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Landscape Research
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Potential of airborne LiDAR data in detecting
cultural landscape features in Slovakia
Juraj Lieskovský, T. Lieskovský, K. Hladíková, D. Štefunková & N. Hurajtová
To cite this article: Juraj Lieskovský, T. Lieskovský, K. Hladíková, D. Štefunková & N. Hurajtová
(2022): Potential of airborne LiDAR data in detecting cultural landscape features in Slovakia,
Landscape Research, DOI: 10.1080/01426397.2022.2045923
To link to this article: https://doi.org/10.1080/01426397.2022.2045923
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Potential of airborne LiDAR data in detecting cultural
landscape features in Slovakia
Juraj Lieskovsk
y
a
, T. Lieskovsk
y
b
, K. Hlad
ıkov
a
c
,D.
Stefunkov
a
d
and
N. Hurajtov
a
a,e
a
Institute of Landscape Ecology, Slovak Academy of Sciences, Nitra, Slovakia;
b
Department of Theoretical
Geodesy and Geoinformatics, Slovak University of Technology, Bratislava, Slovakia;
c
Department of
Archaeology, Comenius University, Bratislava, Slovakia;
d
Institute of Landscape Ecology, Slovak Academy of
Sciences, Bratislava, Slovakia;
e
Faculty of Natural Sciences, Constantine the Philosopher University,
Nitra, Slovakia
ABSTRACT
High-resolution Light Detection and Ranging (LiDAR) scanners provide
detailed information on terrain surfaces, thus enabling the detection of
the topographic signatures of historical anthropogenic landforms over-
grown by trees or covered by the soil surface. This study aimed to
examine the potential of incoming nationwide LiDAR data for detecting
the cultural landscape features in Slovakia. We derived a detailed digital
elevation model from LiDAR points and adopted upgraded visualisation
techniques based on the combination of local relief models, sky view
factor, slope steepness, and colour blending. We visually identified
examples of different anthropogenic landforms and confirmed our find-
ings with existing literature. In addition, we provide examples of previ-
ously unknown historical anthropogenic landforms discovered from
LiDAR images. Finally, we discuss the potential and limits of LiDAR data
in exploring and protecting different groups of historic anthropogenic
landforms as remnants of past cultural landscapes in Slovakia.
KEYWORDS
LiDAR; landscape
palimpsest; visualisations;
cultural landscapes;
landscape archaeology;
anthropogenic landforms
Introduction
The potential of Light Detection and Ranging (LiDAR) scanning to identify the topographic signa-
tures of past anthropogenic features was initially recognised in archaeology at the beginning of
the 21st century (Doneus & Briese, 2013; Luo et al., 2019; Risbøl, 2013). This was demonstrated,
for example, in the Stonehenge landscape survey (Bewley et al., 2005) and the identification of
Mayan settlements and infrastructure (Canuto et al., 2018). LiDAR is considered a revolutionary
tool in the archaeological toolbox (Bewley et al., 2005; Chase et al., 2012), opening possibilities
for identifying and documenting traces of past anthropogenic activities hidden in the landscape
(Doneus & Briese, 2013; Gojda & John, 2013; Mleku
z, 2013).
The airborne LiDAR systems measure surface elevation using repeated emission of a laser
pulse from a LiDAR system placed on an aeroplane or drone. The elevation is derived from the
precisely recorded time until the laser beam is reflected back to the LiDAR sensor. Each recorded
time stamp represents one point on the ground surface with geographic coordinates and eleva-
tion. Points are then interpolated to a very detailed digital surface model, or a digital elevation
CONTACT Juraj Lieskovsk
yjuraj.lieskovsky@savba.sk
Supplemental data for this article is available online at https://doi.org/10.1080/01426397.2022.2045923.
ß2022 Landscape Research Group Ltd
LANDSCAPE RESEARCH
https://doi.org/10.1080/01426397.2022.2045923
model if the points representing vegetation or artificial objects on the earth are filtered out. The
LiDAR images are created by applying visualisation techniques that highlight the terrain uneven-
ness and topographic signatures of anthropogenic landforms.
The fundamental benefits of LiDAR are the speed of data acquisition on a landscape scale,
the quality of its surface data, and its ability to identify macro- and micro-topographical features
that are otherwise undetected by terrestrial surveys (Canuto et al., 2018; Doneus & Briese, 2013).
LiDAR data combined with aerial and terrestrial prospecting and field excavation provide a better
understanding of the relationship between humans and landscapes (Gojda & John, 2013; Henry
et al., 2020; Johnson & Ouimet, 2018). The use of LiDAR in archaeological and cultural heritage
applications was reviewed by Luo et al. (2019).
The interpreted landscape features from LiDAR data can be considered as LiDAR landscape
palimpsest (Johnson & Ouimet, 2018). The term ‘palimpsest’has been used to describe a land-
scape in archaeology (Bailey, 2007) and other disciplines, including landscape ecology (Antrop &
Van Eetvelde, 2017), geography (Marvell & Simm, 2016), and geomorphology (Bloom, 2002).
Palimpsest involves the total removal of past landscapes, except the recent as well as superim-
position and overlay of traces of human activities and natural processes from different time peri-
ods (Antrop & Van Eetvelde, 2017; Bailey, 2007). Tarolli et al. (2019) described anthropogenic
landscapes as socio-cultural palimpsest and classified anthropogenic landforms into symbolic,
habitation, transport and exchange, subsistence, mining, refuse disposal, and warfare categories.
Cultural landscape research shares a common interest with landscape archaeology in terms of
relationships between people and the environment (F€
orster et al., 2013). LiDAR now provides the
opportunity for both disciplines to map the topographic signatures of human activity on a land-
scape scale (Johnson & Ouimet, 2018; Risbøl, 2013).
Although LiDAR initially provided data only in the 1–5 points per square metre density range,
technological advances now enable it to scan large areas at unprecedented point densities. The
area of Slovakia is being scanned from 2017 at a resolution of 20–30 points per square metre
and is scheduled to be completed by 2023 (Leitmannov
a & Kalivoda, 2018). LiDAR data has
begun to be implemented in Slovak archaeological research and cultural heritage management
(Bist
ak et al., 2019; Hor
n
ak & Zachar, 2017; Lieskovsk
y & Faixov
a Chalanov
a, 2020; Neumann,
2021;
Steiner, 2020). Following the examples from local and regional studies (Antrop & Van
Eetvelde, 2017; Canuto et al., 2018; Gheyle et al., 2018; Godone et al., 2018), we decided to
examine the potential of incoming nationwide LiDAR data to detect the cultural landscape fea-
tures in Slovakia. We explored examples of historical anthropogenic landforms and discussed the
potential and limits of LiDAR data to explore and protect different groups of historic anthropo-
genic landforms as remnants of past cultural landscapes in Slovakia.
Materials and methods
Study area
Slovakia, a country located in the Central European region (Figure 1), has been shaped by chang-
ing cultures since prehistory. Early subsistence farming and initial amplified landscape transform-
ation in Slovakia are related to ongoing Neolithisation from the 6th millennium BC (Bene
s, 2018).
The transformation from hunting and gathering to a settled lifestyle, domestication of animals,
cultivation of plants, and population spatial expansion has provided strong geomorphic evidence
of anthropogenic impacts (Bogaert et al., 2014; Tarolli et al., 2019).
The earliest fortified hilltop settlements were apparent in the Eneolithic era in the second half
of the 5th millennium BC (Pe
ska et al., 2019) and fortifications became an integral part of low-
land settlements from the Early Bronze Age (B
atora et al., 2012). This was followed by medieval
and post-medieval village creation in previously uninhabited areas (
Caplovi
c et al., 1985). The
earliest appearance of burial mounds in Slovakia was a characteristic of Eneolithic societies, and
2 J. LIESKOVSKÝ ET AL.
their traces were visible in post-medieval times. Additional anthropogenic landforms such as ter-
races and ‘holloways’appeared in the prehistoric and medieval periods as well.
The Slovak cultural landscape changed completely during the 20th century. The socialistic col-
lectivisation of agriculture destroyed most of the earlier cultural landscape features. Small-scale
mosaics of agricultural fields transformed into large-scale fields. In addition, the transition to a
market economy after 1989 was accompanied by changes in industrial production, with concur-
rent agricultural decline and abandonment (Paz
ur et al., 2020; Paz
ur & Bolliger, 2017). Finally, the
European Union (EU) accession in 2004 promoted the stimulation of large-scale agriculture, and
Slovak industrial production became focussed on car manufacturing.
Consequently, combined collectivisation, the market economy, and EU accession altered most
Slovak agricultural landscapes (Bez
ak & Mitchley, 2014; Kanianska et al., 2014)to‘intensity and
value focussed cultural landscapes, leading to forest landscapes now having a ‘persistence and
value focussed identity (Tieskens et al., 2017).
LiDAR data processing
The nationwide airborne LiDAR scanning in Slovakia was initiated in 2017 under the Geodesy,
Cartography and Cadastre Authority of the Slovak Republic administration, and its completion is
scheduled in 2023. The classified LiDAR point cloud is freely available at 20–30persquaremetre
density and approximately 5–6 cm horizontal and vertical accuracy (Leitmannov
a & Kalivoda, 2018).
For the interpolation of the LiDAR points to digital elevation models, we used points classified
as ground and buildings. We applied the Delaunay triangular irregular network interpolation
using the LidarTINGridding tool from the Whitebox GAT 1.4.0 software (Lindsay, 2016).
Interpolation to a triangular irregular network has two advantages: first, it is less demanding in
terms of computing capacity; second, the triangles in visualisations indicate the areas without
LiDAR points, where the visual interpretation is uncertain.
We upgraded the visualisation techniques based on a simple local relief model (Kokalj &
Hesse, 2017) by adding a local dominance to relief curvature representation and also adding a
Figure 1. Location of presented examples of cultural landscape features. The exact location is presented in Supplement 1.
LANDSCAPE RESEARCH 3
combination of slope steepness and sky view factor to relief contrast visualisation. Our LiDAR
images represent the convex features in a blue-green colour, the concave features in yellow, and
the dynamics of relief changes by changes in the intensity of red colour. Image contrast repre-
sents the combination of the sky view factor and slope steepness. Visualisations were adjusted
for flat (for example, Figure 2C, 7A,7B) and for hilly terrain (for example, Figures 3B,4B). To
derive the sky view factor and local dominance from the digital elevation model, we used the
Raster visualisation toolbox 2.2.1. For the final combination and visualisation of the derived
layers, we used Quantum GIS 3.18.
Identification of historical anthropogenic landforms in Slovakia
We visually identified the topographic signatures of historical anthropogenic landforms in images
with a pixel resolution of 1 m (for example, Figures 3A and 4B), where overexposed and oversa-
turated large-scale features such as walls and shallow ditches were easily visible. Greater details
of the less obvious features were then visualised from the digital elevation model with a 50cm
resolution (for example, Figures 4A and 5C) or a 25 cm resolution (for example, Figures 2B and
3C). To ensure the reliability of the presented examples, we present the images of the objects
Figure 2. Examples of symbolic structures: (2A) –burial mounds (location, Skalica, 9
th
century); (2B) –abandoned civilian
cemetery (location,
Cabradsk
y Vrbovok, 19
th
century); (2C) –ditch enclosure (location, Golianovo, 5000 BC); (2D) –Baroque
garden (location,
Cerven
y Kame
n, c. 18
th
century). The convex features are represented in blue-green, concave features in yel-
low, and dynamics of relief change by changes in the intensity of red colour. For the exact location, see Figure 1 and
Supplement 1.
4 J. LIESKOVSKÝ ET AL.
that are previously known from the literature. Even though we did not systematically scan the
LiDAR images, we discovered many unknown historical anthropogenic landforms that require
verification. Some of them are presented in the Conclusion section, and their uncertainty is
acknowledged.
We followed the anthropogenic landform ontology proposed by Tarolli et al. (2019) and we
present the landforms under the following categories: (1) ‘symbolic’comprising graves, gardens,
and monuments; (2) ‘habitation’comprising cities, villages, settlements, and housing; (3)
‘transport and exchange’comprising roads and railways; (4) ‘subsistence’comprising agricultural
terraces and ploughed furrows; (5) ‘mining’comprising mines and quarries, and (6) ‘refuse dis-
posal and warfare’comprising ditches, fortifications, and bomb craters.
Results and discussion
Symbolic anthropogenic landforms
The most easily detected symbolic anthropogenic landforms are the cemetery features. Figure
2A depicts a group of burial mounds near Skalica from the 9th century (Bist
ak et al., 2019;
Figure 3. Examples of habitation structures: (3A) –habitation structure in lowlands (location, Vr
able-Fidv
ar, c. 2000 BC); (3B) –
habitation structure in hills (location, Smolenice-Molp
ır, 7
th
–6
th
centuries BC); (3C) –abandoned dispersed settlement (loca-
tion, P
ıla-Horn
ıJakalovci, 15
th
–20
th
centuries). The convex features are represented in blue-green, concave features in yellow,
and dynamics of relief change by changes in the intensity of red colour. For the exact location, see Figure 1 and
Supplement 1.
Figure 4. Examples of transport structures: (4A) –holloways (location, Zvolen, medieval to post-medieval period); (4B) –aban-
doned forest railway structure (location, Pernek, 20
th
century). The convex features are represented in blue-green, concave fea-
tures in yellow, and dynamics of relief change by changes in the intensity of red colour. For the exact location, see Figure 1
and Supplement 1.
LANDSCAPE RESEARCH 5
Hlad
ık et al., 2020). According to the results of the LiDAR analysis, the Monuments Board of
the Slovak Republic is preparing a declaration of a burial mound near Skalica and Gbely for
national cultural monuments. Figure 2B shows a more recent abandoned civilian cemetery,
probably from the 19th century in the
Cabradsk
y Vrbovok (Mi
no, 2010). While abandoned
Jewish or war cemeteries could be detected as well, simple prehistoric and early medieval
flat cemeteries were not detectable. For their identification, other methods such as remote
sensing (satellite images, vertical aerial photos, etc.), geophysical methods, and field surveys
may be used.
Other symbolic features include prehistoric ditch enclosures and roundels (Figure 2D) that
most likely commemorated sacred communal sites (Mat
akov
a, 2012; Pav
uk & Karlovsky, 2004).
Figure 2D depicts the burial area in the Golianovo village, approximately dated to the 5th millen-
nium BC (Kuzma & Cheben, 2012).
Figure 2C then highlights the remnants of an early symbolic Baroque garden at the
Cerven
y
Kame
n Castle. This provides an example of anthropogenic landforms associated with gardens,
and while the primary geometric structures remain visible, the enclosure is unique because
Baroque gardens were typically in open landscapes (Neumann, 2018).
Cultural landscapes reflect specific land usage practices and human’s spiritual relationship
with nature (Mitchell et al., 2009). The sites with religious significance have been an important
part of the landscape since prehistoric times. Besides the cemetery shown in Figure 2B, we can
identify further mass graves that are the result of major disasters, war casualties, and pandemics;
many churches also have graves on-site (Blau et al., 2018). In addition, Slovak Calvary, Stations of
the Cross, Trinity and Marian columns, pilgrimage sites, and agricultural landscape chapels have
become important symbolic places (Mat
akov
a, 2012).
Similar to how human spiritual perception is reflected in symbols, human nature is invested
in gardens and their architecture (Klagyivik, 2011). Landscaping has created sidewalks, flower
beds, terraces, fences, ponds, and other garden elements. This provides recognisable remains
that can be traced and mapped in LiDAR images (Harmon et al., 2006).
Habitation anthropogenic landforms
While airborne LiDAR scanning detects both the fortified lowlands illustrated in Figure 3A and
the hilltop settlements illustrated in Figure 3B, the detection of unfortified lowland features and
elevated settlements remains difficult. We were able to identify both the fortified settlements at
the Fidv
ar site near Vr
able shown in Figure 3A, which was inhabited around 2100–1450 BC
(B
atora et al., 2012) and the elevated settlement site at Molp
ır near Smolenice, shown in Figure
3B, which was predominantly inhabited in the Early Iron Age (M€
uller, 2012). Both these settle-
ments were important centres of political, socio-economic, religious, and refuge functions with
regional and inter-regional significance.
LiDAR also identifies other settlement types from medieval and post-medieval times. These
include abandoned villages or fortification features that are otherwise unobservable. Interesting
remnants of the P
ıla-Horn
ıJakalovci abandoned dispersed settlement in the Nov
aBa
na district
are depicted in Figure 3C. The settlement was founded by German colonists in the 15th century
and was abandoned and dissembled when the Germans were expelled after the Second World
War (
Solcov
a & Dubcov
a, 2009).
‘Settlements and territories should be regarded as the primary building blocks of the cultural
landscape’(Antrop & Van Eetvelde, 2017). Urbanisation is one of the main driving forces of land-
scape change (Antrop, 2005) and is increasing almost everywhere (Antrop, 2004; United Nations,
2019). Information about historical or abandoned urban areas is crucial for understanding
human-induced changes in the landscape.
6 J. LIESKOVSKÝ ET AL.
Transport/exchange networks
Transport/exchange infrastructure rapidly evolves with ongoing urbanisation. The remnants of
transportation networks are detectable in the LiDAR images (Figure 4), although the exact chron-
ology is difficult to determine. The ‘holloways’from the medieval and post-medieval eras in
Figure 4A show the communication network connecting the Pust
y hrad mountain-top settlement
in the Zvolen township with its surroundings (Pa
zinov
a et al., 2013). Figure 4B depicts the aban-
doned forest railway in the Pernek Malacky area. This dense forest railway network transported
loggers and their wood until the first half of the 20th century (Ondru
s, 2013).
During its long history, many important roads passed through the territory of Slovakia. In add-
ition to connecting settlements, many were of military or commercial importance (Ivani
c, 2011).
From the period of the early and high Middle Ages, we know two important paths of suprare-
gional significance in Slovakia, referred to as Via Magna. The first one connected Moravia and
Ko
sice and passed through Western Slovakia. The second one connected the Kingdom of
Hungary and Poland and passed through central Slovakia near Pust
y hrad (Hanuliak, 1996). In
addition, the important road Via Bohemica connected Buda with Prague and passed through
Western Slovakia (Hunka & Ruttkay, 1998).
Trails, paths, and roads are essential structures of the human landscape (Snead et al., 2010).
Roads and road landscapes can be considered cultural heritage (Grazuleviciute-Vileniske &
Matijosaitiene, 2010). Figure 4 shows that LiDAR can identify prehistoric and historic roads and
railway networks and aid the precise location of acknowledged historic transport infrastructure.
Information on transportation networks and corridors is crucial for landscape history, land-
scape ecology, and land-use science. Isolation is one of the determinants of cultural landscape
hotspot preservation (Lieskovsk
y et al., 2014; Solymosi, 2011) and the construction of roads can
be a precursor to landscape changes (B€
urgi et al., 2004). The distance from roads is related to
agricultural land abandonment (Baumann et al., 2011; Prishchepov et al., 2013), whereas accessi-
bility drives the development of agricultural land (Hatna & Bakker, 2011; MacDonald et al., 2000)
and accelerates urbanisation (Antrop, 2004), deforestation (Laurance et al., 2002; Nagendra et al.,
2003), and other processes in the landscape (Geurs & van Wee, 2004).
Subsistence anthropogenic landforms
Typical subsistence anthropogenic landforms are agricultural terraces and stonewalls (
Spulerov
a,
Dobrovodsk
a, et al., 2017; Varotto et al., 2018). Those that originated in Slovakia before agricul-
tural collectivisation are the most valuable traditional agricultural landscapes (Baran
cokov
a&
Baran
cok 2020; Bug
ar et al., 2020;
Spulerov
a, Bez
ak, et al., 2017). Figure 5B shows the traditional
terraces in Liptovsk
a Tepli
cka, which originated in the 17th–19th centuries (Dobrovodsk
a, 2014;
Kenderessy et al., 2020). Most of the traditional agricultural landscapes were destroyed during
the socialist agricultural collectivisation in the second half of the 20th century (Lieskovsk
y et al.,
2014); however, some terraces for vineyards or orchards cultivation originated during collectivisa-
tion (Figure 5C).
Figure 5A depicts the hilltop Sitno terraces that most likely originated in the prehistoric
period and were used as settlement areas in the medieval and post-medieval eras. While these
terraces were created for agriculture, later-period slag and technical pottery findings are related
to the metallurgical activity (Hajnalov
a, 1990;
Zebr
ak, 1985). LiDAR can detect the additional sub-
sistence landforms of field fences, walls, hedgerows, and furrows.
The agrarian wall and terrace systems already existed in developed ancient European cultures
(Price & Nixon, 2005) and these were especially apparent in the Mediterranean area (Andlar
et al., 2017; Tarolli et al., 2014). These landscapes and other relict agrarian landforms now have
great bio-cultural value (Agnoletti et al., 2011; Cullotta & Barbera, 2011; Dobrovodsk
a et al., 2019;
Poschlod & Braun-Reichert, 2017) and are often protected as cultural heritage (Andlar et al.,
LANDSCAPE RESEARCH 7
2017; Kladnik et al., 2017). However, these are often threatened by abandonment and afforest-
ation (Lieskovsky et al., 2013; Momirski & Kladnik, 2009;
Spulerov
a, Bez
ak, et al., 2017; Tarolli
et al., 2014), urbanisation and agricultural intensification, heavy-machinery land-levelling, and the
construction of landslide-prone bench terraces (Cots-Folch et al., 2006). Moreover, abandoned
terraced areas on steep slopes are now threatened by mass waste and the risk of soil erosion
(Cammeraat et al., 2005; Koulouri & Giourga, 2007; Lesschen et al., 2008).
Mining anthropogenic landforms
Mining activities have significantly transformed landscapes since prehistory. The intentionally cre-
ated or accidental surface mining relief is still apparent in the landscapes (Hron
cek, 2011;
Jan
cura et al., 2010). The intentionally created mining landscape features include terraces and
embankments with associated escarpments in quarries, underground tunnel entrances, pits, and
pit clusters in skilled mining zones. An example of the gold exploitation area between Chvojnica
and Malinov
a on the eastern slope of Mal
a Magura (Hvo
zd'ara, 1999) is illustrated in Figure 6C.
The incidentally formed mining landforms include cover subsidence and cover-collapse pingen
ranging from a few square metres to kilometres (Jancewicz et al., 2021; Krokusov
a&
Cech, 2014).
Figure 6A depicts the wetlands in the upper Nitra mining region, which originated after surface
Figure 5. Examples of subsistence structures: (5A) –prehistoric terrace structures (location, Sitno, prehistoric period); (5B) –
traditional terrace structures (location, Liptovsk
a Tepli
cka, c. 17
th
–18
th
centuries); (5C) –collectivization terrace structure (loca-
tion,
Cel
are, 20
th
century). The convex features are represented in blue-green, concave features in yellow, and dynamics of
relief change by changes in the intensity of red colour. For the exact location, see Figure 1 and Supplement 1.
Figure 6. Examples of mining areas: (6A) –wetlands resulting from underground coal mining (location, Ko
s, end of 20
th
cen-
tury); (6B) –mining landscape (location, Bansk
a Hodru
sa, c. 13
th
–20
th
centuries); (6C) –gold exploitation area (location,
Chvojnica and Malinov
a, 14
th
–20
th
centuries). The convex features are represented in blue-green, concave features in yellow,
and dynamics of relief change by changes in the intensity of red colour. For the exact location, see Figure 1 and
Supplement 1.
8 J. LIESKOVSKÝ ET AL.
subsidence caused by underground coal mining (Petrovic et al., 2008; Svitok et al., 2011), and
Figure 6B highlights the mining landscape in the Bansk
a Hodru
sa area that originated in medi-
eval times (Hron
cek et al., 2018; Hrub
y et al., 2016).
Quarrying and mining can have significant negative impacts on environmental quality (Vrablik
et al., 2017), natural habitats (Butsic et al., 2015), or buildings and infrastructure (Krokusova et al.,
2015). In contrast, abandoned mines and quarries enhance geo- and biodiversity (Bene
s et al.,
2003;B
etard, 2013; Woch et al., 2017) and are potential destinations for geo-tourism (Hut
arov
a
et al., 2021) or education and recreation (Ka
zmierczak & Strzałkowski, 2019; Vrablikova
et al., 2016).
Here, LiDAR data provide new insights into mapping and classifying geomorphologic mining
features, as well as their distribution, dimensions, and spatial relationships. This knowledge is
important for research on landscape change, especially for monitoring landform evolution
(Jancewicz et al., 2021) and providing greater insight into archaeology and mining history
(Fabbri et al., 2021; Gawior et al., 2017).
Water infrastructure
Typical anthropogenic water infrastructures include artificial river beds, channels, and ditches
constructed for irrigation, amelioration, and flood control. Although most Slovak water infrastruc-
ture was constructed during socialism, some large projects began at the end of the 19th century
(Pi
s
ut, 2002). Figure 7A shows the
Zitava river channels created in the second half of the 20th
century and the remnants of old meanders near the Fidv
ar Early Bronze Age settlement
(Nowaczinski et al., 2015). The ditches in the Lid
er Tejet locality highlighted in Figure 7B were
constructed during the time of socialism for irrigation and amelioration. The maintenance for
many of these was abandoned, and these consequently became ground-levelled or overgrown
by vegetation (Halmo & Alena, 2011). They serve as bio-corridors and provide various ecosystem
services (Izakovi
cov
a et al., 2020; Kalivoda, 2016; Kozelov
a et al., 2020).
Special water management systems were constructed for mining purposes in medieval and
early modern Slovakia (Hron
cek et al., 2019). The created ponds and water channels supplied
water for mining machinery, and then for shaft drainage (Kubinsk
y et al., 2014). The most famous
Slovak water management system at Bansk
a
Stiavnica is now on the UNESCO World
Heritage List.
Figure 7. Examples of water infrastructure areas: (7A) –melioration structure and former meanders of river
Zitava (location,
Vr
able-Fidv
ar, Early Bronze Age settlement); (7B) –irrigation channels (location, Lid
er Tejet). The convex features are repre-
sented in blue-green, concave features in yellow, and dynamics of relief change by changes in the intensity of red colour. For
the exact location, see Figure 1 and Supplement 1.
LANDSCAPE RESEARCH 9
The oldest types of catch-drained or irrigated meadows and pastures provided quality live-
stock feed (Sl
amov
a et al., 2015; Smith & Stamper, 2018). These ‘water meadows’were wide-
spread throughout Europe in the Middle Ages and they now form an important part of
landscape heritage (Renes et al., 2020). Historical irrigation canals could also be protected and
considered natural and cultural heritage (Ricart et al., 2019). Small water reservoirs were typical
and beneficial in the Central European medieval agricultural landscape (Juszczak & KeRdziora,
2003; Pavelkov
a et al., 2016). They played a significant role in local groundwater management,
served as bio-centres and recreational areas, and also provided water retention for fire-fighting
(Pavelkov
a et al., 2016). However, this system is now almost extinct, and information on it is
sporadic (Neumann, 2016).
The most important water infrastructure is recorded on historical maps (Pavelkov
a et al.,
2016). LiDAR images could help to precisely determine the infrastructure locations or identify
unmapped water infrastructures such as ditches, water channels, or ponds. Additionally, old nat-
ural riverbeds and meanders are also visible on LiDAR images (Figure 7).
Refuse disposal
Physical remnants of resource exploration activities vary in size from small household middens
to large waste landfills (Tarolli et al., 2019). Figure 8A highlights the landfill from the Sered'
Nickel Smelter in Sered', which produced nickel from 1963 to 1993. This is now considered an
environmental burden and a source of air, soil, and water pollution (Michaeli et al., 2012), and
scientists are therefore implementing revitalising schemes such as planting suitable vegetation
(
Ciernikov
a et al., 2021). However, unsightly waste landfills still exist, and Figure 8B depicts the
landfill constructed in Michal nad
Zitavou in 1992 (Spi
siak, 2007).
Landfills adversely affect the environment and landscapes, while some cause underground
and surface water contamination, air pollution, fire hazards, cover subsidence, and potential land-
slides (De Wet, 2016; Hroncov
a et al., 2020; Suflita et al., 1992). Large industrial landfills are visu-
ally manifested in the landscape as human-made hills (Wei et al., 2018) and their remediation is
very difficult. Old landfills could be transformed into fauna and flora refuges in a relatively sterile
industrial or urban environment (Wiezik, 2006) or form local biodiversity hotspots in the agricul-
tural landscape (Baranov
a et al., 2015).
Detrimental wildlife and human health hazards must be counteracted, and it is therefore
important to first have precise data on these refuse disposal sites and their contents, and then
Figure 8. Examples of waste disposal areas: (8A) –nickel hold (location, Doln
a Streda); (8B) –waste disposal (location, Michal
nad
Zitavou, 1992). The convex features are represented in blue-green, concave features in yellow, and dynamics of relief
change by changes in the intensity of red colour. For the exact location, see Figure 1 and Supplement 1.
10 J. LIESKOVSKÝ ET AL.
be diligent in monitoring and eradicating extreme dangers (Biotto et al., 2009; De Wet, 2016).
LiDAR provides high-resolution data on landfill topography, including the subtle surface changes
that can warn authorities of precipitous anthropogenic and natural disasters at the site (De
Wet, 2016).
Warfare infrastructure
LiDAR scanning is extremely beneficial in identifying military structures, especially those hidden
in forested areas. These include trenches, bunkers, and enclosures from the Napoleonic wars,
World War II, the Slovak National Uprising, and remnants from other conflict sites. Figure 9
depicts a rectangular enclosure with vertical linear features from the 1809 Napoleonic siege of
Bratislava. The fortification was temporarily re-employed during the Second World War
(Kov
a
c, 2019).
The LiDAR images also identified many remains of Slovak south-western defensive trenches,
mortar emplacements, and bunkers constructed during the Second World War. The example in
Figure 9A shows a trench system with mortar positions from the warfare discovered in a forested
area near the Bukov
a Pass (V
sivavec area) constructed by Germans in 1945 (Neumann, 2021).
Despite the increasing attention of archaeologists and geographers on war heritage and mili-
tary landscapes (Havl
ı
cek et al., 2018; Rech et al., 2015; Woodward, 2014), only a few studies
have mapped the traces of war conflicts on a landscape scale (Gheyle et al., 2018; Schriek, 2020).
The availability of LiDAR to produce a detailed elevation model of large areas enables us to
reveal remnants of past conflicts and warfare infrastructure (Dolej
s et al., 2020; Maio et al., 2013;
Steiner, 2020) as shown in Figure 9. The historical war infrastructure could be an interesting cul-
tural heritage (Dobinson et al., 1997; Seitsonen, 2017). Armed conflicts also have fundamental
and often long-lasting effects on land systems and land use patterns (Baumann & Kuemmerle,
2016; Butsic et al., 2015); therefore, mapping the military landscapes could also be interesting for
land system scientists. Additionally, inaccessible warfare areas, military training areas, and cold-
war boundaries now provide a natural refuge for animal and plant species (Havlick, 2007). A
prime example is the former ‘Iron Curtain’boundary, which extends the European green belt
(Zmelik et al., 2011).
Figure 9. Examples of warfare areas: (9A) –rectangular fortification (location, Bratislava-Pe
cniansky les, 1809); (9B) –defensive
trenches with mortar position (location, V
sivavec area, Little Carpathians, 1945). The convex features are represented in blue-
green, concave features in yellow, and dynamics of relief change by changes in the intensity of red colour. For the exact loca-
tion, see Figure 1 and Supplement 1.
LANDSCAPE RESEARCH 11
Conclusion
The new possibilities and advances that LiDAR brings indicate the high potential of LiDAR
images for cultural landscape research and protection in Slovakia. The LiDAR images highlight
the natural and anthropogenic geomorphic features that are not visible in aerial pictures or, in
some cases, even in the field. In addition to the previously known symbolic features, the new
burial mounds near Un
ın or new fascinating ditch enclosures were discovered. Traces of previ-
ously unknown settlements, for example, near Topol'
cany, Brodsk
e, or Vel'k
aMa
na, have also
been detected and need to be verified by archaeologists. Historical roads are still only a marginal
point of interest in Slovakia. LiDAR images, in combination with cartography sources and histor-
ian knowledge, could help to trace and refine the historical roads. This will contribute to a better
understanding of the movement of goods and people, and possibly also explain the function of
solitary settlements in the landscape. Although the nationwide mapping of traditional agricul-
tural landscapes was realised in Slovakia in 2010, the LiDAR images show the remnants of over-
grown stonewalls or terraces that were not visible in aerial pictures. These include previously
unknown prehistoric terraces in the Sitno or Tribe
c mountains. Dry stone-walled and terraced
landscapes are considered as cultural heritage in southern Europe, and we believe that the new
complex knowledge of historical and prehistorical terraced landscapes could help in protecting
the most valuable landscapes in Slovakia. Besides the well-known mining landscapes around
Bansk
a Bystrica, Bansk
a
Stiavnica, and Kremnica, few mining landscapes have been studied in
the alpine parts of Low Tatras mountains or the Juhoslovensk
a basin. We see the high potential
of LiDAR data for mapping the remnants of mining infrastructure and mining landscapes in
those areas, as well as in other areas where the information from historical maps or archives is
limited. The historical ‘water meadows’are considered cultural heritage in some countries. Such
meadows were identified in aerial pictures combined with field research around Pol'ana moun-
tains and the use of LiDAR is planned for further research in larger areas. Refuse disposals have
a negative impact on the surrounding environment, and LiDAR could help to precisely quantify
their area and volume. Published warfare elements were found in the southern part of Slovakia,
and there is a high potential for LiDAR use in the identification of other warfare features. LiDAR
images from Eastern Slovakia, where the most intensive battles from both the World Wars
occurred, will be and available in 2022
While LiDAR can provide precise measurements of the height, length, and volume of
anthropogenic features, the LiDAR images do not provide reliable information on their function,
age, and origin. Additional data are therefore essential for accurate interpretation; and interdis-
ciplinary cooperation with geomorphologists, hydrologists, geologists, and other disciplines is
often needed. LiDAR detects only the structures with clear topographical manifestations in the
landscape. Soil erosion, inundation, and human activities often wipe out the topographic finger-
prints. In Slovakia, the fertile lowlands were heavily transformed by agricultural activities after
the second half of the 20th century. However, areas without topographic signatures cannot be
considered as areas without past human activities.
Acknowledgments
We are very grateful to the three anonymous reviewers for critically reading the manuscript and suggesting sub-
stantial improvements.
Disclosure statement
No potential conflict of interest was reported by the author(s).
12 J. LIESKOVSKÝ ET AL.
Funding
This work was supported by the Slovak Scientific VEGA agency under Grant No. 2/0018/19 “Ecological Analyses of
Landscape Acculturation in Slovakia since Early Prehistory until Today”, Grant No. 1/0100/19 “Knowledge of the
Bronze Age Economy and Society in the Area north of the Middle Danube by the Archaeological and
Environmental Sources”, Grant No. 1/0468/20 “Development of innovative approaches to cartographic visualisation
of the data obtained by aerial laser scanning “and UGA agency under Grant No. VIII/9/2021 “Research of human
impact on the landscape and its historical development using an interdisciplinary approach”. This publication is the
result of the project implementation: “Scientific support of climate change adaptation in agriculture and mitigation
of soil degradation”(ITMS2014 þ313011W580) supported by the Integrated Infrastructure Operational Programme
funded by the ERDF (20%).
Notes on contributors
Juraj Lieskovsk
y, PhD. is a senior research scientist at the Institute of Landscape Ecology of the Slovak Academy of
Sciences (ILE SAS). He is an expert in GIS analysis, synthesis and visualisation, database design and analyses. His
research focuses on modelling and analysing soil erosion and landscape changes and their driving forces. He has
participated in several international projects, including EUFP projects (OpenNESS, HERCULES, EBONE, Alter-Net) and
NASA Land-Cover and Land-Use Change programme projects. Juraj Lieskovsk
y also works as a GIS expert in the
European Topic Centre on Biological Diversity. He finished his Ph.D. thesis at the Institute of Landscape Ecology
SAS in 2010 and then held a post-doctoral fellowship at the Swiss Federal Institute for Forest, Snow and Landscape
Research WSL from 2013 to 2016.
Tibor Lieskovsk
y, PhD. is a lecturer and researcher at the Slovak University of Technology in Bratislava. He is cur-
rently working on spatial modelling and data integration in the field of cultural heritage, and most recently he spe-
cialises in digital elevation models and their visualisation for specific purposes. This especially includes the
protection of cultural and historical heritage. Tibor Lieskovsk
y has participated in research projects in Guatemala,
Iraq, Sudan, Egypt and Syria in the fields of GIS, photogrammetry and land surveying. He is a member of the
PACUNAM LiDAR Initiative which is a consortium of research institutions using the LiDAR data in archaeology.
Finally, Tibor completed his Ph.D. thesis on archaeological predictive modelling at STU Bratislava in 2011.
Katar
ına Hlad
ıkov
a, PhD. works as an assistant professor at the Department of Archaeology at the Comenius
University in Bratislava, Slovakia, where she completed her Ph.D. in 2013. She teaches the courses Computer
Application in Archaeology, GIS in Archaeology, and courses related to protohistory. Her research focus is targeted
on the social archaeology of later European prehistory and protohistory, and landscape archaeology. She partici-
pated on several national research projects. She received a six-month Post-Doctoral Scholarship at the University of
Vienna at the Department of Prehistoric and Historical Archaeology in 2020.
Dagmar
Stefunkov
a, PhD. is a senior researcher at the Institute of Landscape Ecology of the Slovak Academy of
Sciences (ILE SAS). Her research focuses on cultural landscapes and their development trajectories. She is a member
of the EUCALAND international expert network where she is co-author of several studies devoted to different types
of European agrarian landscapes and their bio-cultural values. Dagmar
Stefunkov
a completed her Ph.D. thesis in
2004 in ILE SAS, and has since participated in several national and international projects. Amongst others, they
include the Landscape Atlas of Slovak Republic, Research and maintenance of biodiversity in historical structures of
the agricultural landscape of Slovakia, Rural Etinet and ALTER-Net.
Nat
alia Hurajtov
ais a doctoral student at the Institute of Landscape Ecology of the Slovak Academy of Sciences
(ILE SAS). The topic of her Ph.D. thesis is ‘The Impact of Human Activities on the Landscape Structure in Historical
Perspective’. Her research focuses on the reconstruction of past human activities, and this is based on analysing
macro-remains, old maps and archival documents and preserved historical structures captured by aerial laser scan-
ning. Finally, Nat
alia Hurajtov
a is a member of The Slovak Archaeological Society (SAS).
ORCID
Juraj Lieskovsk
yhttp://orcid.org/0000-0002-9779-8340
T. Lieskovsk
yhttp://orcid.org/0000-0001-6015-5926
K. Hlad
ıkov
ahttp://orcid.org/0000-0002-9689-7419
D.
Stefunkov
ahttp://orcid.org/0000-0001-7929-7481
N. Hurajtov
ahttp://orcid.org/0000-0002-9296-4944
LANDSCAPE RESEARCH 13
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