=Paper=
{{Paper
|id=Vol-3834/paper82
|storemode=property
|title=Assessing Burial Mound Intervisibility and Prominence at Regional Scale
|pdfUrl=https://ceur-ws.org/Vol-3834/paper82.pdf
|volume=Vol-3834
|authors=Adela Sobotkova
|dblpUrl=https://dblp.org/rec/conf/chr/Sobotkova24
}}
==Assessing Burial Mound Intervisibility and Prominence at Regional Scale==
https://ceur-ws.org/Vol-3834/paper82.pdf
Assessing Burial Mound Intervisibility and
Prominence at Regional Scale
Adela Sobotkova1
1
Aarhus University, Department of History and Classical Studies, Jens Chr. Skous Vej 5, Aarhus, 8000, Denmark
Abstract
Visibility and intervisibility have been important aspects of spatial analysis in landscape archaeological
studies, but remain hampered by computational intensity, small-scale study area, edge effects, and bare-
earth digital elevation models. This paper assesses intervisibility and prominence in a dataset of over
1000 burial mounds in the Middle Tundzha River watershed in Bulgaria. The aim is to obviate the pitfalls
in regional assessment of visibility through vegetation simulation and MC modelling and to gauge when
intervisibility and prominence truly mattered to past mound-builders.
Keywords
visibility studies, burial mounds, edge effects, vegetation simulation
1. Introduction
’Will to visibility’ has been noted in funerary monuments from the United Kingdom to Missis-
sippi Valley, confirming that communities constructed new landscape features with respect to
natural landmarks as well as pre-existing sites and monuments[4, 2, 30]. Two approaches have
governed visibility studies in landscape archaeology. The first sees visibility as an attribute of
the environment and employs viewsheds, lines of sight, and topographic prominence in digital
elevation models (DEMs) to represent potential visibility under ideal conditions[6, 28, 30, 26,
14, 15, 5]. The second interprets visibility as an embodied perceptual act, one that is depen-
dent on a person’s knowledge, visual acuity, movement, and scale within the landscape[24, 9,
8] and requires simulations or virtual reality approaches to factor in individual attributes [29,
27]. Regardless of approach, both types of visibility studies share the same shortcomings, such
as the lack of vegetation in the input DEMs, the problem of edge effects - where viewpoints
along the edges of the study area are less ”connected” because their visual connection to points
outside the study area is not counted -, lack of tests for randomness, and small-scale focus or a
massive computational overhead for regional-scale studies [11, 13, 12, 16, 7].
In this paper I use 1073 burial mounds from the Yambol Province in SE Bulgaria to assess
the impact of edge effects and of bare-earth models on intervisibility in a regional context.
Parallelizing custom spatial functions in R, I calculate visual connectivity among the burial
mounds, comparing the results from bare-earth elevation model with two different vegetation-
covered simulations. Next, I extract the topographic prominence in mounds at two different
CHR 2024: Computational Humanities Research Conference, December 4–6, 2024, Aarhus, Denmark
∗
Corresponding author.
£ adela@cas.au.dk (A. Sobotkova)
ȉ 0000-0002-4541-3963 (A. Sobotkova)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
869
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
Figure 1: According to Arkheologicheskite Otkritia i Razkopki, journal that logs annual excavation re-
ports in Bulgaria, 40 mounds were excavated in the Yambol Province in 1987-2014 yielding 295 distinct
burials, whose assemblages have been dated within the chronological range above.
radii and assess it against background values through Monte Carlo modelling. My aims are
to (a) explore the feasibility of rigorous testing of intervisibility and prominence at regional
scale in R, and (b) to assess how much visual connectivity mattered to mound-builders across
Yambol through time.
2. Data and Methods
2.1. Burial mounds
The present dataset is one of the outputs of the Tundzha Regional Archaeological Project
(TRAP) which has operated in the Yambol Province since 2008[20]. The project digitised burial
mound symbols from 1:50,000 scale Soviet topographic military maps and then verified their
status in the field, yielding the locations and descriptions for 1073 mound features in a region of
3,355 sq km[23, 22]. According to annual archaeological reports, only 40 of these mounds have
been excavated to date, offering limited chronological control. Figure 1 shows that excavated
burial assemblages span from the Early Bronze Age to the Mediaeval Era, peaking in the Early
and Late Bronze Age followed by the Roman imperial period.
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Figure 2: Raster profile of the Yambol ASTER DEM in map units (pixel is 30m) with a visibility line
showing unobstructed view.
2.2. Prominence
For mound prominence I use Llobera’s (2001, 1007) definition of “topographic prominence as a
function of height differential between an individual and his/her surroundings as apprehended
from the individual’s point of view”[14]. Replacing an individual with individual mound height,
I translate this calculation into R. The resulting value for each location is a percentage that
expresses the proportion of locations that lie at or below the mound top’s location within a
given radius. I calculate prominence at two different radii of 250 and 2000 m respectively to
gauge landscape affordances for various scales within the Yambol Province. An additional test
of burial mound visual dominance can be achieved by comparing the prominence distribution
of mounds with that of the entire region. Such bootstrapping was undertaken previously for a
subset of Bronze Age mounds in Yambol[25]. Including all mounds here, I iterate 99-times the
measurement of prominence within a 250 m buffer at 1200 random locations in the region and
compare the resulting values to those from a random sample of the burial mound locations.
2.3. Intervisibility
To assess intervisibility, I calculate line of sight (LoS) from each of the 1073 mounds inside the
Yambol Province boundary to all other neighbours within the region. A positive LoS means
that the view from point A to point B is unobstructed, meaning there is no higher elevation
871
between the two mound tops (see Figure 2). I translate this approach into R as the comparison
of elevation at location A to the elevations encountered on a straight line to location B, derived
from a raster profile. In order to reduce edge effects in 341 mounds located within a 5 km buffer
of the regional administrative border, whose view is constrained by the arbitrary boundary, I
also calculate their LoS to additional 1206 mounds within 25 km buffer outside the Yambol
Province border. The locations of the latter 1206 mounds have also been digitized from the
Soviet military topographic maps but remain unverified[22].
2.4. Digital elevation model and vegetation modeling
I mosaic together three ASTER DEM tiles[10] of 30 m resolution to produce a digital elevation
model for the Yambol Province and a buffer of 25 km around it. This DEM is a bare-earth model
(BOM). The lack of vegetation maximizes intervisibility of landmarks within this model[21]. To
challenge this model I simulate vegetation following a regional paleoecological study which
attests to patchy forested landscape within the Tundzha watershed[3]. I generate two different
surfaces: first, trees of 10m height distributed randomly over 50% of the landscape, and second,
vegetation of variable height from 1 to 20 m (with a mean at 10 m) randomly covering 50% of
the landscape. Both surfaces have the same average height, but the second is more gradual
and ‘permeable’. I overlay these vegetation surfaces over the BOM and re-calculate mound
intervisibility. Results allow me to gauge the drop in mound intervisibility due to vegetation.
Intervisibility calculation workflow is coded and parallelized in R and is available for review in
Github.
3. Results
Topographic prominence calculations using the bare-earth DEM confirmed that mounds were
built in fairly prominent locations throughout the Yambol Province. As table 1 shows, more
mounds appear more visually dominant within the 2000 m than in the reduced 250 m radius.
Table 1
Mounds that enjoy 50%, 95%, and 99% prominence in the region
Radius|Prominence 50%+ 95%+ 99%
250 m 592 (54%) 81 (3.5%) 12 (1.1%)
2000 m 853 (80%) 61 (5.6%) 19 (2%)
The drop in prominence in smaller radius calculation runs contrary to Llobera’s expecta-
tion of prominence decreasing as we calculate over a greater aggregate area. One explanation
could be that the scale of area covered by 250 and 2000 m buffers is negligible compared to
the scale of the region which routinely affords expansive vistas over 40 km radius. Maybe
mound builders positioned their monuments carefully with an idea to longer-distance rather
than short-distance visual control. A more realistic explanation, however, is that my calcula-
tion is spurious: percentage of lower elevation within a given radius is not a replacement for
line of sight calculation, but is a simplistic way chosen to make the computational analysis
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Figure 3: Topographic prominence percentage in 1200 locations randomly distributed in the Yambol
landscape (dark grey band) and the 1200 values randomly sampled from the burial mound dataset (red
band).
feasible for a vast area (2000 m radius means a moving window of 132 x 132 raster cells enters
in the calculation for each discrete mound point). To avoid misrepresenting reality, I evaluate
bootstrapped data for prominence within 250 m radius alone.
The resulting prominence density chart in Figure 3 shows that the Yambol landscape data
(represented by the dark grey band enclosed by light gray confidence interval) forms an arc with
the main mode at 30-60% prominence and a secondary tight peak at 80%. The burial mound
curve rises to a tight global maximum at 70% and escapes the bounds of randomness in the 60
to 85% prominence band as well as the 10 to 30% band. From this visual investigation alone,
we can see that the mound locations differ from a random sample taken from the landscape of
the Yambol Province both in the low and high values. The next question is how significant is
this result, really? T-test and Mann-Whitney test in Table 2 show the prominence simulation
results are robust and statistically significant except in the case of upper confidence interval.
The p-value for upper confidence interval is above the threshold of 0.05 indicating that there
is some uncertainty here. Given the robust lower and median values, I would lean towards a
significant difference between the prominence of burial mounds and the overall landscape for
most but not all of the confidence interval.
When modelling intervisibility, the results for the bare-earth model (BOM) deliver on ex-
pectations: when there is no vegetation, most mounds in Yambol are highly intervisible. The
group with the lowest intervisibility - having only 1 to 10 visible counterparts - is small at 143
features out of 1073 (13%). Out of the 1073 mounds, 508 (47%) can see 10 to 100 counterparts
and 422 (40%) mounds see over 100 other mounds. The most visually dominant 60 mounds can
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Table 2
T-test and Mann-Whitney test results of topographic prominence in Yambol burial mounds. Significant
p-values are in bold.
test Lower CI Median Upper CI
t-test U-Statistic 1.483944149 2.04568119 2.95154358
p-value 0.0016 0.0205 0.0699
Mann-Whitney test U-Statistic 595288.450 605842.50 0.830611
p-value 0.0017 0.0178 0.0858
see over 250 other mounds. Their lines of sight extend across the entire region, as far as 60 km
away, and probably further if the study area were extended.
The mound with the highest intervisibility: 9412, west of the Yambol City, has an unob-
structed line of sight to 491 mounds across the region, visible in Figure 5A. Yet, we can reason-
ably doubt the real possibility of recognizing anything over 15 km distance, except perhaps fire
beacons at night or smoke stack from a burning village during daytime. Anything else - even
a 7 m high mound - would be reduced to an insignificant and unrecognizable dot especially
under less than ideal atmospheric conditions [8].
In addition to considerations of scale and limits of human vision, vegetation changes the
situation dramatically (see Figure 4). In the first simulation with static 10m tall vegetation,
intervisibility drops by 35-90%. Over 400 of 1073 (40%) mounds lose 90% of their field view due
to a patch of trees. Intervisibility groups get radically adjusted. Most mounds now fall in the
lower intervisibility group, seeing 1-10 mounds. Their count having risen three-fold over the
BOM. The middle rank drops by over 20%, but is still strong at 370 (36%) mounds with 10 to
100 intervisible counterparts. Only 103 mounds (10%) remain in the visually dominant rank
seeing over 100 other mounds. This considerable drop in intervisibility makes sense in light of
the 50% tree coverage and is consistent with Skov-Petersen’s [21] findings despite difference
in relief between the two study areas.
In the second scenario with variable 20m (10m mean) vegetation, the decline in visibility is
also present, but less pronounced. Intervisibility group membership shufÒes again. Compared
to BOM, the lowest rank doubles to 41% with 441 mounds, the middle rank remains almost
the same at 516 mounds (48%) and the highest rank of mounds attenuates to 116 (11% of total).
Even though some trees in second scenario are higher than in the first, the overall vegetation
variability makes this overlay more ’permeable’. This contributes to a less dramatic drop in the
middle intervisibility rank, shufÒing the class membership gradually.
Now that we have addressed the groups, what effect does vegetation have on individual
mound ranking, especially the formerly leading ones?
The downward adjustments contribute to reshufÒing among the leading mounds. Given
the one time run, these results are merely illustrative of the general tendency and probability.
In the present iteration of 20m variable vegetation model, the former total winner no. 9412
moves into a second place with 249 intervisibile mounds, a decline of 46% over BOM. It is
superseded by 9044, a 6m tall mound near Botevo, with 291 visible mounds. Only four of the
ten leading mounds retain their dominant position: 9412, 9411, 9044 and 8700. The remaining
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Figure 4: Change in the intervisibility group membership among 1073 mounds in Yambol across three
different digital elevation models: bare earth, simulation with static 10m tall vegetation, simulation
with variable 1-to-20m tall vegetation.
six sink in status with their line of sight obscured by trees, while others take their place. The
specific winners depend on vegetation configuration, but they are always selected from the top-
ranking group. In the end a rule emerges: unless the mound location happens to be covered
by vegetation, once in a commanding position, always highly intervisible.
Likewise, accounting for the edge effects does not massively alter the order of the leading
mounds. While many of the border region mounds grow in visual dominance, the absolute
winners’ field of view grows too. To illustrate the point, 9412 dominates intervisibility with a
line of sight to 409 other mounds inside the region in the bare-earth model. When we extend
the vision beyond the region to limit edge effects, 9412 continues its lead with a line of sight
to 491 other mounds (an increase of 20%). In the top ten mounds, eight retain their positions
when we extend the view beyond the border of the Yambol Province. While the arbitrary limit
on vision imposed by the regional boundary suggests that edge effects will be considerable for
mounds in immediate proximity of border, it is the relief that is the decisive factor. Extending
the view 25 km outside the region makes the intervisibility numbers go up by as much as
20%. However, they go up for many mounds in the region, not perturbing the regional order
dramatically.
These results confirm two points: (1) landscape affordances in the Yambol Province drive the
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intervisibility and prominence results, with vegetation having considerable effect on individual
mound field of view, and (2) ancient mound builders were aware of these landscape attributes
and exploited them (or not) intentionally, building in just the right locations. Visibility mat-
tered, but was not the only criterion. To underscore the point, locations exist in the region that
offer supreme visual dominance of 99%, such as the peak of Bakadzhitsite or the Dodoparon hill.
Scaling these peaks, however, is clearly beyond the needs for ancestral worship or territorial
signaling of the local communities.
Figure 5: Lines of sight to mounds inside the Yambol Province (thin grey outline) and within a 25km
buffer of the region visible from (A) mound 9412 (n = 491) and (B) mound 8007 (n = 378). The thick black
curve represents the national border between Bulgaria and Turkey.
3.1. The Winners
In the comparison of intervisibility and prominence, two winners merit a bit more detailed
attention: mounds 9412 and 8007 occupy the highest intervisibility rank (see Figure 5). Both are
perched on an outcrop with an open view across the Middle Tundzha watershed. 8007 has over
95% prominence and 9412 has 76 to 89% across all vegetation models at 250 m radius. Mound
9412 sits close to northwest border on a slope that faces the rest of the region to southeast.
Mound 8007 sits near the geographic center of the region, with an unobstructed view of the
entire region. Culturally, the mounds perhaps also share a story. Mound 8007 belongs to the
40 excavated mounds in the region, having been investigated in a 2010 rescue campaign before
the opening of a nearby quarry. Cultural material, DNA, and C14 results indicate it was built
by the Steppe people during the Early Bronze Age [18, 17]. After the initial tomb was cut, 23
other individuals were interred here in the course of the next three thousand years, attesting
to the long-term significance and popularity of the location. Survey in 2009 revealed a dense
network of settlements spanning Early Bronze Age to Roman period within 5 km buffer of
this location[19]. Mound 9412 remains unexcavated as of the writing of this paper. Excavated
mounds in the vicinity (”Drazhevo” mounds no 1262, 1263) yielded rock-cut pit graves inside
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elaborate stone circles, not unlike those found in 8007. Silver embellishments and other burial
goods led the excavator to attribute these burials to the Early Bronze Age period[1].
4. Conclusion
This study explores the impact of vegetation and of edge effects on intervisibility and promi-
nence rates among 1073 mounds in the Yambol Province, SE Bulgaria. Two different vegetation
regimes are generated to facilitate a comparison of visual connectivity among Yambol mounds
within bare- and vegetated-earth models. Line of sight results show that Yambol mounds lo-
cated on isolated outcrops achieve supreme visual control over their surroundings. Adding
vegetation of variable height between 1 and 20 m reduces the intervisibility less than adding
vegetation of static 10 m height, even if mean vegetation height remains the same. Adding
vegetation into digital elevation models always wreaks havoc on the individual mound inter-
visibility and reduces the visually-dominant group membership by 75%. Unless hid by a forest
directly, however, the ultimate winners remain largely the same thanks to the inexorable topo-
graphic properties of the local landscape. Finally, edge effect correction (adding a 25 km buffer
to the region) has a negligible effect on the intervisibility results, confirming that 3,355 sq km
area is large enough for a regional-scale visibility study.
The present analyses were possible thanks to dedicated spatial libraries and parallelisation
options offered by the R programming language. In addition to making workflows efÏcient
and reproducible, these libraries place compute-intense regional analysis within the reach of
scholars without access to computing clusters. Others can now adapt and improve the present
code, and pursue visibility explorations further, be it to investigate regional intervisibility net-
works or study the visual relationship between mounds and associated settlements and road
networks.
Acknowledgments
The paper was possible thanks to 10 years of fieldwork funded in sequence by the ARC Link-
age project 0989901, grant no. 19686 from the Endeavour Short-Term Mobility Programme
of the Australian Ministry of Education, and the Aarhus University Forskningsfond Starting
grant no. AUFF-E-2018-7-22 awarded to the ‘Social Complexity in the Ancient Mediterranean’
(SDAM) project. It involved scholars from three continents and dozens of volunteers as well
as researchers from the Regional History Museum of Yambol, Sofia University of St. Kliment
Ohridski, New Bulgarian University, Aarhus University, UNSW Australia, and Macquarie Uni-
versity. An early version of this paper was presented at the international conference “Research
of Ancient Thrace between Traditionality and Modernity: Theoretical Aspects and Scientific
Methodology” on 11-13 April 2024 in Sofia, Bulgaria.
877
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A. Online Resources
Code for this paper is available via GitHub.
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