman

road system here was imposed on an existing landscape or it was a development of

existing routes. This issue, also present for other areas of the Roman Empire (e.g.

Chevalier 1997), has been discussed for some time now in the regional literature (eg.

Caamaño Gesto 1980, González-Ruibal 2001). Beyond the immediate implications, the

problem is closely related to wider discussions about the more or less “disruptive”

character of the Roman occupation of the area.

The study is based on an operative hypothesis, based on the fact that, in the absence of

any other criteria, roads are designed to follow the route that requires the least effort in

terms of movement. This assumption fits extremely well with the main methodological

tool chosen, LCP. Indeed, “LCP analysis is based on the assumption that people optimise

the costs of routes which are taken frequently, and that, over time, this leads to the

development of the real-world equivalent of an LCP” (Herzog 2013). Of course, we are

well aware that this is usually a rather problematic assumption, since there are many other

conditioning factors that affect mobility, both of cultural and physical nature (e.g. Llobera

2000, Cameron 2013). Although this might be a major issue when trying to predict or

reconstruct ancient routes, our approach here minimizes those risks, since it considers

that as a hypothesis, and not as an expected behaviour. What we are trying to check is to

what extent it is possible to understand the Roman road network based on this hypothesis,

or not; and if not, to obtain additional information in order to understand which other

factors could have conditioned the network.

The selected case study is also very well suited to such an approach, since it consists of a

highly formalized network of paths, developed within the context of a complex social and

political formation such as the Roman state. We are not dealing here with fluid, unstable

and easily changing forms of mobility, but with a context where a strong discipline was

imposed over the landscape. This also produced a significant ensemble of material

remains that constitute a rich source of evidence.

Within this problem-oriented approach, the study follows an analytical sequence based

on the proposition of a series of hypotheses, from the simpler to the more complex,

related to a very basic idea: roads are intended to join places. So the sequence of analysis

consists of three very basic steps:

To define a series of locations that could have served as primary movement

‘nodes’ (starting or arrival points).

To model the different effort required to cross through the terrain, expressed in

terms of ‘cost’ and ‘accumulated cost’, that will be the basis to delineate the

optimal corridors to join those locations across the landscape.

To define a series of elements to compare the results provided by our hypothesis,

and the situation they represent. In this case, we require direct, spatially located

indicators of the actual route of the Roman roads.

Other issues could be argued regarding the calculation of movement costs and LCP

through the available GIS software, issues related to the imperfection of the GIS

representation of actual movement in a landscape (Herzog 2013, Kantner 2012).

However, considering the scale of our analysis (see next section), they can be regarded as

minor issues.

In terms of methodology and data, two critical questions must be addressed to perform a

LCP analysis: the selection of a procedure to theoretically model the costs of movement

across the terrain, and the selection of the data needed to implement that model (the

fundamentals of cost analysis are well explained elsewhere, for instance in Conolly and

Lake 2006 or Herzog 2013).

The theoretical modelling of human movement has been the subject of different proposals

(Pandolf et al. 1977, Tobler 1993, Llobera and Sluckin 2007, Herzog 2013 [based on

Minetti et al. 2002]). Most of them are designed to predict movement costs due to

variations in the terrain slope, and are aimed at modelling human walking movement. In

our case, considering the conditions and needs of the Roman road system, a cost function

designed to model wheeled movement (such as the one in Herzog 2013) could seem the

obvious choice. However, as was mentioned above, one of our main aims is to explore to

what extent the Roman roads may be related with pre-existent, pedestrian routes, so we

need to stick to walking costs.

Among the existing cost functions, perhaps the best-known and more widely used (at

least for archaeological purposes) is the ‘hiking function’ developed by W. Tobler (1993).

It was our first choice here, considering the good results it provided in previous research

developed in the same region (Fábrega-Álvarez and Parcero-Oubiña 2007). Besides that,

some experiments have proved that Tobler’s function produces reliable results when

tested on the field (Kondo and Seino 2010). However, a lively debate exists as to what

extent this might be the best option available. While it has been argued that other

proposals may be more accurate in the representation of how the slope affects human

walking (Llobera and Sluckin 2007, Kantner 2012, Herzog 2013), it has also been noted

that, in practical terms, differences are typically not very big (Verhagen and Jeneson 2012:

127) 1.

Figure 3. Comparison of LCP produced by the most commonly used cost functions in a test area.

To assess those questions, we examined the outcomes of the different functions in a same

test area, where a good knowledge of the likely route of the Roman road exists. The four

functions were tested with the same parameters. The objective was twofold: on the one

hand, to check to what extent the outcomes of the different functions differ to each other

in a zone that is representative of the whole study area, with a rather hilly relief; on the

1 Rather, different outcomes in the determination of LCPs usually relate to the use of different DEMs or

different software tools (Herzog and Posluschny 2011, Herzog 2013). See next section for the influence of

this factor in our case study.

other hand, to pragmatically evaluate the adequacy of each function for our specific

purpose by comparing their results with the most probable route of the Roman road.

The cost functions assessed were those by Pandolf et al. (1977), Tobler (1993), Llobera

and Sluckin (2007) and Herzog (2013, based on Minetti et al. 2002)2. The results (Figure

3) show that the derived LCP produce two basic layouts: while those based on Tobler,

Llobera-Sluckin and, to a great extent, Pandolf et al. follow a similar route well in line

with most of the known milestones, the one derived from Herzog shows a lower

correlation. It is especially remarkable the similarity between the LCP produced by

Tobler and Llobera-Sluckin functions.

For quantification, the similarity between these LCP and the most probable route of the

Roman road was measured in two ways. First, we directly measured the linear distance

between each LCP and all the known in situ milestones in this area. As seemed at first

sight, the histogram (Figure 4) shows that the first three functions are in general close to

the location of the known milestones. Second, we compared each LCP with the proposed

route of the Roman road in this area, following the procedure suggested by Goodchild and

Hunter (1997) to evaluate the similarity between two linear features: it is based on

determining the proportion of a linear feature (in our case each LCP) that lie within a

buffer distance from what are taken as the “true” linear features (the proposed

reconstruction of the Roman road). The results (Table 1), shown here for two buffers of

500 and 1,000 m, offer a complementary measure that reinforces the best performance of

the function by Llobera and Sluckin for this particular context and case.

Figure 4. Histogram of distance between known in situ milestones and different LCP in the test area.

Besides slope, water courses were the only other features considered in our determination

of walking costs, although in a very specific way. Water courses are problematic when

2 The parameters chosen for Pandolf’s formula were: speed = 5 km/h, load = 0, terrain factor = 1.

calculating movement costs, for two reasons. On the one hand, they are portions of the

terrain not suitable for most forms of movement: one cannot walk on the water. On the

other hand, they can be crossed but usually only in specific points, and this can impose

strict limitations on the ability of humans to move.

Table 1. Similarity between different LCP and the probable route of the Roman road between Bracara and Tude.

The first problem is purely operational: since river courses are areas with slopes gentler

than most of the surrounding terrain in this region, they typically may be regarded by the

software as theoretically good areas for movement (Figure 5). This might be a significant

problem in our area, due to the huge number of watercourses. To avoid that effect, to

prevent the optimal routes from following river courses, we assigned a single cost value

to every water course equivalent to move across a slope of 0.27 gradient (15º). That figure

was obtained after some experimentation in previous research (Fábrega-Álvarez and

Parcero-Oubiña 2007) and allows a good performance in avoiding the effect while

allowing LCP to cross any river.

Figure 5. Due to topographic reasons, LCP can follow water courses if only terrain slope is considered as a cost factor.

The second problem, the effects in movement of the existence of some specific places to

cross the rivers, is of a different nature. In our case, it is actually not a precondition of the

analysis but a part of what we want to explore. We actually know the location of some

Roman bridges (Figure 1). What we want to find out is to what extent those places,

spatially located indicators of the actual route of the Roman roads, match the routes

theoretically determined by the LCP analysis. Only in a later phase of the analysis we will

make a different use of one of those bridges (see section 4.3).

To sum up, after the tests performed, we selected for our analysis the functions by

Llobera-Sluckin and Tobler as a way to double check the significance of the LCP we will

produce. Both were implemented anisotropically with the modules PathDistance and

CostPath in ArcGIS 9.3. To include the correction factor for water courses, we set a

buffer zone of 50 m around every single river and assigned those areas the above

mentioned cost factor 3.

3 PathDistance allows the combination of anisotropic and isotropic factors into a single calculation.

The main input source needed to determine the costs of walking across the landscape is a

DEM representing the topography of the terrain. We needed a DEM covering uniformly

all the area of interest, a vast territory that includes portions of Spain and Portugal. This

posed some practical difficulties for using geographical data produced at the national

level. While for Spain a number of different DEM are available nowadays from the

Instituto Geografico Nacional (cell sizes of 5, 25 and 200 m) 4, for Portugal only a 50 m

DEM is available for public use so far 5. Besides differences in cell size, they are

heterogeneous both in origin (photogrammetry or lidar data for Spain, interpolation of

digitized contours for Portugal) and spatial reference systems used (ETRS89 for Spain,

Lisboa-Hayford datum for Portugal). That all makes very problematic to mosaic them

into a continuous, uniform surface that represents relief in a homogeneous and

comparable way across the whole area of interest.

Global models as SRTM or Aster GDEM are free of those problems, but their spatial

resolution and, in some cases, accuracy might be problematic. Despite its higher

resolution (ca. 30 m), it has been observed that Aster GDEM includes important

systematic errors (see for Spain Gómez-Gutierrez et al. 2011), while SRTM (ca. 80 m)

has proved an acceptable average accuracy for some areas of Portugal and Spain

(Gonçalves and Fernandes 2005, Gómez-Gutierrez et al. 2011), so we considered it as our

DEM of choice.

In order to evaluate its suitability, we used the same test zone to compare the outcomes of

two LCP calculated with the same parameters (cost functions) using the SRTM and a 10

m DEM produced by ourselves from the interpolation of contours from 1:5.000 maps.

The results (Figure 6) show a remarkable similarity in both LCP, indicating that the

SRTM is providing a sufficient representation of the topography, at least in terms of the

influence of the terrain slope on human movement and at the scale of our analysis.

4 http://centrodedescargas.cnig.es/CentroDescargas

5 http://www.igeo.pt/DadosAbertos/Listagem.aspx

Figure 6. Comparison of LCP calculated with the SRTM and a 10 m cell size DEM.

As we mentioned above, water courses are a second essential data layer for our analysis.

As was the case for topography, we discarded the combination of different existing river

layers for their lack of homogeneity, uniformity and consistency between Spanish and

Portuguese data. As an alternative, we produced our own representation of the water

courses in the area through a flow accumulation analysis of the selected DEM.

Regarding archaeological data, a selection of all the features related to the Roman road

network was made based on different bibliographic sources and inventories. Milestones

are the most numerous and appropriate element of the record directly associated with the

route of the ancient roads (Figure 1). The spatial location of those elements was taken

from Rodríguez Colmenero et al (2004). Only those with a well-known original in situ

location were considered in our study. Roman bridges were also considered, following

the studies of Alvarado Blanco et al (1990) and the Portuguese national monuments

record data available on-line 6.

6 http://arqueologia.igespar.pt/

After the final conquest of the whole NW Iberian Peninsula by Augustus around 19 BC, a

territorial organisation was created based on the foundation of three administrative

territories called Conventus (Asturicense, Bracarense and Lucense) with their respective

capitals, Asturica Augusta (García Marcos and Vidal Encinas 1999), Bracara Augusta

(Martins 2000) and Lucus Augusti (Rodríguez Colmenero 2001). These cities were the

nerve centres for the organisation of the territory by the Roman authorities from a

political, fiscal and military perspective. Therefore, our initial hypothesis to test is that the

first roads that were created in the region would have been designed to connect these

cities, and from there on to create a network that connected them with other areas of

interest in the region. Assuming as part of the hypothesis that this was the only criterion

considered when designing the route of the roads, they should be expected to follow the

simplest path between those locations. May this hypothesis be valid, a great deal of

coincidence should occur between the theoretically calculated LCP and the location of

the actual remains of the ancient roads.

Figure 7. LCPs between the three capital towns, compared to milestones and bridges. In light yellow, the proposed reconstructions of the main roads (after Rodríguez Colmenero et al. 2004, see figure 2).

To test this first hypothesis, we only need to determine the LCP between the three capital

towns, and compare them with the known routes. Choosing an anisotropic approach, as

mentioned in section 3.2.1., implies the potential production of 2 routes for every

connection (A to B and B to A), which may differ considerably (Herzog 2013). In our

case, the nature of the archaeological evidence helps in deciding which route makes more

sense, since it has been documented that most of the Roman road network in the region

had its origin in Bracara, being Asturica the main destination (Rodríguez Colmenero et al

2004). The LCP shown in the figures and used in the following calculations were chosen

following that argument.

Despite that, we calculated all the possible LCP between these three main nodes, in order

to obtain a measure of their similarity. The results (Table 2), measured again following

the procedure suggested by Goodchild and Hunter (1997), show a remarkable

coincidence in all cases, even within such a small buffer distance as 100 m. Only the

Tobler-based LCP between Lucus and Bracara show two completely different routes for

the two directions, the one starting in Bracara (Figure 7) having a much higher

coincidence with the spatial distribution of milestones. The results of this test point

towards the existence of some remarkable topographic determinants for mobility in this

region at a general scale, which strengthens the potential value of the approach proposed

here.

Table 2. Similarity of the two possible anisotropic paths (A to B and B to A) between the three Roman capitals.

At first sight, if we compare the results with the general outline of the network (Figure 7,

see also Figure 2) we can see how the three LCP might be the theoretical equivalents of

road XVII (Bracara-Asturica), a section of road XIX (Lucus-Asturica) and a secondary

road between Bracara and Lucus. We can measure how close the theoretically

determined LCP are to their “true” equivalents in the same two ways previously defined

(see section 3.2.1): by comparing them with the location of the milestones belonging to

each particular road section (highlighted in black in Figure 7) and with the proposed route

of the roads (Figure 8, Table 3). We won’t consider here the road between Lucus and

Asturica because of the very few in situ indicators of the original route.

The results support the idea that the logic of LCP connecting the main towns in the region

allows us to understand only a small part of the road network: only the route between

Bracara and Lucus (Figure 2), which has been considered by some as a later road, maybe

built in the Late Empire, although an early origin has also been suggested (Pérez Losada

2002: 161). For that particular case, the LCP delineate a corridor that is significantly

coincident with the location of in situ milestones and bridges. Coincidence with the

proposed route of the road is not so high (Table 3), but it must be noted that the

reconstruction (taken from Rodríguez Colmenero et al. 2004) is quite speculative in those

sections where no direct evidence is available.

However, in the case of the road between Bracara and Asturica only a short section near

Bracara shows a good coincidence. For most of the road, both the in situ indicators and

the proposed reconstruction have a very different layout than those of the LCP.

Figure 8. Histograms of distances between in situ indicators of Roman roads (milestones and bridges) and corresponding LCP for routes between Bracara-Lucus (top) and Bracara-Asturica (bottom).

Table 3. Similarity between LCP and the proposed route of the Roman roads.

At this point two options exist. The first is that most of the roads followed a logic other

than that of the optimal pedestrian connection between places. The second is that other

positions in the landscape operated as primary nodes when building the road network.

Although the first might explain the differences between LCP and actual roads in the

areas examined in the previous section, it does not allow to understand the remaining

parts of the network.

Considering again that the organization and administration of the Roman province was

based on urban, or semi-urban, settlements, we decided to extend our hypothesis by

incorporating the secondary Roman settlements in the region, those on a scale

immediately below the regional capitals. In this stage, the nodes included are those

referred to by Pérez Losada as “secondary settlements”: Iria Flavia, Tude, Flavium

Brigantium and Aquae Flaviae (Figure 9, Pérez Losada 2002, Rodríguez Colmenero

1997). All of them are centres of population with an urban or semi-urban layout, some of

which contain remains of public architecture and a large number of Roman epigraphs,

associated with worship and official activities. Another characteristic feature, except in

the case of Aquae Flaviae, is their location as riverside ports (Tude and Iria) or sea ports

(Flavium Brigantium) which were of great importance for long-term navigation and trade.

Finally, they are all referred to in different classical sources as mansio (wayside inns),

although in these cases their urban development mean that they played a more significant

role than mere points on the road network.

Considering again the paucity of first hand information about the road network around

Flavium Brigantium (few milestones and, consequently, highly speculative

reconstructions of the roads), we will not include it in our analysis. Compared to the

results obtained in the previous analysis (section 4.1), now we have add up theoretical

equivalents for the full road XIX, and we have modified the route between Bracara and

Asturica by introducing the intermediate node of Aquae Flaviae.

When comparing these new results with the known evidence of the roads, a greater

understanding of the network is obtained, though still not full (Figure 10, Table 4). The

route of the road XIX is highly coincident with the newly calculated LCP, with most of

the in situ indicators located less than 2 km from the theoretical optimal routes. The

coincidence between the LCP and the reconstructed road is not so determinant, but it is

very much influenced by the strong disagreement in the section between Iria and Lucus,

where again we find just a couple of in situ elements and the reconstruction is highly

speculative (compare Figure 1 and Figure 2). If we evaluate only the best known section

between Bracara and Iria, the similarity increases significantly (Table 4).

Figure 9. LCP between the regional capitals and the secondary settlements. In light yellow, the proposed reconstructions of the main roads (after Rodríguez Colmenero et al. 2004, see figure 2).

The results suggest that when defining the layout of the road XIX, the town of Iria was

among the primary nodes chosen. This means that it was were probably a crossing point

that were necessary in order to establish the layout of the roads; in other words, when

defining the road sections, Iria was a primary node through which the roads had to pass, a

primary node within the Roman communications network. The case of Tude is not so

clear if we only take into account the analysis shown here, since Tude might have been

established as an intermediate point on the way to Iria.

As regards the road between Bracara-Aquae Flaviae-Asturica (via XVII), we find again

that the coincidence between LCP and the road is very low, no matter how we measure it.

It is obvious that in this case we are still far from understanding the logic of this particular

road.

Figure 10. Histograms of distances between in situ indicators of Roman roads (milestones and bridges) and corresponding LCP for routes between Bracara-Tude-Iria-Lucus (top) and Bracara-Aquae Flaviae-Asturica (bottom).

Table 4. Similarity between LCP and the proposed route of the Roman roads.

So far, we have only considered settlements as the primary nodes to understand the road

network. We have seen that the road network was not only based on the three regional

capitals, but that towns originally considered to be secondary have been shown to be

primary nodes in this network. However, there is a good portion of the road network that

is still beyond our understanding. This applies especially to most of the via XVII and the

whole via XVIII (Figure 2).

Moving beyond the significance of settlements, we have looked for other types of spatial

features that could have acted as primary nodes. At this point, we could have involved

any type of geographical elements whose significance for mobility in the region we

wanted to test. Considering the geographical characteristics of the region, and the

available historical knowledge about it, we have proposed that crossing points of rivers

could have also played an essential role. Using these bridges as nodes in these analyses is

largely based a previous work (Fábrega-Álvarez and Parcero-Oubiña 2007) where the

key role of the crossing points for the main rivers as principal nodes in organising the

historical road network in this region was explored.

The location of a series of bridges of certain or likely Roman origin is known in the region

(see Figure 1). However, not all of them should be expected to have played an equivalent,

primary role. Actually, in principle a bridge is a device to allow the communication of

two external places, and not a place in itself to start from or arrive at. In fact, after some of

the analyses already made, the location of some of those bridges can be well understood

yet: crossing points placed within the LCP that were joining primary nodes (see for

instance the two bridges located in the LCP between Bracara and Lucus or the possible

Roman bridge in via XIX). The point here was to select which of those bridges could have

acted as primary nodes, which are in places that could be radically conditioning the

possibilities of movement.

Considering both the previous results (we are interested here in understanding those parts

of the network beyond explanation), the geographical characteristics of the region and the

material characteristics of the preserved bridges, we proposed to select one single bridge,

Ponte Bibei, as the new node to be explored. Ponte Bibei is one of the most monumental

Roman bridges in the region, and the only major one that is located out of a settlement

place.

The results allow to grasp a much better understanding of the network, especially of the

so far elusive via XVIII (Figure 11). Although there is still some divergence (as should be

expected and will be discussed in section 5), the new LCP route is rather coincident with

the alignment of the known remains of the road, as the quantification also show (Figure

12, Table 5). Although the coincidence between LCP and in situ indicators is rather high,

the comparison between LCP and the proposed original roads (Table 5) is not as high as

the map may suggest. Again, this is basically caused by the notable difference in the

section of the via XVIII near Asturica, where the reconstruction made by Rodriguez

Colmenero et al. (2004) proposes a noticeable, and debatable, detour.

Figure 11. LCP including Ponte Bibei (yellow star) as a primary node. In light yellow, the proposed reconstructions of the main roads (after Rodríguez Colmenero et al. 2004, see figure 2).

Figure 12. Histograms of distances between in situ indicators of Roman roads (milestones and bridges) and corresponding LCP for the route between Bracara-Ponte Bibei-Asturica (via XVIII).

Table 5. Similarity between LCP and the proposed route of the Roman road between Bracara-Ponte Bibei-Asturica (via XVIII).

So far, we have seen that an important part of the network can be understood as the

optimal routes linking the main settlement places of the Roman period (capitals and some

of the secondary settlements) and, in some parts, also considering bridges as primary

nodes. This is of great interest for our initial objectives: the exploration of the logic of the

roads, to what extent they impose a new landscape or reinterpret a pre-existing one.

However, evidence is still ambiguous: while the extensive coincidence of optimal

pedestrian routes with Roman roads might indicate the existence of previous

requirements for their design (the appropriation of existing pathways), the nodes

considered have all been chosen for their relevance in Roman times. So the question

remains of how new this layout is.

Some additional clues can be obtained if we look at the temporality of the evidence. If

those principal roads that we have explored are considered as an essential part of the

construction of a new landscape in the region from the very beginning of the Roman

period, the nodes considered in their construction must have been in operation since those

early times. We know for sure that the three capital towns, Bracara, Lucus and Asturica,

were founded soon after the end of the Roman conquest (beginning of 1st century AD). In

their turn, secondary settlements as Iria Flavia or Aquae Flaviae acquired only important

status as Roman settlements by the end of the 1st century AD (Pérez Losada 2002).

However, the analysis shown here illustrates that the geographical locations they occupy

must have been relevant places prior to that.

Figure 13. Distribution of milestones from the Julio-Claudian dynasty.

Actually, the distribution of milestones belonging to the period of the Julio-Claudian

dynasty (first two-thirds of the 1st century AD) reinforces that assumption (Figure 13): the

roads they are placed along are precisely those that lead to Iria and Aquae Flaviae, places

that don’t have a significance as Roman settlements until the Flavian period (last third of

the 1st century AD) (Pérez Losada 2000: 108-9, Fonseca 2012). And, as we have seen,

those routes can be largely understood as the optimal pedestrian routes linking those

points.

Many Roman sites might have appeared, or rather were established, in specific points in

the territory because they stood alongside the main roads in the Roman communication

network. But if places like Iria or Aquae Flaviae are not considered as pre-existent,

primary nodes, much of the road network we know today could not be understood.

The main aim of this study was to test a methodological approach based on the use of a

simple, well established GIS-based determination such as Least Cost Paths, to understand

rather than to predict some forms of mobility in the past. As has been shown, this

approach can provide interesting results when dealing with complex, highly formal

contexts for which a significant body of evidence is available, in the form of numerous

remains of ancient road networks.

It is important to remark that the proposed approach is not aimed at providing a

significant new knowledge (reconstructing) on the routes under analysis, in our case the

Roman roads of the NW Iberian Peninsula. In a different direction, it provides new clues

on what decisions could have been taken when constructing that network. The more

direct evidence we have about the actual route of the roads, the more significance we can

extract from such an approach.

In our case study, we have shown how a significant portion of the Roman road network in

this area can be understood in terms of least cost pedestrian routes joining a few key

nodes in the landscape. On the one hand, this suggests that the role of pedestrian mobility

was important when designing the road network. On the other hand, the results also

inform us about the significance as primary nodes of elements other than the settlement

sites. Specifically, the relevance of some crossing points over water has been detected.

This may be argued for some cases, while other are better understood as located along

pre-existing, or pre-designed, routes. Beyond the reconstruction of the possible routes of

the roads, our approach focuses on affordability, on the key, primary role for the

articulation of human mobility in this region of some specific geographical positions.

Even in such a complex and technologically advanced context as the Roman Empire, not

only political and administrative criteria would have operated when designing such a

crucial element in the construction of a new landscape as the road network. This is

probably not any different to what has been already concluded, proposed or sometimes

just assumed from different archaeological approaches, but our contribution here, based

on a totally different argumentation, helps to understand some of the logics behind that.

The analysis also provides relevant arguments for the discussion proposed at the

beginning, focused on the possible re-use of pre-Roman roads in designing this road

network in Roman times (Caamaño Gesto 1980, González Ruibal 2001), something that

has been argued for elsewhere in Europe (e.g. Chevalier 1997). In this case the primary

role of some settlement sites, such as Iria Flavia or Aquae Flaviae, seems rather obvious

from the very beginning of the construction of the network. However, this contrasts with

the apparently late development of these places as truly relevant settlement areas. All the

former suggests that those places were already significant nodes in terms of mobility in

this region well before their emergence as focal Roman sites, and supports the suggestion

that, to a great extent, the Roman road network was here the formalization of already

existing routes.

It is also evident that the approach presented here does not fully explain the road network,

and in full detail. Regarding the lack of detail, in most cases the divergence when

measuring the similarity between the LCP, the milestones and the proposed

reconstruction of the roads might be related to an issue of scale (see for instance the via

XVIII), but in a few specific cases it might also have to do with the proposals by our main

source (Rodríguez Colmenero et al. 2004) about the assignation of milestones to specific

roads or the suggested routes of the roads where little direct evidence is available. But in

other cases the divergence is more radical. The most obvious case is that of the via XVII,

which to a great extent cannot be “explained” with the evidence we presented here. It may

be the case that, as happened with the via XVIII and Ponte Bibei, some additional primary

nodes have existed in the region between Aquae Flaviae and Asturica that forced the road

to follow a route other than the optimal pedestrian least cost path. Or we could also

consider that maybe not all the roads were following the same logic. The search for

possible additional nodes in this area, or the testing of different cost functions (maybe

those designed to model optimal movement of wheeled vehicles) could shed some light

on this particular matter. For the specific case of the road between Bracara and Asturica it

is also possible that avoiding high altitude areas was a relevant factor. Although some

other sections of the network cut across mountain ranges (for instance, between Lucus

and Asturica), this factor could be relevant to find an alternate logic for this particular

case.

It must also be taken into account that our approach here was made on a very general

scale, and consequently the results are only valid at that regional scale. What we have

explored is the correspondence between roads and general corridors of least cost

movement. An analysis made on a much smaller scale and for specific parts of the

network could provide a more detailed understanding based on the determination of

theoretical paths rather than on broad-brush corridors.

In methodological terms, our experience here has also shown that, considered at this scale

and for this particular topographic conditions, the results produced by the two cost

functions are highly coincident for the most part, save for some specific areas, and even in

those cases the differences do not imply major changes in the general direction of the

paths (again, the area between Aquae Flaviae and Asturica Augusta is the one that shows

the greatest difference and the sole area where the two LCP are actually showing different

routes at our scale of analysis).

The approach presented here is technically and methodologically rather simple and

straightforward, and as such it may be easily extended to any equivalent archaeological

context. Instead of “joining the dots”, a focus on the opposite “dotting the joins” may be a

useful way to inject some meaning in the abundant remains of ancient roads.

We would like to thank the very useful comments and suggestions by the reviewers of the

paper, 2 anonymous colleagues and -very especially- Irmela Herzog, who waived her

anonymity, for her very thorough and constructive comments and suggestions. We would

also like to thank A. González Ruibal for providing useful comments on a previous

version of this paper. This research has been partially supported by an 'Isabel Barreto'

grant from the Galician regional government (Xunta de Galicia).

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