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ISSN: 1133-598X
eISSN: 2341-1112
Vol. 23, Nº1
(2023)
Vol. 23 Núm. 1 • 2023 • D.L.: GC1206-1214
ISSN: 1133-598X • eISSN: 2341-1112
https://doi.org/10.51349/veg
Periodicidad: Semestral
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Vol. 23 Núm. 1 • 2023 • D.L.: GC1206-1214
ISSN: 1133-598X • eISSN: 2341-1112
https://doi.org/10.51349/veg
Periodicidad: Semestral
EQUIPO EDITORIAL / EDITORIAL BOARD
Dirección / Editor in Chief
María del Cristo González Marrero (ULPGC,
España)
Manuel Ramírez-Sánchez (ULPGC, España)
Secretaría / Deputy Editor in Chief
Antonio Hernández Cordero (ULPGC, España)
Consejo de Redacción / Editorial Board
Antonio Castillo Gómez (U. de Alcalá, España)
Pedro Javier Dorta Antequera (U. de La Laguna,
España)
Laura Mariateressa Durante (U. degli Studi di Napoli
Federico II, Italia)
Antonio Carlos Gaeta (U. Estadual Paulista, São
Paulo, Brasil)
María Victoria Marzol Jaén (U. de La Laguna,
España)
Gonzalo Pasamar Alzuria (U. de Zaragoza, España)
Purificación Ruiz Flaño (U. de Valladolid, España)
Enrica Salvatori (U. di Pisa, Italia)
María Teresa Sánchez Salazar (U. Nacional
Autónoma de México, México)
Juan Manuel Santana Pérez (ULPGC, España)
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Consejo Asesor / Advisory Board
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Youssef Bokbot (Institut National des Sciences de
l’Archéologie et du Patrimoine, Maruecos)
João Manuel de Lemos Baptista (U. de Aveiro,
Portugal)
Francisco Comín Comín (U. de Alcalá, España)
Heriberto Cruz Solís (U. de Guadalajara, México)
Jean Marc Delaunay (Université Sorbonne Nouvelle -
Paris 3, Francia)
Carmen Fraga González (U. de La Laguna, España)
Mauro S. Hernández Pérez (U. de Alicante, España)
Paloma Ibarra Benlloch (U. de Zaragoza, España)
Carlos Martínez Shaw (U. Nacional de Educación a
Distancia, España)
María Montserrat Gárate Ojanguren (U. del País
Vasco, España
Francisco M. Gimeno Blay (U. de Valencia,
España)
José Ojeda Zújar (U. de Sevilla, España) Ascensión
Padilla Blanco (U. de Alicante, España)
Ramón Pérez González (U. de La Laguna, España)
Horst Pietschmann (Universität Hamburg,
Alemania)
Xavier Pons Fernández (U. Autónoma de Barcelona,
España)
Enrique Propín Frejomil (U. Nacional Autónoma de
México, México)
Carlos Reyero Hermosilla (U. Autónoma de Madrid,
España)
Reinaldo Rojas (U. Pedagógica Experimental
Libertador, Venezuela)
José Manuel Rubio Recio (U. de Sevilla, España)
Pere Salvá Tomàs (U. de les Illes Balears, España)
Jean Stubbs, Institute of the Americas (U. College
London, Reino Unido)
Editor traducción inglés / English Translation
Editor
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Edición / Edition
Facultad de Geografía e Historia de la Universidad
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© 2023 ULPGC. Los originales de los textos publicados en la revista Vegueta, edición impresa y electrónica,
son propiedad de la Universidad de Las Palmas de Gran Canaria y se encuentra en acceso abierto, distribuidos
bajo los términos de la licencia Creative Commons Atribución-NoComercial-SinDerivar (by-nc-sd) Spain 3.0,
siendo necesario citar la procedencia en cualquier reproducción parcial o total del contenido.
Vol. 23 Núm. 1 • 2023 • D.L.: GC1206-1214
ISSN: 1133-598X • eISSN: 2341-1112
https://doi.org/10.51349/veg
Periodicidad: Semestral
SUMARIO / SUMMARY
Dossier: Modelizaciones computacionales para la comprensión de fenómenos históricos y sociales /
Computational Modelling for Understanding Historical and Social Phenomena
ALFREDO CORTELL-NICOLAU, SALVADOR PARDO-GORDÓ: Presentación / Presentation 9-14
ANDREAS ANGOURAKIS: El lugar de la simulación social en arqueología / The Role of Social Simulation in
Archaeology 15-55
MICHAEL KEMPF, ELI J. S. WEAVERDYCK: Modelling Bias and Environmental Preferences in Archaeological
Spatial Analysis / Sesgo de modelado y preferencias ambientales en el análisis espacial arqueológico
57-95
MIGUEL CARRERO PAZOS: Análisis de patrones espaciales de puntos para el estudio de tendencias locacionales
en distribuciones de yacimientos arqueológicos / Spatial Point Pattern Analyses for the Study of Locational
Trends in Archaeological Site Distributions 97-114
CARLOS RODRÍGUEZ-RELLÁN, RAMÓN FÁBREGAS VALCARCE: Assessing the Perceptibility of Prehistoric
Monuments on their Landscape. An Exploratory Approach Using Agent-Based Modelling / Evaluación de la
perceptibilidad en el paisaje de los monumentos prehistóricos. Un enfoque exploratorio por medio de la
modelización basada en agentes 115-145
OLGA PALACIOS MARTÍNEZ: Aplicación del aprendizaje automático en Arqueología: ¿Un cambio de
paradigma? / The Application of Machine Learning to Archaeology: A Paradigm Shift? 147-186
IVAN GIRONÈS ROFES, MIQUEL MOLIST MONTAÑA : Palimpsestos, colecciones descontextualizadas y la
estadística bayesiana: un punto de encuentro / Palimpsests, Decontextualised Collections and Bayesian
Statistics: A Meeting Point 187-241
SALVADOR PARDO-GORDÓ, ALFREDO CORTELL-NICOLAU : ¿Falta de concienciación o desconocimiento? La
transparencia y la reproducibilidad en la Arqueología Computacional / Lack of Awareness or Lack of
Knowledge? Transparency and Reproducibility in Computational Archaeology 243-263
Estudios / Studies
ADRIÁN CALONGE MIRANDA: Hispania en el Imperio Galo de la sublevación de Póstumo a la restauración del
Imperio con Aureliano a la luz de la epigrafía ¿Una frontera en el Ebro Medio? / Hispania in the Gallic
Empire in the Light of Epigraphy, from Postumus’s Uprising to Aurelian’s Restoration of the Empire: A
Border in the Middle Ebro? 267-288
FERNANDO R. CONTRERAS MEDINA, MAR RAMÍREZ ALVARADO, ALBA MARÍN: Estudio exploratorio sobre el
Régimen Escópico del Chavismo en Venezuela / Exploratory Study of the Scopic Regime of Chavismo in
Venezuela 289-314
RAFAEL ESCOBEDO ROMERO: La España franquista y la prensa católica estadounidense durante la Segunda
Guerra Mundial / Francoist Spain and the American Catholic Press during World War II 315-343
Vol. 23 Núm. 1 • 2023 • D.L.: GC1206-1214
ISSN: 1133-598X • eISSN: 2341-1112
https://doi.org/10.51349/veg
Periodicidad: Semestral
JORGE FERNÀNDEZ GONZÀLEZ: Fernando González, más allá del poeta. Una trayectoria truncada por la
represión franquista al profesorado / Fernando González Beyond his Poetry: A Career Frustrated by the
Francoist Repression of Teachers 345-367
PABLO ALBERTO MESTRE NAVAS: Los sellos diplomáticos de los cabildos catedrales andaluces (s. XIII):
Función, custodia e identidad / Diplomatic Seals of the Andalusian Cathedral Chapters During the 13th
Century: Function, Custody and Identity 369-394
JUAN PEDRO NAVARRO MARTÍNEZ: Las «imperfectas»: mujeres acusadas y víctimas del crimen de sodomía ante
la justicia ordinaria hispánica en el Antiguo Régimen / The “Imperfect Ones”: Women Victims Accused of the
Crime of Sodomy in Spanish Ordinary Justice During the Old Regime 395-421
VÍCTOR PEÑA GONZÁLEZ, MARIO ROSANO ALLOZA, JULIO PÉREZ SERRANO : «Comunistas y punto». Una
aportación al debate sobre la ortodoxia en el comunismo español, 1968–1989 / “Communists and That’s It”:
A Contribution to the Debate on Orthodoxy in Spanish Communism, 1968–1989 423-445
ROCÍO POSTIGO-RUIZ: Prepararse para morir en la Sevilla bajomedieval. Testamentos y dotaciones de
capellanía (1371–1474) / Preparing to Die in Late Medieval Seville: Testaments and Endowments (1371–
1474) 447-476
PAOLA SILVIA RAMUNDO: La cartografía arqueológica de la quebrada de La Cueva (Humahuaca, Jujuy,
Argentina) como herramienta para el estudio de la historia disciplinar / Archaeological Cartography of La
Cueva Gorge (Humahuaca, Jujuy, Argentina) as a Tool for the Study of Disciplinary History 477-509
VÍCTOR DANIEL REGALADO GONZÁLEZ-SERNA: Implantación de las canonjías de oficio en la hispalense iglesia
colegial del Salvador (1807) / The Establishment of Trade Canonries in the Sevillian Collegiate Church of the
Saviour (1807) 511-526
RAÚL ROMERO MEDINA: Retórica de la imposición del Toisón de Oro en tiempos de Felipe IV: ritual, símbolos
y espacios para la ceremonia del V marqués de Priego / Rhetoric of Imposition of the Golden Fleece During
the Reign of Philip IV: Ritual, Symbols and Spaces in the Ceremony of the Fifth Marquess of Priego 527-554
Reseñas / Reviews
VALERIA AGUIAR BOBET, MANUEL DE PAZ SÁNCHEZ : José Antonio Ferrer Benimeli, La masonería hispana y
sus luchas democráticas. Sueños de libertad, Editorial Masónica, Oviedo, 2022, 493 págs., ISBN: 978-84-
19044-27-3 557-560
ANNE DUBET: Sergio Solbes Ferri y Daniel Castillo Hidalgo, La diferencia Insular. El modelo fiscal de
Canarias en perspectiva histórica. El Antiguo Régimen: La Real Hacienda y el proceso de construcción del
Estado, Tirant lo Blanch, Valencia, 2022, 348 págs., ISBN : 978-84-1397-979-3 561-567
JOSÉ JOAQUÍN QUESADA QUESADA: Francisco José Pérez-Schmid Fernández y Adolfo Hamer Flores (coord.),
Colonias y colonizaciones agrícolas en la España Moderna y Contemporánea. Nuevas miradas y
aportaciones, Fundación Caja Rural de Jaén, La Carolina, 2022, 206 págs., ISBN: 978-84-124267-5-5
569-571
115
Copyright: © 2023 ULPGC. Este es un artículo de acceso abierto distribuido bajo los términos
de la licencia Creative Commons Atribución-NoComercial-SinDerivar (by-nc-nd) Spain 3.0.
Vegueta. Anuario de la Facultad de Geografía e Historia
23 (1), 2023, 115-145
eISSN: 2341-1112
https://doi.org/10.51349/veg.2023.1.05
Assessing the Perceptibility of Prehistoric Monuments on their
Landscape. An Exploratory Approach Using Agent-Based Modelling
Evaluación de la perceptibilidad en el paisaje de los monumentos prehistóricos.
Un enfoque exploratorio por medio de la modelización basada en agentes
Carlos Rodríguez-Rellán∗
Universidad de Granada
Departamento de Prehistoria y Arqueología
https://orcid.org/0000-0001-5884-6592
carlos.rellan@ugr.es
Ramón Fábregas Valcarce
Universidade de Santiago de Compostela
Departamento de Historia
https://orcid.org/0000-0002-7940-6884
ramon.fabregas@usc.es
Enviado: 12/08/2022; Revisado: 11/12/2022; Aceptado: 22/12/2022
Abstract
The perceptibility of a prehistoric monument (the property of being perceptible from its surrounding
landscape) can be quite difcult to analyse by means of traditional static models. Such difculty lies
in the fact that perceptibility depends upon many other factors beyond simple topographical position,
such as size, colour, contrast with the surroundings or even the specic circumstances of the audience,
many such circumstances being of an immaterial nature. In this paper, we explore the potential use of
Agent-Based Modelling for the analysis of archaeological perceptibility.
Keywords: Late Prehistory, NW Iberia, Rock Art, Mounds, Visibility.
* Corresponding author / Autor de correspondencia.
Vegueta, 23 (1), 2023, 115-145. eISSN: 2341-1112
Assegin the Perceptibility of Prehistoric Monuments on their Landscape
116116116
Resumen
La perceptibilidad de un monumento prehistórico (la propiedad que este tiene de ser divisado
desde el paisaje circundante) puede resultar bastante difícil de analizar a partir de modelos estáticos
tradicionales. Tal dicultad reside en el hecho de que la perceptibilidad depende de muchos otros
factores además de la posición topográca, como el tamaño, color, contraste con el entorno o incluso
las circunstancias especícas de la audiencia, muchas de ellas de naturaleza inmaterial. En este trabajo,
exploraremos el potencial uso del Modelado Basado en Agentes para el análisis de la perceptibilidad
arqueológica.
Palabras clave: Prehistoria Reciente, NO de Iberia, arte rupestre, túmulos, visibilidad.
1. INTRODUCTION
Galicia –located in the Northwest of the Iberian Peninsula– is a territory
of little more than 29500 km2 where a rich archaeological heritage is preserved,
including a minimum of 3400 open-air rock art sites (RodRíguez, Vázquez and
FábRegas, 2018) and 3300 prehistoric mounds (CaRReRo-Pazos, 2019; Fig. 1).
These monuments were mainly built/engraved between the Neolithic and the
Early Bronze Age (second half of the 4th millennium and beginning of the 2nd
millennium BC).
Figure 1. Location of Galicia and general distribution of mounds and rock art sites.
Carlos Rodríguez-Rellán y Ramón Fábregas Valcarce
Vegueta, 23 (1), 2023, 115-145. eISSN: 2341-1112 117
The relevance of Landscape Archaeology among Galician researchers
(CRiado, 1989; CRiado and VilloCh, 1998), combined with the huge impact of
foreign scholars doing eldwork there (bRadley, 1997; bRadley, CRiado and
FábRegas, 1994), has led to the production –from the 1980s onwards– of many
studies exploring the distribution of mounds and petroglyphs across the region.
In most of these approaches, prehistoric monuments have been interpreted as
nodes connected to each other through routes retraceable by means of eld work
(CRiado and VilloCh, 2000), the analysis of mobility patterns of animals (inFante,
VaqueRo and CRiado, 1992), the layout of historical routes (PaRCeRo, CRiado and
santos,1998) and –in recent years– through the calculation of least-cost paths
using GIS tools (CaRReRo-Pazos, beVan and lake, 2019; CaRReRo-Pazos et al.,
2020; FábRega-álVaRez and PaRCeRo-oubiña, 2007; RodRíguez and FábRegas, 2015;
RodRíguez-Rellán and FábRegas, 2017).
The reasons behind this alleged connection between prehistoric monuments
and what has sometimes been labeled as “geography of movement” (CRiado and
VilloCh, 2000; InFante, VaqueRo and CRiado, 1992) derives from the fact that, within
the theoretical framework of most of these studies, monuments are considered to
act as a kind of normative mechanism of land tenure (bRadley, 1997). In addition to
other purposes, mounds and petroglyphs would have allowed still quite itinerant
farmer communities to negotiate their own identity and place in the world as well
as to manage preferential and/or exclusive access to areas of economic and/or
symbolic signicance (bRadley, 1997; CasimiR, 1992; ingold, 1987).
The interaction between Galician monuments and the prehistoric
landscape has been traditionally understood in terms of four specic variables:
monumentality (usually equated to size), location (closeness/remoteness to a
given spot), intensity (uneven density of monuments), and visual control (visual
command over a specic place). Theoretically, the analysis of how these variables
interact with each other would allow the archaeologists to understand how
relevant a specic set of monuments was within the prehistoric landscape.
Another variable has received much less attention but is still essential for
understanding the role of monuments in shaping the prehistoric landscapes,
namely their perceptibility.
1.1. Visibility and perceptibility of archaeological features
From a semantic point of view, both visibility and perceptibility are almost
synonymous, the former being dened as “the capacity of being seen” while the
latter is “the state or property of being perceptible”, that is “able to be seen or
noticed” (steVenson, 2010). However, in spatial analysis applied to Archaeology,
visibility has gradually adopted a univocal meaning equivalent to the result of
the viewshed analysis, which is generally carried out from an archaeological site
towards its surroundings (Wheatley and gillings, 2000).
This may cause some confusion on the very few occasions when this term has
been used “in the opposite direction”, that is, to dene the area of the surrounding
Vegueta, 23 (1), 2023, 115-145. eISSN: 2341-1112118
Assegin the Perceptibility of Prehistoric Monuments on their Landscape
landscape from which a given site is noticeable. More importantly, visibility and
perceptibility refer to two different dynamics that –if misunderstood– can lead to
signicant mistakes. Most readers have probably experienced during eldwork
that an archaeological site can be potentially visible (it is located within our eld of
vision), but still not be perceptible (we are not able to notice its presence). Taking
these subtle but important differences into account, we have been advocating for
the need to clarify when we intend to calculate visibility and when perceptibility,
avoiding the interchangeable use of both terms (RodRíguez, 2016; RodRíguez-
Rellán and FábRegas, 2017).
Back to Galician mounds and petroglyphs, the consideration of whether, how
much and from where these monuments would have been perceived has been
unevenly present in the literature. Being linked to the “geography of movement”,
it has been assumed –somewhat uncritically– that most mounds and rock art
sites would be easily perceptible from the surrounding landscape and, more
importantly, from the routes and paths along which prehistoric communities
would have moved.
Regarding mounds, some authors have suggested that prehistoric
communities would have sought to modulate the perceptibility of such monuments
by choosing whether to build them in visually prominent areas which would
make them conspicuous (by standing out against the horizon) or –conversely–
restricting their noticeability to certain spaces (llobeRa, 2015; RodRíguez, 2016;
RodRíguez-Rellán and FábRegas, 2017). Other ways of enhancing perceptibility
would have been, for example, the use of specic building materials (e.g., quartz
cobbles and other shining stones) to increase the contrast between the monument
and its background (bRadley et al., 2000; tilley, 1996). Alas, this would have
implied some kind of “maintenance”, since the vegetation would have quickly
claimed its place over the monument, thereby decreasing its perceptibility.
Being in the open and easily accessible from the small fertile valleys and
coastal platforms where most domestic sites would be located, Galician rock
art has been considered a phenomenon whose contemplation would be little
restricted, especially when compared to megalithic and schematic art (located in
the walls of small burial chambers or in inaccessible caves, rock shelters and cliffs)
(bRadley, 2002; 2009). This would have undoubtedly reected the type of audience
to which petroglyphs would have been intended. Since “these rock carvings were
readily accessible and were created in places which more people would have been
able to visit”, then ”they could have been visited by large numbers of people
had they wished to do so” (bRadley, 2002: 239-240), including maybe (and this is
quite important) the members of neighboring –and perhaps rival– communities.
It would follow that petroglyphs, much like burial mounds, could have acted as
“inter-group” references, therefore having the potential to become a signicant
player in the denition and negotiation of prehistoric territories.
Subsequent research has shown the need to qualify, at least partially, some
of these conclusions. The discovery of petroglyphs inside small rock-shelters or
tafoni where there is barely room for one or two people clearly shows that in
Galician rock art too there seems to have been the wish to conceal specic sites
Carlos Rodríguez-Rellán y Ramón Fábregas Valcarce
Vegueta, 23 (1), 2023, 115-145. eISSN: 2341-1112 119
from the public eye (FábRegas and RodRíguez, 2012b). The question then arises
as to whether there were mechanisms that made it possible to modulate the
perceptibility of rock art sites located outdoors, making them accessible or not to
specic types of audiences.
R. Bradley –who has undoubtedly produced the most compelling reections
on the audience of Galician rock art– while claiming that the petroglyphs would
be easily accessible to large numbers of people, also stated that “it is impossible to
say whether everyone was allowed to view these pictures” (bRadley, 2002: 240),
recognizing the possibility that there may have been physical and/or immaterial
barriers that would have made it difcult for certain individuals or groups to
access the engravings.
The rst and perhaps most obvious of these barriers is remoteness, with the
more distant petroglyphs being interpreted as those that would be intended for
a more restricted audience, since it would have required signicant knowledge
of the terrain to be able to reach them (bRadley, 1997; 2002). The characteristics of
the engraved rock were probably also important: the choice of large, conspicuous
rocks or vertical panels has been understood as a desire to make the engravings
more perceptible (de la Peña santos and Rey gaRCía, 2001), whereas the selection
of small, ground-level rocks or horizontal panels would have had the opposite
effect.
Other variables, which would undoubtedly have affected the perceptibility
of the engravings, have been systematically ignored. Leaving aside the –presently
unproven– possibility of petroglyphs being also painted, carving a dark-colored
rock (dark gray to black) would cause a sharp contrast with the freshly made
grooves (white to light gray), making them much more perceptible. However,
it would be necessary to refresh the grooves from time to time to prevent such
contrast from fading. Conversely, the selection of light-toned rocks and shallow
groves would have made it difcult to identify the carvings even from a few steps
away.
The perception of the motifs may also have depended on light conditions.
In those petroglyphs where there is little contrast between carvings and rock
surface, perception is highly dependent on the incidence of sunlight. Thus, a
petroglyph can be practically invisible when observed at noon and fully revealed
in the light of dawn or dusk. Other atmospheric factors (i.e., rain) may have an
inuence as well (FábRegas and RodRíguez-Rellán, 2015). As such, knowing the
optimal conditions for observing a petroglyph may have been as insurmountable
a barrier to their perception as it was knowing their location.
Finally, it is important to keep in mind that the capacity of being noticed is not
entirely (or even mainly) based on physical factors: the social or ritual signicance
of a specic monument might have multiplied its perceptibility, regardless of its
remoteness or size (RodRíguez-Rellán and FábRegas, 2017).
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1.2. GIS approaches to perceptibility of archaeological sites
Prior to the widespread use of computers, the perceptibility of prehistoric
monuments was analyzed in a somewhat impressionistic manner, based mainly
upon personal experience gained during eldwork. However, since these
assessments were extremely time-consuming, they were usually conducted in an
unsystematic way. As such, the results were little more than a rule of thumb (a
general threshold beyond which a specic set of monuments of a given region
were no longer noticeable) and they could hardly be applied to other regions and
sites.
With the generalization of Geographic Information Systems (GIS), this
type of analysis became much easier to implement and, as a result, it began to
increase in popularity. However, this brought a whole new set of problems. Most
approaches used the standard tools available in GIS suites: line-of-sight and
binary viewsheds. As other authors have already noted (gaFFney and leusen,
1995; gillings et al., 2000), such tools only take into consideration as limiting
factors for visibility the characteristics of the terrain and, optionally, the curvature
of the Earth, atmospheric refraction, etc. However, they do not account for other,
equally important aspects when determining whether a structure or object is
perceptible from afar, such as its size, color, contrast with the background, etc.
Being aware of this problem, several studies have sought to address the
limitations of the traditional viewshed computations in different ways. The rst
group of them are based on a similar concept: those areas more noticeable from
the surroundings are more likely to have acted as landmarks and, therefore,
might have played a signicant role within the cognitive and symbolic geography
of the human groups living nearby. A recurrent setting of archaeological sites in
those conspicuous areas might imply that these were purposely built/engraved
in those places so they might have had a higher chance of being noticed (llobeRa,
2003; 2006). These simulations are based on the calculation of either a cumulative
viewshed for a signicant number of points distributed across the area of interest,
or by the calculation of a total viewshed, in which a viewshed analysis is conducted
for each of the cells in the study area.
In former studies (RodRíguez, 2016; RodRíguez-Rellán and FábRegas, 2017),
we have conducted a variant of this approach based on the calculation of the
cumulative viewsheds from corridors composed of several thousands of least-
cost paths. The logic behind this is that, were the mounds and petroglyphs related
to the “geography of movement”, they would be primarily located at spots
especially noticeable from the routes along which prehistoric communities would
have moved.
The other family of GIS approaches to modeling perceptibility are those
that consider the characteristics of objects or structures to be noticed, such as –
for example– size. All these approximations are distance-dependent, focusing on
dening the limits or ranges beyond which an object, despite being within our
eld of view, would cease to be noticeable. The rst of these approaches is based
on the works by T. Higuchi. The so-called “Higuchi viewshed” decomposes the
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traditional binary viewshed into three ranges (short-distance, middle-distance
and long-distance view), calculated according to the average high of the trees
existing in the area (for a more detailed description, see Wheatley and gillings,
2000: 15-19).
D. Ogburn criticized the use of Higuchi’s approach on the grounds that
a method based on the characteristics of natural elements (trees) has little
applicability to man-made structures (ogbuRn, 2006). Instead, Ogburn proposed
to apply a distance decay function to generate “Fuzzy viewsheds”. These would
represent the degree (ranging from 1 –clearly visible– to 0 –non visible–) to
which an object is clearly perceptible from a given point. Ogburn also proposed
a modied version of this method which takes into consideration the size of the
target by calculating the distance from which the perceived size of a given item
(measured in degrees, minutes, and seconds of the visual angle) is less than the
limits of the human visual acuity (usually 1 arc minute for a perfect vision).
Also based on the visual angle occupied by a monument (in this case
barrows), M. Llobera dened four different ranges around it: Not relevant (0.5 <
VA < 0.1º); Background (0.1 < VA < 0.5º); Middle-ground (0.5 < VA < 15º) and
Foreground (VA > 15º). Each of these areas would have the potential to serve as
stage for different activities (communal processions, feasting…) (llobeRa, 2007).
Finally, P. Fábrega and C. Parcero created both a regular and a fuzzy version
of what they called an “Individual Distance Viewshed”. This method was
intended to calculate “the visible area from a given location that falls within a
distance where the presence of a human being can be perceived and recognized
in different ways” (FábRega-álVaRez and PaRCeRo-oubiña, 2019: 64). What is
genuinely novel about this approach is the fact that the thresholds were dened
based on ad hoc experiments with real subjects, who were instructed to recognize
other individuals walking towards their location.
As we have just seen, the solutions applied in GIS to model the perceptibility
of archaeological features have become progressively more complex, overcoming
some of the limitations of standard approaches. However, these solutions are still
limited by their static nature and by the fact that they can handle only a small
number of variables at a time (one of them being the distance between the target
and the observer). In addition, GIS approaches to past landscapes have difculties
when handling immaterial aspects that undoubtedly would have affected the
relationship of prehistoric communities with the landscape.
In this paper, we will explore the potential role of Agent-based Modelling
(ABM) in tackling some of the aspects affecting the perceptibility of archaeological
features that –due to their complexity– are difcult to handle by means of static
models such as those built in GIS environments. For this, we have designed a
simple ABM model aimed to observe the interaction between mobile agents
pretending to be prehistoric people walking around the landscape (walkers) and
specic monuments (mounds and petroglyphs). The main objectives are: a) to
determine whether ABM can be a potentially interesting tool for analyzing the
interaction between prehistoric monuments and people; b) trying to measure
the intensity of such interaction and how different variables (both material and
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intangible) would have inuenced it.
2. METHODOLOGY
2.1. Study area
The area chosen for carrying out the analyses shown in this article is the
Barbanza Peninsula (A Coruña, Spain; Fig. 2). This is the northernmost of the
peninsulas that make up the Rías Baixas, deep sea-inlets in the SW coast of Galicia
(NW Spain). Following a NE-SW orientation, its main geographical feature is the
Serra da Barbanza, a horst structure with an average altitude of 550 m.a.s.l. whose
upper part is comprised of small plateaus separated by ridges and gentle hills and
crossed by several small river valleys. The Serra is surrounded by a rather narrow
coastal plain where settlement and farming areas are concentrated nowadays. The
transition between these two areas (the Serra and the coastal plain) is composed
of slopes that can reach very steep gradients.
Figure 2. Barbanza Peninsula with the location of the catalogued mounds and
petroglyphs.
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The Barbanza Peninsula is known for the important presence of megalithic
burial mounds. Nowadays, a total of 223 mounds are known, although it is
quite possible that their original number has been reduced by the destruction
due to agricultural intensication and urban development (bustelo et al., 2017;
RodRíguez-Rellán and FábRegas, 2017).
As elsewhere in Galicia, the Barbanza mounds are relatively small, especially
when compared to those of other European regions. Most monuments have a
maximum diameter of between 12 and 25 meters, with extreme values reaching
8 and 32 meters. The height is usually ranging between 0.5 and 2.5 meters, again
with extreme values reaching 0.3 and 3.5 meters. However, it should be noted
that such numbers are greatly affected by erosion and other post-depositional
alterations. Likewise, although it is very difcult to ascertain their exact number,
it is very likely that a high percentage of mounds in this area had cuirasses, an
external layer of stones –generally granite and quartz– covering the earthen
mound.
Regarding the rock art sites, a total of 348 petroglyphs are known nowadays
in the Barbanza Peninsula. These display mainly geometric motifs (cup-marks,
cup and rings…), but the presence of naturalistic representations (deer and other
animals, human gures, weapons…) is also relevant (FábRegas and RodRíguez,
2012a; RodRíguez, Vázquez and FábRegas, 2018). Images seldom exceed 0.3 m. in
size, although there are some deer depictions as tall as 1.5 m. and cup and rings
exceeding 0.6 m. in diameter. The average depth of these engravings is around 0.5
cm, with only very few examples exceeding 2 cm.
Nearly all the petroglyphs are found engraved on granite. Although we do
not have information available for the whole Barbanza, the study we carried out
on 164 petroglyphs in the North half of the Peninsula clearly showed that most
engravings were located on at, inconspicuous rocks that are barely visible a few
meters away (FábRegas and RodRíguez, 2012a; RodRíguez, 2016). In the study area,
the size of the engraved rocks rarely exceeds 4.5 meters.
2.2. An exploratory Agent-Based Modeling approach to perceptibility
Agent-Based Modeling (ABM) is a type of computational simulation that
makes it possible to model complex systems. It focuses on the creation of a system
composed of heterogeneous, autonomous individuals (agents) interacting with
each other and with their virtual environment.
Agents can represent any type of entity –whether individual (persons,
viruses, ants, petroglyphs, mounds…) or collective (households, settlements,
cities…)– who can have specic properties (location, size, velocity, memory…).
ABM models usually are spatially explicit: they have a structure that species
the location of each agent within a virtual, heterogeneous environment. This can
be an abstract rendering (i.e., a quadrangular, blank space) or a semi-realistic
representation of a real-world space (i.e., a simplied representation of our study
area). These virtual environments are made of patches, stationary agents which
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can have specic properties (i.e., land, sea, forest, productive capacity, altitude...).
To some extent, one can think of patches as pixels in a raster map.
In addition to being spatially explicit, ABM models are dynamic. In other
words, they can manage processes that unfold over time (RomanoWska, WRen
and CRabtRee, 2021). Thus, the outcomes of the interactions taking place within
a system at time x (tick), may impact the subsequent development of the model
at time n (i.e., an agent can learn from its present interactions and modify its
future behavior based on them). This feature allows us “to move beyond a
static snapshot of the system” (what GIS approaches generally offer) towards “a
dynamic understanding of the system’s behavior” (Wilensky and Rand, 2015: 55).
The interactions between agents (or between agents and the environment)
are governed by a set of behavioral rules that are established during the
implementation of the model. These individual interactions within the system
can lead to the emergence of complex, global patterns which –although generally
intuitive– are rarely predictable (RomanoWska, WRen and CRabtRee, 2021; Wilensky
and Rand, 2015).
To some extent, ABM models can be considered as in silico experiments that
“provide a way to examine the contingencies of history, to test our assumptions
about the dynamics that governed these systems, and to investigate how individual
interactions lead to chains of consequences that produce observable facts”
(RomanoWska, WRen and CRabtRee, 2021: 8). Within this theoretical framework,
archaeologists can act as social scientists, testing and refuting hypotheses,
examining alternative scenarios, and selecting the ones whose results are in
better agreement with those detected in the archaeological record. To achieve
the objectives established for this paper, we have designed an ABM model using
NetLogo (Wilensky, 1999).
2.2.1. Designing the world
As an environment for the simulation, we created a semi-realistic version of
the Barbanza Peninsula (Fig. 3) in which several features were included:
- Land and sea: since our study area is a peninsula surrounded by water,
we have distinguished between “land” and “sea” patches, allowing the agents
(walkers, petroglyphs, and mounds) to interact only on land.
- Least-cost path routes: since we have not considered altitude, slope, and
other topographic features of our study area, we intended to maintain a certain
degree of realism in the movement of the agents through the landscape. For this,
we limited their movement to corridors created from the aggregation of least-cost
paths (LCPs). Although there are approaches that show the potential of ABM for
simulating the generation of LCPs (Gravel-Miguel and Wren, 2018), we chose to
calculate them directly in GRASS GIS to keep the model as simple as possible and
reduce the computational cost of the simulation.
Thus, we created a LCPs network composed of 250 paths linking different
areas of the Barbanza Peninsula (Fig. 5). First, we used the module r.walk for
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calculating the anisotropic cumulative cost of moving along the landscape taking
into consideration altitude, slope, and water accumulation (to hinder transit
through rivers and wetlands). Subsequently, we calculated the routes using the
module r.drain and establishing those places that the archaeological evidence has
shown to be the most probable settlement areas as origin and destination. The
coincidence of the LCPs with some of the historical routes that cross the Barbanza
Peninsula (FábRegas ValCaRCe et al., 2018) suggests that the simulated paths are
representative of the actual mobility strategies developed by the communities
who inhabited the study area in the past.
Figure 3. Interface of the Agent-based model implemented for this article.
2.2.2. Choosing the protagonists
Three different types of agents were created for this model: walkers,
petroglyphs, and mounds.
As their name suggests, “walkers” are the only agents in the simulation with
the ability to move. These are intended to simulate human individuals walking
through the landscape. Some of their major characteristics are:
- Number: up to 150, dened by a slider on the interface of the model.
- Original location (yes/no): the places where the walkers start the
simulation. They can be random or xed in those areas especially suitable for
prehistoric habitat (FábRegas and RodRíguez, 2012c).
- Homeland (yes/no): if activated, all walkers who start the simulation
on the same original location become “fellow members” of the same group and
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–if the “Cultural Transmission” option is enabled– they will share information
among themselves (i.e., the location of new monuments they encounter as they
move through the virtual world).
- Destination (yes/no): if enabled, walkers choose a specic area as target
or destination. This option prevents random walking.
- Sight limit: up to 5km, dened by a slider on the interface of the model.
- Visual acuity: between 0.01 and 10 degrees, dened by a slider on the
interface of the model. Establishes the minimum visual angle that the target must
occupy in a walker’s retina before it can be perceived.
Petroglyphs are immobile agents with some of the basic features of the rock
art sites. Their major characteristics are:
- Number: up to 500, dened by a slider on the interface of the model. If the
random location is not activated, the number is equivalent to that of the actual set
of petroglyphs existing in the study area (348).
- Random Location (yes/no): if activated, petroglyphs are randomly
distributed over the land area of the virtual world. Otherwise, they will be placed
in their actual locations within the study area.
- Rock size: height in meters of the rock on which the engravings are
located. For the purposes of this work, the size of the rock has been established
randomly according to the minimum and maximum dimensions (0.20 to 4.50
meters) registered in some of the monuments of the study area.
- Panel size: height in meters of the panel (the part of the rock covered
by engravings). For the purposes of this work, the size of the panel has been
established to be a random percentage of the rock size varying from 20 to 70%.
- Inclination of the rock: established randomly between 0 and 90º to the
horizontal.
- Contrast between the carvings and the surface of the rock: given the
difculties for simulating this variable, we have chosen to establish a random
contrast that takes the form of a percentage. 0 means a null contrast while 1.0
(100%) equals a perfect contrast.
- Apparent size of the panel: a function of the three variables described
above (panel size, inclination, and contrast) according to the following formula:
AS = (Size * sin(Inclination)) * Contrast
- Expertise (yes/no): if enabled, the variable “Contrast between the
carvings and the surface of the rock” will be overwritten. Walkers will only need
to perceive the rock to become aware of the existence of the petroglyph. The
contrast of the grooves with the surface of the rock becomes perfect (100%).
- Times perceived: it records the total number of times a petroglyph has
been perceived by walkers.
- Already perceived?: it records if a given petroglyph was previously
perceived by a specic walker
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Mounds are immobile agents with some of the basic features of these
monuments. Some of their major characteristics are:
- Number: up to 250, dened by a slider on the interface of the model. If the
random location is not activated, the number is equivalent to that of the actual set
of mounds in the study area (223).
- Random Location (yes/no): as dened for petroglyphs.
- Height: height in meters of the mound. For the purposes of this work, the
size of the monument has been established randomly according to the minimum
and maximum height (0.50 to 2.50 meters) of most mounds in the area.
- Contrast between the mound and its background: as with petroglyphs,
we have chosen to establish a random contrast that takes the form of a percentage.
However, we have set the limits between 0.5 (50%) and 1.0 (100%), since the con-
trast between the mound and its background will never be so low as to impede
its perception (unlike rock art, where a null contrast between engravings and the
surface of the rock has been documented).
- Apparent size: a function of height and contrast according to the following
formula:
AS = Size * Contrast
- Expertise (yes/no): if enabled, the variable “Contrast between the mound
and its background” will be overwritten. Walkers will perceive the monument as
if its contrast with the surrounding background were always perfect (100%).
- Times perceived: it records the total number of times a mound has been
perceived by walkers.
- Already perceived?: it records if a given mound was previously per-
ceived by a specic walker
2.2.3. Simulating perception
One of the biggest challenges during the implementation of this model
was to create a simulation of the perception process simple enough so that it could
be effectively managed by Netlogo but, at the same time, fairly realistic. Thus, for
each walker, we created a procedure trying to simulate the basic characteristics of
the human eld of view. This is composed by a cone 180o wide (approx. the width
of the human eld of view with head rotation excluded and peripheral vision
included) and a depth ranging from 0 up to 5000 meters (Fig. 4). Each petroglyph
or mound inside this area is potentially perceptible by a walker.
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Assegin the Perceptibility of Prehistoric Monuments on their Landscape
Figure 4. Diagram of the perception process implemented in the simulation. 𝜃: Visual
Angle; AS: Apparent Size of the monument; D: Euclidean distance between the walker
and the target.
However, the nal perception of a specic monument will depend on
whether the perceived size of the target is greater than the threshold set for the
walker’s visual acuity. Following former approaches on this matter (llobeRa,
2007; ogbuRn, 2006), we have considered the perceived size to be equivalent to the
visual angle it occupies on the walker’s retina. This has been calculated according
to the following formula:
Where (𝜃) is Visual angle, (AS) the Apparent Size of the monument, and (D)
the Euclidean distance between the walker and the target (for more details, see
sWeaReR, 2011).
If the visual angle is higher than the threshold established for the visual
acuity, then the target (either a petroglyph or a mound) will be perceived. Each
monument records the identity of the specic walker who perceives it as well as
the total number of times it has been perceived throughout the simulation.
As we have already noted, we have used the Apparent Size of the monuments
for the calculations. This term denes the size at which the monument will be
perceived. Let’s see several examples of how it was calculated.
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- Example 1: a petroglyph carved in a rock engraved on a vertical rock (90º),
with a size of 1.20 meters and a very sharp contrast (90%) between the grooves
and the surface of the rock. Its Apparent Size will be: (1.20 * sin (90)) * 0.9 = 1.08
meters.
- Example 2: a petroglyph carved in a rock engraved on a near-horizontal
rock (10º), with a size of 1.20 meters and a very low contrast (10%) between the
grooves and the surface of the rock. Its Apparent Size will be: (1.20 * sin (20)) * 0.1
= 0.04 meters.
- Example 3: a mound 2 meters high with a very sharp contrast (90%) with
the background. Its Apparent Size will be: 2 * 0.9 = 1.80 meters
- Example 4: a mound 2 meters high with a low contrast (50%) which
makes it difcult to distinguish from the background. Its Apparent Size will be:
2 * 0.5 = 1 meter.
Although we are aware that the option chosen to simulate the impact of
contrast on how objects are perceived is quite abstract and simplistic, we consider
it suitable for a rst, exploratory approach. It will allow us to glimpse the impact
that this variable has had on the perception of prehistoric monuments, something
that has hardly been addressed before.
2.2.4. Simulating the impact of memory, experience, and cultural transmission
Given the ability of Agent-Based Modeling to simulate abstract concepts and
dynamics, including the impact of agents’ behavior in the virtual environment
they inhabit, we decided to explore if and how specic characteristics of the
audience would have affected the perceptibility of monuments. We have paid
attention to how familiarity with the landscape and knowledge of the specic
location of the monuments would have impacted the frequency with which burial
mounds and petroglyphs would have been perceived.
This remains relevant in the context of some of the questions that have
been raised about the target audience for the Galician tumuli and petroglyphs.
As we have already stated, it has been assumed that most mounds and rock
art sites would be easily perceptible for people passing by. Consequently, their
intended audience would be very broad, as it would also include the members of
communities other than the one who created the monument. It would be precisely
this ability to reach “inter-group” audiences what would have allowed them to
act as mechanisms of communication between communities still highly mobile
(bRadley, 1997; ingold, 1987; CasimiR, 1992).
With this goal in mind, we designed the model so that we could test how
petroglyphs and mounds would have been perceived by four different types of
audiences:
- An extremely “naïve” audience whose members ignore the existence and
location of the monuments and only become aware of their presence once/if they
have eventually perceived them. In addition, they are unable to remember the
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location of monuments they have already seen, so they have to “rediscover” them
each time they pass by.
- A “naïve” audience with the ability to learn, so they remember the loca-
tion of a monument once they have seen it for the rst time.
- A “naïve” audience who remembers the location of a monument once
they have seen it and, in addition, are able to share this information with other
members of their community.
- An expert audience who is already aware of the existence and location of
all the monuments in the study area.
To try to understand how each of these audiences would have interacted
with the monuments, we took advantage of the insights gained during more than
15 years working in the eld along students and archaeologists with different
levels of expertise.
Naïve audiences generally need more time and greater physical proximity
to the monument to be able to perceive it and, therefore, to become aware of
its existence. In extreme cases, such as low mounds or very inconspicuous
petroglyphs, many naïve observers have been unable to notice them even from less
than a couple of meters away. A signicant percentage of inexperienced observers
need to visit the monument several times before internalizing its location. Once
this occurs, they no longer need to observe the engravings to become aware of
its existence, since –for example– they can identify the rock from relatively large
distances. In the case of burial mounds, naïve observers can remember the general
location of the monument and perceive it from quite a distance after only a couple
of visits. The transmission of knowledge about the existence of a monument (i.e.,
pointing out its location from afar) accelerates the process of perception by naïve
observers.
In sharp contrast, expert audiences with a deep knowledge of the territory
have a complete mental map composed of thousands of references that allows
them to perfectly locate the monuments in space, regardless of their characteristics.
In such cases, the perception of the monument is almost automatic once the area
where it is located appears in their eld of vision.
We have sought to incorporate these dynamics into our model by varying the
threshold necessary for observers with different levels of expertise to be able to
perceive a given monument.
For petroglyphs, naïve observers must rst perceive the engravings to be
aware of their existence. If the “Memory” option is activated, once walkers have
perceived the engravings for the rst time, they will recall the general location of
the petroglyph, so that the next time they will only need to perceive the rock to
remember the existence of engravings on its surface.
If the “Cultural transmission” option is enabled, a walker with a given origin
at the beginning of the simulation (“Homeland”) will transmit the knowledge
regarding the location of the monuments he/she has seen with all the other
walkers who share his/her same “Homeland”. Enabling this option generates
a kind of “collective memory” in which all members of the same “Homeland”
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will automatically have access to the knowledge generated by their peers.
Consequently, if a walker passes near a petroglyph which has already been
perceived by a fellow member of his/her “Homeland”, he/she will only need
to perceive the rock on which the petroglyph is located (and not the engravings
themselves) to be aware of its existence. To speed up the process, we have
decided that the transmission of information will be done automatically instead
of requiring direct contact between agents (i.e., that they meet each other).
Finally, if the “Expertise” option is activated, all walkers will act as if they
were already perfectly aware of the existence and location of the petroglyphs (they
will only need to detect the rock to be aware of the existence of the petroglyph and
they will see the engravings as if they were perfectly contrasted with the surface
of the rock).
For burial mounds, naïve observers must perceive the monument to be
aware of its existence. If the “Memory” option is activated, once walkers have
perceived the mound for the rst time, they will recall its general location, so
that the next time they will be able to easily perceive the monument as if it had
a perfect contrast with the surrounding environment. If “Cultural transmission”
is enabled, a walker with a given “Homeland” will share with his/her peers the
knowledge regarding the location of the monuments he/she has seen. Therefore,
all the walkers of that same “Homeland” will automatically perceive those mounds
perfectly contrasted against the landscape. If the “Expertise” option is activated,
all walkers will act as if they were already perfectly aware of the existence and
location of the mound (they all will perceive the mounds fully contrasted again
the surrounding landscape).
Likewise, the possibility of simulating the random and targeted movement
strategies makes it possible to verify if the knowledge of the terrain has an impact
on the perception of the monument, since the targeted movement necessarily
requires a sufciently broad knowledge of the surroundings to know how to get
from point a to point b (Fig. 5).
Figure 5. Kernel Density Estimation (KDE) of the movement made by 100 walkers during
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the simulations (10 runs with the “Random Movement” option enabled, and 10 runs with
the “Targeted Movement” option enabled. Duration: 1000 ticks each).
3. RESULTS
The results presented in this paper are derived from a total of 16 experiments,
each of which was run 10 times (Table 1). Thus, a set of 160 simulations was
created, with each simulation running for 1000 ticks. These have resulted in a
virtual dataset consisting of 55520 petroglyphs and 34880 burial mounds (90400
virtual sites).
table 1
Summary of the main characteristics of the experiments carried out for this paper
Experiment Runs Ticks Walk Location Expertise Memory Cultural
Transmission
1 10 1000 Random Real Yes No No
2 10 1000 Random Real No No No
3 10 1000 Random Real No Yes No
4 10 1000 Random Real No Yes Yes
5 10 1000 Random Random Yes No No
6 10 1000 Random Random No No No
7 10 1000 Random Random No Yes No
8 10 1000 Random Random No Yes Yes
9 10 1000 Targeted Real Yes No No
10 10 1000 Targeted Real No No No
11 10 1000 Targeted Real No Yes No
12 10 1000 Targeted Real No Yes Yes
13 10 1000 Targeted Random Yes No No
14 10 1000 Targeted Random No No No
15 10 1000 Targeted Random No Yes No
16 10 1000 Targeted Random No Yes Yes
The rst striking aspect of the results is the small number of monuments that
have been perceived by the walkers (Fig. 6). Thus, for the entire set of simulations,
only 8.82% of mounds (3079) has been perceived at least once. This percentage
drops to 2.24% (1244) in the case of petroglyphs. Moreover, the monuments that
have been observed display an almost exponential distribution, with most of
them being observed just once or twice and only a few more than ve times.
In absolute numbers, mounds have been perceived by walkers 5584 times, an
average of 1.96 times per experiment. Petroglyphs, in turn, were seen almost half
as many times: 2957 (an average of 1.74 times per simulation). Such difference
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between monuments in terms of number of perceptions is statistically signicant
(Mann-Whitney-Wilcoxon U Test. p-value: < 2.2e-16).
Figure 6. Number of times mounds and petroglyphs have been perceived during the
simulations.
The reason for this small number of perceptions is most likely due to the
extremely conservative approach we used when dening the threshold for
walkers’ visual acuity, which was set at 1° (approximately equivalent to the limits
of Higuchi’s short-distance view). As a reference, it should be noted that the limit
that determines perfect vision (20/20) is set at much lower values: just between 1
and 5 arc minutes (between 0.01 and 0.08º). Therefore, if we reduce the threshold
from 1º to 1 arc minute, the number of perceptions will increase signicantly (Fig.
7).
Our option for such conservative limits derives from the fact that the use of a
threshold equivalent to perfect vision yielded very unrealistic perceptual distances
for the type of monuments analyzed in this paper. For example, a threshold of 1 arc
minute resulted in petroglyphs and burial mounds being perceived at distances
greater than four or even ve kilometers, a span similar to that identied by
D. Ogburn for this same threshold (ogbuRn, 2006). In comparison, the average
perceptual distances for the 1° threshold simulations have ranged from 20 to 2700
meters, numbers that (although they may be slightly low for some mounds) are
much more realistic and closer to the perceptual limits of petroglyphs and burial
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Assegin the Perceptibility of Prehistoric Monuments on their Landscape
mounds that we have detected in the eld.
At the same time, these low levels of perceptibility suggested by the Agent-
Based Models seem to support the conclusions reached by our previous studies
using GIS tools, that had already pointed to a low conspicuity of these monuments,
especially of rock art sites. For example, 59.1% of the petroglyphs in the north
of the Barbanza Peninsula would not be visible (they are not located within the
eld of vision) of an individual walking along the main transit routes in the area
(RodRíguez, 2016). Mounds, in turn, are located to a greater extent within the
visual basins of the main transit routes; however, a signicant percentage of them
would also not be visible from such paths (RodRíguez-Rellán and FábRegas, 2017).
In the specic case of rock art, the results achieved by both ABM and GIS are
in line with those gathered during our eldwork in Northern Barbanza. There, we
found that more than half of the petroglyphs were barely perceptible at more than
50 meters away (FábRegas and RodRíguez, 2012a).
Figure 7. Number of times mounds and petroglyphs have been perceived during the
simulation according to the walker’s visual acuity (taken from 3 simulations of 10 runs
each. Duration: 1000 ticks).
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3.1. Impact of the characteristics of monuments on their perceptibility
As mentioned in section 2.2.2., we have simulated a series of physical, intrinsic
characteristics of mounds and petroglyphs to try to determine and quantify,
albeit theoretically, the hypothetical impact that these characteristics would have
had on the perception of such monuments. For mounds, these variables were size
(height in meters) and contrast with the background (percentage). For rock art,
the variables were: rock size and panel size (height in meters), inclination of the
panel (degrees to the vertical) and contrast between grooves and surface of the
rock (percentage).
The statistical signicance of these variables has been measured in two
ways. On the one hand, a Generalized Linear Model (GLM) was calculated using
perception as a dichotomous binary response variable (i.e., Was monument x
perceived at least once? yes/no) and the different characteristics mentioned
above as explanatory variables (Table 2).
This test has allowed us to establish whether the explanatory variables have
had a signicant impact on the probability that a monument were perceived by
walkers. On the other hand, Kendall’s tau correlation was calculated to determine
whether there was any association between the values of each of the explanatory
variables considered and the number of times a given monument was perceived
(Table 3) (i.e., Does the number of times a monument was perceived depend on
the value of the explanatory variable y?). We have chosen this test because it is
relatively robust and suitable for measuring the association between continuous
and discrete variables that do not meet normal distribution.
Both the GLM and the Kendall’s tau correlation were applied only to those
simulations (120) in which the “Expertise” option was disabled (Table 1). The
reason behind this decision is that, as described in Section 2.2, such option
overwrites the Contrast parameters of the monuments, increasing them to the
maximum (100%), which would imply a logical overestimation of the importance
of this variable.
The GLM results suggest that almost all the explanatory variables considered
had a signicant impact on the probability that a given monument would be
noticed by walkers (Table 2). This is not surprising, given the weight assigned to
these variables in the model design. However, what is relevant about the results
is that they point out that not all variables considered have affected the likelihood
of a monument to be perceived in the same way.
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Assegin the Perceptibility of Prehistoric Monuments on their Landscape
table 2
Generalized Linear Model (GLM) calculated using perception as response variable and physical,
intrinsic characteristics of monuments as explanatory variables (Results calculated over the 120
simulations in which the option “Expertise” was disabled)
Mounds
Response variable: Perceived (No vs. Yes). AIC: 14665
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -5.053 0.1427 -35.41 < 2e-16 ***
Size (h) 1.1392 0.0423 26.9 < 2e-16 **
Contrast 1.0746 0.1520 7.07 1.55e-12 ***
Petroglyphs
Response variable: Perceived (No vs. Yes). AIC: 3289.2
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -10.3057 0.2974 -34.650 <2e-16 ***
Rock Size 0.1045 0.0861 1.214 0.225
Panel Size 1.0723 0.1248 8.587 < 2e-16 ***
Inclination 0.0311 0.0025 12.456 < 2e-16 ***
Contrast 3.3016 0.2360 13.985 < 2e-16 ***
Signif. codes: 0 ‘***’ 0.001 ‘**’
Thus, in the case of mounds, the likelihood of a monument being perceived
rises almost equally (1.13 and 1.07) for each unit by which the value of “size” and
“contrast” is increased. This suggests that –at least theoretically and always within
the framework of the simulations– size and the contrast of the monument with
its background might have a similar impact in terms of its probability of being
perceived. For petroglyphs, all explanatory variables –apart from the rock size–
had a statistically signicant impact on the probability of perception. The variable
“contrast” is noteworthy because by every unit it is raised, the probabilities of
a petroglyph being perceived increase notably (3.30). A noticeable, although
somewhat more discrete, impact was also observed for the variable “Panel size”
(1.07). While statistically signicant, “inclination” does not seem to have been
such a decisive factor in increasing the likelihood of a rock site being perceived.
This seems to contradict traditional remarks, linking verticality and perceptibility.
The results of the Akaike Information Criterion (AIC), or measure of the
relative quality of the model, suggest a better t of the model to petroglyphs than
to mounds (a circumstance derived, in large part, from the fact that our model
was originally devised for the analysis of the perceptibility of rock art).
Having analyzed the role of the explanatory variables on the probability of a
given monument being perceived or not, we subsequently explored the impact of
these same variables on the total number of perceptions of each monument. The
results –analyzed by means of Kendall’s tau correlation– again show a statistically
signicant impact of the variables on the number of times the monuments were
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perceived (Table 3). However, the measure of association (tau) shows that such
correlation is very weak, ranging between 0.03 and 0.14 (-1 or 1 being the perfect
association).
table 3
Kendall’s tau correlation of physical, intrinsic characteristics of monuments with the number of
times these were perceived during the simulations (Results calculated over the 120 simulations in
which the option “Expertise” was disabled)
Monument Variable Z tau p value
Mounds Size (h) 28.164 0.1404 < 2.2e-16*
Contrast 6.9261 0.0345 4.325e-12*
Petroglyphs
Rock size 12.985 0.0519 < 2.2e-16*
Panel size 15.759 0.0630 < 2.2e-16*
Inclination 13.003 0.0522 < 2.2e-16*
Contrast 14.979 0.0598 < 2.2e-16*
This is also clearly seen in the scatterplots relating the number of perceptions
and the different characteristics of the monuments considered in our simulations
(Fig. 8).
Figure 8. Number of times the monuments were perceived during the simulations as a
function of the characteristics considered in this paper.
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Assegin the Perceptibility of Prehistoric Monuments on their Landscape
The results suggest that none of the explanatory variables, by themselves,
satisfactorily explain the total number of times a monument has been perceived.
Likewise, they highlight the complexity of the processes of perception of
prehistoric monuments, where material as well as immaterial factors would
have contributed to make a monument particularly conspicuous. However, the
results again suggest that while size (of both mounds and engraved panels) is
an important variable, other factors generally regarded as secondary would also
have had an impact on both the likelihood of a monument being noticed and the
number of times it would have been detected.
A further variable considered was the location of the monuments within
the study area. Using a Monte Carlo-like approach, the perceptibility of mounds
and petroglyphs located in their real location in the Barbanza Peninsula was
compared with that of populations of identical size but randomly distributed.
The effect that location may have had on the perceptibility of the monuments was
then measured by means of a Generalized Linear Model in which the location
–expressed as a dichotomous response variable (Random location vs. Real
location)– was explored in relation to the number of times a given monument
was perceived during the simulations (Times Perceived).
The GLM shows different outcomes depending on whether we focus on
mounds or petroglyphs. Among the rst we can observe a signicant impact
of the type of location on the probability of a monument being perceived to a
greater degree, with the number of perceptions increasing very slightly (0.03) for
the monuments in actual places (Table 4). Conversely, location does not seem to
have played a statistically relevant role in the number of times the petroglyphs
were perceived (Table 5).
These results underscore that perceptibility was more site-dependent for
mounds than for rock art. The former would tend to be built in places with a
greater prominence than the latter, so when the location of mounds in the model
is the same as in the real world, their number of perceptions tend to increase
compared to when randomly distributed. This trend had already been detected
in previous approaches using predictive modelling and GIS platforms. In these
studies, it was observed that visual prominence was a signicant predictor for
mounds in the Barbanza (CaRReRo-Pazos et al., 2020), but not for rock art sites
(RodRíguez and FábRegas, 2015).
3.2. Impact of the character of audiences on the perceptibility of monuments
As we mentioned earlier, one of the advantages of ABM over GIS when
modeling the perception of prehistoric monuments is, in addition to its dynamic
nature, the comparative ease with which ABM can manage intangible variables.
These include specic characteristics of the audiences to whom these monuments
would have been preferentially or exclusively addressed.
To test the possibilities of ABM in simulating if some of these immaterial
aspects of the prehistoric observers might affect their ability to perceive the
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monuments, we designed a “virtual audience” (walkers) with capabilities such
as “Expertise”, “Memory”, and “Cultural Transmission” (see section 2.2.4. for
an explanation of these variables). Likewise, walkers were provided with the
ability to develop two different types of mobility strategies: Random walking
vs. Targeted walking (Fig. 5). The purpose of these variables was to simulate
audiences with variable degrees of familiarity with both the study area and the
monuments located there.
We applied a Generalized Linear Model in which the audience characteristics
–expressed as dichotomous response variables– were analyzed in relation to
the number of times the monuments were perceived during the simulations.
The results suggest that, for mounds, only one of the four variables analyzed
–“Walking strategy”– shows a statistically signicant effect on the likelihood
of these monuments being perceived more of less often (Table 4). However, the
estimated value of this variable (-0.24) suggests that such effect would not have
been particularly powerful.
table 4
Generalized Linear Model (GLM) calculated using different characteristics of mounds and
audiences as response variables and the number of perceptions as explanatory variable
Mounds
Response variable: Location (Random vs. Real). AIC: 48350
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -0.0057 0.0109 -0.526 0.5991
Times
Perceived
0.0361 0.0132 2.720 0.0065**
Response variable: Walking strategy (Random vs. Targeted). AIC:
48163
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept 0.0353 0.0110 3.199 0.0013 **
Times
Perceived
-0.2451 0.0200 -12.224 < 2e-16 ***
Response variable: Expertise (No vs. Yes). AIC: 39232
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -1.0981 0.0125 -87.370 <2e-16 ***
Times
Perceived
-0.0029 0.0141 -0.209 0.834
Response variable: Memory (No vs. Yes). AIC: 33306
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept 0.6915 0.0133 51.888 <2e-16 ***
Times
Perceived
0.0101 0.0150 0.673 0.501
Response variable: Cultural Transmission (No vs. Yes). AIC: 33306
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Assegin the Perceptibility of Prehistoric Monuments on their Landscape
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -0.6920 0.0133 -51.940 <2e-16 ***
Times
Perceived
-0.0069 0.0147 -0.473 0.636
Signif. codes: 0 ‘***’ 0.001 ‘**’
Regarding petroglyphs, only the variable “Expertise” seems to have played a
statistically signicant role in their perception (Table 5). In addition, such variable
shows an important effect (1.38) on the probabilities of petroglyphs increasing or
decreasing the number of times they would have been noticed.
table 5
Generalized Linear Model (GLM) calculated using different characteristics of petroglyphs and
audiences as response variables and the number of perceptions as explanatory variable
Petroglyphs
Response variable: Location (Random vs. Real). AIC: 76969
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept 0.0006 0.0085 0.078 0.938
Times
Perceived
-0.0138 0.0138 -0.995 0.320
Response variable: Walk (Random vs. Targeted). AIC: 76971
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -3.216e-05 8.49e-03 -0.004 0.997
Times
Perceived
6.042e-04 4.64e-03 0.130 0.896
Response variable: Expertise (No vs. Yes). AIC: 61213
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -1.1513 0.0100 -114.76 <2e-16 ***
Times
Perceived
1.3851 0.0529 26.14 <2e-16 ***
Response variable: Memory (No vs. Yes). AIC: 53013
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept 0.6929 0.0104 66.472 <2e-16 ***
Times
Perceived
0.0176 0.0732 0.241 0.809
Response variable: Cultural Transmission (No vs. Yes). AIC: 53012
Parameter Estimate Std. Error z value Pr(>|z|)
Intercept -0.6923 0.0104 66.408 <2e-16 ***
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Times
Perceived
-0.0795 0.0770 -1.033 0.301
Signif. codes: 0 ‘***’ 0.001 ‘**’
These GLM results suggest that the audience variables show a more varied
and, to some extent, complex behavior than those analyzed in section 3.1. As far
as the tumuli are concerned, it seems quite clear that none of the variables related
to a more expert audience have a signicant impact on their chances of being
perceived more often. Neither the ability of walkers to remember and recognize
the location of these monuments, nor the capability to transmit this information to
other members of their community, nor a targeted mobility strategy have led to a
signicant increase in the number of times mounds were noticed.
This is not the case with petroglyphs. The fact that the variable “Expertise”
does have a statistically signicant effect on the perceptibility of rock art suggests
that the existence of an audience with an important level of knowledge of the terrain
may have been an important condition for these monuments to be noticeable. This
can be clearly seen in the difference regarding the number of perceptions if the
variable “Expertise” is enabled or not. When it was not activated, the petroglyphs
were perceived 448 times (as opposed to 4203 times for the tumuli). Meanwhile,
when “Expertise” was enabled, the number of perceptions rose to 2509, higher
than the tumuli (1381).
The fact that neither the “Memory” nor the “Cultural Transmission”
variables had a signicant impact on the number of perceptions may suggest
that the accumulation and transference of knowledge between walkers was not
extensive enough in our model to generate a sufciently familiar audience for
this circumstance to be reected in an increase of perceptions. Maybe longer
simulations (10,000 or 20,000 ticks) would allow the emergence of audiences with
a sufciently broad and generalized knowledge of the environment to really
impact the perception processes. This should be explored in future developments
of this model.
4. DISCUSSION
The implementation of an Agent-Based Model aimed at simulating the
process of perception of monuments (mounds and petroglyphs) by prehistoric
audiences has demonstrated the potential of ABM to handle this kind of questions
and overcome some of the limitations of static models built in GIS suites through
which this problem had been usually handled.
To begin with, the analysis of physical properties intrinsic to the monuments
(location, size, contrast...) has made it possible to show how some of the variables
hitherto considered as secondary, would have had –at least in theory and in the
framework of the simulations implemented in this paper– an equivalent impact
on the perceptibility of the monuments to that of factors traditionally considered
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Assegin the Perceptibility of Prehistoric Monuments on their Landscape
to be of much greater importance, such as size. This is the case with “Contrast”.
For lack of a solution that allows a more realistic simulation of this variable, our
model has clearly shown how the contrast of mounds with their surroundings or
of engravings with the surface of the rock would have been of great importance
in modulating the perceptibility of these monuments. Conversely, factors
traditionally considered relevant, such as the inclination of the engraved panels,
have proven to be of little relevance in our model.
As for the characteristics of the audiences considered in our model, these
suggest that the existence of viewers with a deep knowledge of the landscape and
the location of the monuments would have been a very important factor for the
petroglyphs to successfully perform the role of landscape markers they have been
traditionally assigned. This does not seem to be the case for the tumuli, whose
perceptibility seems to have been quite independent of the level of experience of
the audiences.
These results, although taken with the caution inherent to the merely
exploratory nature of this approach, could suggest that the attribution to rock
art of an “inter-group” communication role may not be too realistic (at least
for a substantial part of petroglyphs). For such function to have been effective,
it would have required from the viewers a deep knowledge of the territory of
neighboring and perhaps rival communities, fact that we are far from knowing if
it would have been feasible. Conversely, it might be suggested that Galician open-
air rock art may have been more of an element of “self-consumption” aimed at
audiences made up mainly of members of the very community responsible for the
carvings, perhaps as a means of reinforcing the group’s identity and the link with
its own territory. What does seem to be evident is that, in almost all the scenarios
considered in our simulations, megaliths would have been a much more effective
element in shaping prehistoric landscapes, being much more perceptible than
petroglyphs.
In short, the results of this rst, exploratory approach to modelling the
perceptibility of prehistoric monuments using Agent-Based Modelling, suggest
that ABM –in collaboration with GIS tools– could bring valuable insights into the
analysis of complex processes in which material and immaterial variables may
have contributed to make specic monuments more noticeable than others. ABM
may, therefore, allow us to get a little closer to understanding the processes of
shaping and transformation of cultural landscapes during prehistoric times.
5. ACKNOWLEDGMENTS
Carlos Rodríguez Rellán research is funded by the Programa Emergia (Junta
de Andalucía, Spain) (EMERGIA20_00349). The authors truly appreciate the
comments and recommendations by the two anonymous reviewers, which have
helped to improve the manuscript.
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