QuaternaryInternational566-567(2020)163–170
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Quaternary International
journal homepage: www.elsevier.com/locate/quaint
Hidden images in Atxurra Cave (Northern Spain): A new proposal for visibility analyses of Palaeolithic rock art in subterranean environments
Iñaki Intxaurbea,d, Olivia Riverob, Ma Ángeles Medina-Alcaidec, Martín Arriolabengoad, Joseba Ríos-Garaizare, Sergio Salazarb, Juan Francisco Ruiz-Lópezf, Paula Ortega-Martínezg, Diego Garatea,∗
a Instituto Internacional de Investigaciones Prehistóricas de Cantabria (IIIPC, Gobierno de Cantabria, Universidad de Cantabria, Santander). Edificio Interfacultativo, Avda. Los Castros s/n, 39005, Santander, Spain b Dpto. Prehistoria, Historia Antigua y Arqueología, Universidad de Salamanca, 37008, Salamanca, Spain c Dpto. Historia, Facultad de Letras, Universidad de Córdoba, 14071, Córdoba, Spain d Dpto. Mineralogía y Petrología. Euskal Herriko Unibertsitatea/Universidad del País Vasco, 48940, Leioa, Spain e Archaeology Program, Centro Nacional de Investigación sobre la Evolución Humana (CENIEH), Paseo Sierra de Atapuerca 3, 09002, Burgos, Spain f Dpto. de Historia. Universidad de Castilla – La Mancha, 16001, Cuenca, Spain g Independent Researcher
- A R T I C L E I N F O
- A B S T R A C T
Keywords:
Cave art Viewshed Archaeological context Cave geomorphology GIS
Visibility has been the subject of study in Palaeolithic rock art research ever since the discovery of Altamira Cave in 1879. Nevertheless, until now, the different approaches have been based on subjective assessments, due to computational limitations for a more objective methodology. Nowadays, cutting-edge technologies such as GIS allow us to address spatial studies in caves and overcome their geomorphologically complex and closed characteristics. Here we describe an innovative methodology that uses computing tools available to any researcher to study the viewsheds of the graphic units in decorated caves. We have tested its validity on the recently discovered rock art ensemble of Atxurra Cave, in Northern Spain. We demonstrate that this technology (GIS), widely used in other fields of archaeology, especially in outdoor studies, is also useable in caverns, taking into account the complex morphologies -ceilings and diverse floor-levels, for example. These programmes have also allowed us to consider the lighting systems used by the prehistoric groups inside the cave, as well as various data previously estimated by other authors, such as the height of individuals during the European LUP. The dynamism of these tools −2.5D-, as well as the advancement of new 3D GIS technologies, will allow in the future remarkable progress in these types of structural studies for a better understanding of Palaeolithic cave art phenomena.
Palaeolithic
1. Introduction: research precedents and objectives
by other researchers (Pastoors and Weniger, 2011).
The final aim of these studies is usually to observe patterns in the topographic distribution or organization of the rock art ensembles within the cave. These patterns can then be compared between different rock art sites (generally within the same geographical and chronological framework). This has led to numerous interesting proposals, from the use of the term of sanctuaries for these caves (Leroi-Gourhan, 1964) to inferences about their organization (González-Sainz, 2017) or even attempts to interpret their meaning in the form of sentences (Sanchidrián, 1992). Interest in spatial studies is more than justified, and for that reason methods should be developed that are as objective as possible, to validate the observations and avoid (as far as possible) all subjective interference or errors derived from personal appreciations.
The visibility (and invisibility or concealment) of Palaeolithic rock art images in European caves has attracted several researchers’ attention since the discovery of cave art in Altamira in 1879 (Sanz de Sautuola, 1880), and its subsequent approval by the scientific community in 1902 (Cartailhac, 1902). In recent years, this aspect has been considered by several authors, usually to compare decorated zones in the same cave, or to illustrate Point Of Views (POVs) of each figure or
panel on the cave plan (González-García, 2001; Villeneuve, 2008; Garate, 2010; Ruiz-Redondo, 2014; Ochoa and García-Diez, 2018;
Jouteau et al., 2019). They measure the visibility area in some cases, and compare it with such other spatial features as occupancy, estimated
∗ Corresponding author.
E-mail address: [email protected] (D. Garate). https://doi.org/10.1016/j.quaint.2020.04.027
Received 13 February 2020; Received in revised form 3 April 2020; Accepted 15 April 2020
Availableonline21April2020 1040-6182/©2020ElsevierLtdandINQUA.Allrightsreserved.
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- Most spatial studies involve estimating the visibility area on a cave
- recording method previously tested (Trimmis, 2018).
plan. The use of GIS is usually avoided, adducing the limitations produced by the three-dimensional features of caves, identified previously in a work in La Griega Cave (Ortega, 2014), and other reasons of costs or time consumption.
Prior to the geolocation process, and to minimize as much as possible any type of magnetic distortion that could alter the measurements, the device was calibrated within the karst system itself, and in particular, in the main gallery of Armiña Cave (the lower part of the cavesystem) (Fig. 2A).
Geolocating the archaeological elements with DistoX2 requires a process similar to the production of a conventional speleological survey, in which it is necessary to draw a polygonal starting from a point 0. To position this point 0 in space with coordinates in a specific datum, it can be georeferenced on the surface, using a differential GPS, for example. However, if a previously georeferenced point-cloud exists, as is the case of the caves that have been scanned three-dimensionally -and our case of Atxurra-, obtaining the coordinates of identifiable “reference points” (Fig. 2B and C) is easy, and the polygonal can be started from there.
The use of GIS in “sensorial” archaeology, and specifically in visi-
bility studies in rock art (Wheatley and Gillings, 2000; Gillings, 2015; Díaz-Andreu et al., 2017; Wernke et al., 2017; Wienhold and Robinson,
2017) has become very popular in recent years because of their precision and ability to interpret the terrain, despite their strengths and limitations, previously identified (Gillings, 2017). These techniques are usually employed in open-air studies, but some precedents are known in closed and three-dimensionally complex sites (Landeschi, 2019), including caves (Ortega, 2012, 2014). One of most successful analytical platforms directly uses the 3D mesh for different analyses of visibility in
these types of environments (Dell’Unto et al., 2016; Landeschi et al., 2016).
The general objective of the present paper is the implementation of
“digital technologies” (like GIS or 3D models) to advance in studies on the spatial structure of Upper Palaeolithic rock art ensembles in cave environments. As noted above, 3D GIS tools, like Lines of Sight (LOS), have been tested for visibility analyses in complex environments
(Landeschi et al., 2016, 2019; Landeschi, 2019). However, despite the
accurate results that could be obtained in simulations and archaeological analyses with these 3D GIS technologies, rapid conversions to 2.5D GIS technology can offer also valid results, for example for viewshed analyses of Palaeolithic rock art ensembles in caves. The specific objectives of the present study are: 1) to describe the steps followed using certain GIS programmes to obtain precise measurements of the viewshed areas of parietal figures, identifying and resolving the main limitations; 2) to test their validity in the cave of Atxurra (Northern Spain) and verify the results in situ, since its conditions are ideal for this purpose (decorated sectors hidden from the main transit zones in the passage, archaeological remains associated with parietal art and related to the illumination systems used by the artists, etc.); 3) to explain different kinds of visibility of images in the same cave regarding their location, but also in relation with their iconography and technique or the different illumination systems.
Once the fieldwork was carried out (Fig. 2D), the data was processed in the VisualTopo® (David, 2009) program, making the pertinent magnetic declination corrections. Finally, the data was converted to the datum of our choice (ETRS 89 UTM 30).
3. Methodology: analysing visibility using GIS inside the cave
3.1. Recreation of cave geomorphology
Atxurra Cave was scanned by the company Gim-Geomatics SL using a terrestrial Laser Scanner 3D Faro® Photon 120. Approximately 59.6 million points have been obtained per scan, in 538 scan stations. As for the accuracy of the operation, the estimated error is 1 mm per 25 m, with 90% reflectance. After this, the point cloud was treated with ArcGIS® by Gim-Geomatics SL to obtain two raster files. This work was done in “strict” 3D because in 2.5D it fails both on walls and when passages overlap. First a raster was defined with a cell size of about 2.5 cm on which we dump the data that interests us. In this case “minimum Z” is defined as the minimum value of the 3D mesh in that cell (if there are several nodes, only the minimum dimension) and “maximum Z” the maximum value. That is, search among all the nodes that fall in the cell, for example 5 × 5 cm2, (square defined by xmin, ymin, xmax, ymax) and choose the highest and lowest, to obtain two raster archives, representing the position of floor level (GroundDEM) and ceilings (CeilingsDEM). However, it is important to note that the procedure to import 3D files in GIS had already been defined (Opitz and
Nowlin, 2012).
2. Materials: the Palaeolithic rock art ensemble of Atxurra Cave
The cave of Atxurra is formed in Aptian-Albian reef limestone
(Lower Cretaceous) in the province of Biscay (Northern Spain) (Fig. 1A). Although this prehistoric site has been known since 1929 (Barandiarán, 1961), in 2015 a parietal art complex was discovered deep in the cave, with more than 100 engraved and painted animal figures in Upper Magdalenian style based on techno-stylistic conven-
tions (Garate et al., 2016, 2020).
In our case, the coordinates of 3D models (in at least 6 digits) was previously reduced to 3/4 digits, because of the size of files. The limitations of GIS software mean that editing 3D (ESRI, 2012) is impossible, so the coordinates could only be reconverted (creating a 2.5D GIS), once the rasters to be used had been extracted.
The panels with rock art are between 186 m and 366 m from the prehistoric entrance, in the upper level of the system, and they are located mainly above side-ledges reached by more or less dangerous climbs (Fig. 1B). Exhaustive exploration and identification fieldwork has been carried out between 2016 and 2020, and 257 Graphic Units (GUs) have been documented.
In addition, an enormous amount of Inner Archaeological Context
(IAC) remains have been documented near the rock art panels (usually under them). These types of vestiges provide valuable information about the “use-life” of the cave during the past (Clottes, 1993; MedinaAlcaide et al., 2018). Most attention was paid to remains stemming from the illumination systems, which provide useable data to make inferences about the kind of illumination used (Medina-Alcaide et al.,
2015, 2019).
Prior research had been carried out on karst geomorphology and cave evolution in Atxurra (Arriolabengoa et al., 2018, submitted). It proved that no great changes have taken place in the areas with rock art since the Upper Palaeolithic. Some detrital and lithochemical sedimentation has occurred -mainly in the lower part of the gallery-, but in terms of visibility, the current state resembles the original perceptions, which have not been altered by geomorphological evolution.
3.2. Processing GIS data
To perform visibility analysis in Atxurra, we obtained each GU's viewshed using the “Viewshed 2” analysis tool in ArcGIS®’s ArcMap™ (Fig. 3). To solve the main problems of these analyses (Gillings, 2017), we have calculated the maximum angle to observe these points, even 360° horizontal and 0-90° vertically. With this, we can calculate the maximum area within which each GU is visible, according to positive indivisibility between the observer and the rock art: i.e., “if the GU can
see me, I can see the GU”.
Once all forms of evidences in the cave (GUs and also IAC elements) had been documented, they were georeferenced using a DistoX2 device, in conjunction with a tablet using an Android system with Bluetooth, and with TopoDroid® (Corvi, 2015) application installed, following a
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Fig. 1. Location of analysed rock art ensemble. A: Position of Atxurra Cave in the Iberian Peninsula (source: https://www.juntadeandalucia.es/ institutodeestadisticaycartografia/DERA/). B: 3D model of Atxurra Cave, made by GIM-GEOMATICS, detailing the location of decorated sectors.
Fig. 2. Geolocation process using DistoX2. A: Calibration of DistoX2, in Armiña Cave. B: position of point 0 on a remarkable speleothem. C: Obtaining the coordinates of this last point in the point cloud, using SCENE LT© of FARO©. D: Geolocation of archaeological elements in the cave (IAC elements or GUs).
First of all, we have performed a prior step to consider the situation of ceilings, because our scenario -a subterranean gallery decorated with rock art-is three-dimensionally complex and enclosed. It consists of identifying the minimum value in altitude (minimum Z value) of each panel, reclassifying CeilingsDEM (the raster containing the Z values of ceilings) with the “Reclassify” tool, and after that weighting with “Weighted Overlay” tool. We assign high values (e.g. 9 value) when the altitudes of the ceilings are lower than our panel minimum Z (i.e. the ceilings can block the visibility), and we assign a “restricted” value when the altitudes are higher than the panel minimum Z. This way, we will create a new raster with zero values when the ceilings allow visibility, and high values when the altitudes or the forms of ceilings block it. Later, we sum this raster with the GroundDEM (the raster containing the Z values of floors) using the “Plus” tool, creating a modified new raster to perform the viewshed analyses of GUs located in this particular panel.
The “Viewshed 2” tool, unlike other similar tools, does not have a Z factor parameter, so, to ensure the accuracy of the output visibility
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Fig. 3. A conceptual map created using Model Builder in ArcGIS®, showing the steps of the method followed to measure the area of the viewshed of a certain GU (Atr.F’.I.01).
raster, we must introduce the Z value of each GU. The tool also allows the introduction of other variables, and these will be used. Nonetheless, the results must be checked in the cave, modifying introduced variables if necessary.
Redondo, 2018), including rock art studies (e.g. Acevedo et al., 2019), these techniques remain unpopular in approaches focused on Palaeolithic cave art -both in Europe and other zones worldwide-, although some references are known (Ortega, 2014).
In the case of Atxurra, as explained above, the enormous amount of
IAC elements found under rock art panels have allowed us to determine prehistoric illumination systems (Garate et al., 2020). In particular, three different illumination techniques have been identified in Atxurra: torches (estimated by scattered charcoal remains found in most sectors), hearths (found in Sector J) and a portable sandstone lamp (found in Sector D). Particularly, the primary position of Sector J hearths, deep in the cave and under rock art motifs, indicates their function for lighting. With different multi-analytical approaches and experimentation, we have estimated each illumination technique's maximum radius of action (Medina-Alcaide, 2020), and these have been considered to introduce these numerical values in our analysis. Although we have avoided introducing more variables in the analyses (e.g. reflectance, luminance, etc.), these are possible additions to make in the future. We have also introduced mean stature during the Late Upper Palaeolithic (Holt, 2003) to simulate as closely as possible the scenario in which the rock art of ensemble of Atxurra was created -and preferably observed-, in the Upper Magdalenian. This stature −1.60 m-has only been taken as a reference to perform our test, and it must be regarded as provisional, since the anthropological record in these chronologies is limited and it only takes into account adults -when we know that children or people of small stature also entered caves (Bégouën et al., 2009)- and in an upright position (when they could be sitting, lying down, etc.). In any case, we believe that this reference serves to establish valid criteria when estimating potential viewsheds, as proven by the recent comparisons with ancient DNA (Cox et al., 2019). This value must be added to establish the viewshed from a potential observer's eye height. Otherwise, if we do not add this value, the viewshed is considerably less than the real one.
Some of the main limitations that have hindered the use of these tools in caves are the complexity and enclosed three-dimensional nature of underground environments. However, even if they are designed to be used in the open air, current GIS technology allows some processes to be applied to solve these problems (Fig. 5).
The first limitation that we have identified is due to the ceilings: caves are enclosed environments, so, besides the floors, irregular morphologies arising from the passage wall and ceiling (e.g. roof pendants, notches, speleothem formations, etc.) can affect the visibility (Fig. 5A). These (ceilings) can be taken into account following the first steps of the proposed method, i.e., the modification of the floor raster based on the ceilings raster, modified using the minimal Z of the analysed panel (Fig. 3).
The second main problem is also related to the three-dimensionality complexity of caves. There can be two (or more) floor-levels or obstacles affecting visibility, in addition to the ceilings. In these cases, it is possible to create different floor or ceiling rasters (for example, one for each level or obstacle), and perform the analysis using the appropriate archive for each GU.
Another problem is due to the limited surface of the passages, and the “Viewshed 2” function programming. The tool does not take into account the “NON DATA” cells, so if there are two passages near to each other in the same Z, the software can count the two passages as visible although that may be impossible (because there is a wall between these two zones). This can be solved by sectoring the cave into different rasters (one for each passage, for example). The problem can also be solved by a bug that software tends to do, “increasing” exponentially the cell value when it is in a position where null values coincide with those of ceilings or floors. This only happens in the outermost pixels, so with the level of accuracy that we are working with (25 cm2), a GU is unlikely to be located in the outermost cell.
Finally, once all the viewsheds had been obtained -one for each GU of the cave- (Fig. 4), we have measured the area (in square metres) of each obtained raster. This has allowed us to make comparisons with precise values (Supplementary Data. S1).
Finally, some authors have claimed that GIS are hardly applicable to a large number of sites because of their complexity, or because of the time and funding required to create certain useable archives (e.g. Ochoa, 2017). We believe that both problems can be avoided by employing cutting edge technologies like photogrammetry, which has been increasingly used in rock art studies in recent years (e.g. Azéma
