# Comprehensive workflow for erosion monitoring of coastal archaeological sites by means of digital photogrammetry: An Iberian case study

Juan Mencía, María-Eugenia Polo, Ángel Manuel Felicísimo, Marie-Yvane Daire, Alejandro Güimil-Fariña, Patricia Mañana-Borrazás, Xosé Ignacio Vilaseco Vázquez, Elías López-Romero

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## ► To cite this version:

Juan Mencía, María-Eugenia Polo, Ángel Manuel Felicísimo, Marie-Yvane Daire, Alejandro Güimil-Fariña, et al.. Comprehensive workflow for erosion monitoring of coastal archaeological sites by means of digital photogrammetry: An Iberian case study. Digital Applications in Archaeology and Cultural Heritage, 2024, pp.e00373. 10.1016/j.daach.2024.e00373. hal-04686949

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# Comprehensive workflow for erosion monitoring of coastal archaeological sites by means of digital photogrammetry: An Iberian case study

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Juan Mencíaª, María-Eugenia Poloᵇ, Ángel Manuel Felicísimoᵇ, Marie-Yvane Daireᶜ,
Alejandro Güimil-Fariñaᵈ, Patricia Mañana-Borrazásᵈ, Xosé Ignacio Vilaseco Vázquezᵉ,
Elías López-Romeroª,ᶜ

## ARTICLE INFO

**Keywords:**

Erosion monitoring

Coastal archaeology

Cultural heritage vulnerability

Climate change

Photogrammetry

Orientation analysis

## ABSTRACT

In keeping with the debate of the effects of climate change and human pressure on cultural heritage, research on archaeological sites that are threatened by erosion—and eventually subject to complete destruction—has increased in the last decade. Different solutions have been proposed at the national and international levels for the study and management of this cultural heritage sites across the globe. Since 2006, an international team of French and Spanish researchers has been working together in the research, monitoring and management of coastal archaeological sites in different Western European regions and in the French West Indies. As a result, several methods and approaches have been developed and implemented. Among those methods, 3D photogrammetric recordings of archaeological sites that are at risk. In this paper, we focus on the methodological aspects of photogrammetric erosion monitoring analysis, taking as an example one case study from NW Iberia: Guidoiro Areoso megalithic monument M3 (Galicia, Spain). Four photogrammetric models were to account for short (6-month to 1-year intervals) and long (10-year intervals) erosion monitoring. The results show the complexity of the local erosion/accretion conditions. The workflow uses free and/or low-cost software and is easy to extrapolate to different sites, regions and archaeological and geographical contexts.

## 1. Introduction

The vulnerability of cultural heritage is becoming the focus of increasing attention, particularly in areas such as the European and American Atlantic regions, where the combined forces of sea-level rise, coastal environment dynamics and human activity significantly alter the coastline (e.g., Cassar 2016; Sesana et al., 2018; Dawson et al., 2017). The need for a better understanding of this heritage, its setting and its vulnerability is urgent (e.g. Erlandson 2008; Fitzpatrick 2010). In Europe, Scottish archaeologists were among the first to warn of the threat to this heritage (Ashmore 1994) and, in 1997, English Heritage initiated the Rapid Coastal Zone Assessment Surveys (RCZAS; English Heritage, 1997). In this context, the ALeRT project (Archéologie, Littoral

et Réchauffement Terrestre) was initiated in 2006 in Brittany, France, to address the vulnerability of coastal archaeological heritage. The project is based on the principle of 'preservation by record' and integrates a participatory research-action approach (Daire et al., 2012; López-Romero et al., 2013), an approach that is common to other projects addressing this issue worldwide (e.g. Dawson et al., 2020; Miller and Murray 2018; Wragg et al., 2017). Since 2009, the project's theoretical framework and tools have been extended and applied to other Western European Atlantic regions, including Pays de la Loire and Normandy in France and Galicia in NW Spain; more recently, since 2017, the Guadeloupe archipelago in the French West Indies has also been the object of specific research (Motte et al., 2022). Digital photogrammetric recording of selected archaeological sites was initiated in

<footnote>ª Instituto de Arqueología de Merida (IAM), CSIC-Junta de Extremadura, Consejo Superior de Investigaciones Científicas, Spain</footnote>

<footnote>ᵇ Departamento de Expresión Gráfica, Centro Universitario de Mérida (Universidad de Extremadura), Spain</footnote>

<footnote>ᶜ UMR 6566 CreAAH - Centre de Recherche en Archéologie, Archéosciences, Histoire, Rennes, France</footnote>

<footnote>ᵈ DIMENSO, Collaborator of Institute of Heritage Sciences (Incipit, CSIC), Santiago de Compostela, Spain</footnote>

<footnote>ᵉ Archaeologist. Xunta de Galicia, Spain</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: juanmencia97@gmail.com (J. Mencía), mepolo@unex.es (M.-E. Polo), amfeli@unex.es (Á.M. Felicísimo), marie-yvane.daire@univ-rennes.fr (M.-Y. Daire), guimil@dimenso.es (A. Güimil-Fariña), patricia@dimenso.es (P. Mañana-Borrazás), jose.ignacio.vilaseco.vazquez@xunta.gal (X.I. Vilaseco Vázquez), elias.lopez-romero@iam.csic.es (E. López-Romero).</footnote>
2013, with case studies from Brittany, Galicia and the Isles of Scilly (López-Romero et al. 2014, 2016). The aim of the detailed three-dimensional recording of those sites is twofold: first, to produce a digital copy of the sites and to allow for the scientific analysis of some aspects (e.g., architecture) even in the event of severe damage or destruction; second, to enable periodic monitoring of erosion processes in and around the sites that would help us understand changes at the microspatial scale while contributing to the decision-making process involving the different stakeholders and managers. For this second objective, several fieldwork campaigns were planned with a 6-month interval, beginning in September 2013 and ending in September 2014. More recently, in 2022 and 2023, new photogrammetric models were obtained for the archaeological sites under study. While several projects are now using photogrammetry to record or monitor archaeological excavations (e.g. Ostrowski et al., 2024; González-Quinones et al., 2022), its uses in heritage vulnerability assessment and as a tool for decision-making needs to be further discussed and developed. In this, the need for replicable workflows can play a major role, and the case study in this paper is one that epitomises the urgent situation many archaeological sites are facing.

Located in the northwest of the Iberian Peninsula, Galicia is the region with the longest coastline in Spain; its western coast is characterised by the presence of several rias. A number of islands and islets can be found within or at the mouth of such rias, where an increased number of archaeological sites from different periods are being put to light. Despite its long coastal perimeter and the historic importance of the sea, the development of specific coastal prehistory research programmes is relatively rare in Galicia. In the 1980s and 1990s, there was an increase in research and publications on coastal prehistory with, for example, debates on the macrolithic industries of the Mesolithic; Neolithic and Bronze Age rock art; the analysis of Iron Age shell-middens; and the study of sea-level fluctuations (e.g., Aira Rodríguez et al., 1992; Martínez Cortizas and Costa Casais 1997). Despite these advances, at the beginning of the 2000s, some scholars drew attention to the fact that studies on the use of the sea in the prehistory and antiquity of Galicia were still not properly developed (Vázquez Varela & Rodríguez López, 1999–2000). Since 2010, research on the coastal archaeology of the Western Rias by our team and, more recently, by colleagues from other Galician universities and research centres (e.g., Fernández et al., 2022a) has fostered new perspectives on these areas. Recovering scientific information from these archaeological contexts is crucial, as most of the region lacks sedimentary archives suitable for the preservation of organic materials that can be found in coastal environments. Due to the increased threats to the archaeology of the area, questions about erosion and the scientific importance of the sites must be addressed (López-Romero et al., 2023). One very special location within these Western Rias of Galicia is the islet of Guidoiro Areoso (municipality of A Illa de Arousa), which is approximately 1400 m to the West as the crow flies, occupying an almost central position in the ria de Arousa. Its surface area is very small (c. 8 ha), approximately 600 m from north to south for less than 200 m at its widest. Its maximum height a.s.l. is 9 m, and it is subject to wind and marine weathering. The northern half of the islet is characterised by an active dune system, while its southern half is dominated by numerous granite outcrops and a vegetated and apparently inactive dune. Using as an example one megalithic monument in the islet (Fig. 1), in this paper, we present—in the form of a comprehensive workflow—our methodology for short (6 months–1 year intervals) and long (10-year interval) erosion monitoring of the sites.

## 2. Materials and methods

Five Neolithic megalithic chambers and several Bronze Age funerary cists have been recorded here since the 1980s (Fig. 2) (Rey García and Vilaseco Vázquez, 2012; López-Romero et al., 2015). Among those, megalithic monuments M1 and M2 were excavated by J.M. Rey García, monument M5 was completely destroyed in 2013 by coastal erosion and

weathering, and monument M4 was excavated in the summer of 2017 (Mañana-Borrazás et al., 2020).

Monument M3 is the only remaining Neolithic chamber that has not been destroyed or excavated; it sits on the southwestern end of the islet, is embedded in the dune and is very close to the high water mark. Monument M3 settled next to monument M2, but it was completely covered by the sand dune when the latter was excavated, not being discovered until 2011. The upper section of several granitic orthostats is visible today, suggesting that archaeological layers can still be preserved under the sand (Fig. 3). Because of its scientific interest and vulnerability, monument M3 has been the object of specific monitoring since 2013. The protocols used for this purpose are hereafter proposed as comprehensive workflows for monitoring the erosion at other archaeological sites.

### 2.1. Desk-based planning and fieldwork

Following previous visits to the islet and in the frame of the eSCOPES European Commission Marie Curie project n°328753 (FP7-PEOPLE-2012-IEF, Evolving spaces: coastal landscapes of the Neolithic in the European Land's Ends, PI E. López-Romero, Durham University, 2013–2015), erosion monitoring by means of digital photogrammetry was planned on the site. The idea was to obtain precise geo-referenced 3D models of monument M3 at six-month intervals for the duration of the project. We chose to use Agisoft Metashape software (Agisoft 2023), which implements the structure from motion (SfM) algorithm to estimate the 3D structure of a scene from a set of 2D images. This procedure reconstructs camera pose and scene geometry from overlapping photographs captured by a camera moving around the scene (e.g., Jones and Church 2020). Two reflex cameras (a Nikon D300 instrument equipped with a GPS receiver and a Canon EOS 700D) were used for photographic recording in the field. After careful consideration of the advantages and disadvantages of the image format, the JPG format was chosen instead of the RAW format as a compromise between the quality of the photoshoot and the savings of time and resources. While RAW images do not suffer from loss of image detail, they contain all the sensor noise.<fnref n="1" /> JPG images are lighter and faster to process, an important advantage for us considering that the number of photographs for a single site in one fieldwork campaign could exceed 800 (as was the case for the Le Lomer and Coalen case studies in Brittany, France; López-Romero et al. 2014). Images were taken at the floor level (perpendicular and oblique to the orthostats and the surrounding area) and with the camera mounted on a pole (perpendicular to the floor).

To provide accurate geo-referencing of the models, the planning of the photographic campaigns included detailed topographic records using reference points in the vicinity of each site with a Leica TCRP1203 total station and a differential global positioning system (DGPS, Leica GPS1200), combined with a series of control point measurements at the site. Fixed topographic reference stations were hence placed in significant locations on the islets (Fig. 4). The control point measurements were obtained through coded targets created in Agisoft and printed prior to each fieldwork campaign. The chosen reference frame was the European Terrestrial Reference System 1989 (ETRS89), which is the standard precise GNSS coordinate system throughout Europe endorsed by the INSPIRE data specification (D2.8.I.1 Data Specification on Coordinate Reference Systems; EU, 2007). The same protocol from desk-based planning to data capture was followed during three fieldwork campaigns: 25th September 2013, 10th March 2014 and 22nd September 2014. The resulting 3D models account for the short-term (6-month to 1-year intervals) evolution of the site.

Precise georeferencing is extremely relevant to analyse changes at the centimetric level. However, in the domain of island and coastal survey and monitoring of archaeological sites at risk of destruction,

<footnote n="1">¹ https://www.agisoft.com/forum/index.php?topic=963.0.</footnote>
<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Map of the western rias of Galicia showing the location of Guidoiro Areoso (basemap from Digital Terrain Model MDT25 2009-2015 by IGN: https://pnoa.ign.es/pnoa-lidar/modelo-digital-del-terreno).</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Islet of Guidoiro Areoso with indications of some of the main prehistoric sites discovered. M1 to M5, Neolithic megalithic monuments; C1 and C2, Bronze Age cists (basemap from PNOA2010 imagery and LiDAR2011 data: https://pnoa.ign.es/web/portal/inicio).</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Fig. 3. Guidoiro Areoso monument M3.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 4. The topographic reference station was at the highest point of the islet.</figcaption></figure>

there are circumstances where it is not always possible to undertake
such precise topographic recording. Site accessibility, rapid assessment
campaigns or the lack of expertise of the team conducting the survey (e.
g. in citizen science projects) may limit the capacity to develop a full
recording procedure. This was the case on 27 April 2023, when a visit to
a different islet in Ria de Arousa by two of the authors (X.I. Vilaseco and
E. López-Romero) allowed for an unplanned visit to Guidoiro Areoso and
for a new photographic recording of monument M3. In this instance, the
recording was performed with a compact Canon PowerShot G15 camera
and without topographic measurements on coded targets. The geore-
ferencing of the resulting model was hence performed differently, as
described below (2.2.3. Georeferencing). Compared to the previous
models, the 2023 3D model accounted for the long-term (10-year in-
terval) evolution of the site.<fnref n="2" />

## 2.2. Photogrammetric modelling and outputs

Agisoft Metashape Professional v. 1.8.4 was used for the photo-
grammetric modelling. The following workflow was used:

2.2.1. Photo addition and alignment

All available photographs for each fieldwork campaign were added to Agisoft Metashape Professional. After checking that the camera positions obtained with the Nikon D300 instrument equipped with a GPS receiver did not improve the alignment or the subsequent modelling procedures, the coordinate reference for each camera was removed. All the images hence lacked any reference, and their relative position was automatically calculated by the software during the alignment process. Before the photo alignment, image quality was also checked using the Estimate Image Quality tool in Metashape. Images with quality values less than 0.5 units were disabled and excluded from photogrammetric processing; the value of the parameter was calculated based on the sharpness level of the most focused part of the picture.<fnref n="3" /> While unnecessary for our current case-study due to its limited surface, ensuring comprehensive spatial coverage and adequate image overlap becomes imperative for larger-scale projects. In such cases, acquiring supplementary images and conducting realignment procedures are recommended practices (Ostrowski et al., 2024).

2.2.2. Sparse cloud and mesh

The sparse clouds resulting from the alignment process were cleaned using the Gradual Selection tool in Metashape; all points featuring fewer than 3 images were deleted. After this process, all the cameras were optimised. The mesh was then created from the depth maps, intermediate products of the processing based on the common tie points camera pairs. Small, disconnected parts of the resulting mesh were removed using the Gradual Selection tool in Agisoft (connected component size >99%). Similarly, holes in the mesh surface were filled in and smoothed using the Close Holes and Smooth options in the Tools menu. Finally, to prepare the mesh for the following steps, a texture was created from photographs with visible coded targets.

The key parameters defining the models and the Metashape pro-
cessing are summarized in Table 1.

Decimation of the 3D models was deemed unnecessary as the point
clouds were manageable and sufficient computing power was available.
However, there may be instances where decimation is required to model
larger extensions (Hamarneh and Leutgeb, 2023).

2.2.3. Georeferencing

For the 2013 and 2014 campaigns, markers were created for each of
the coded targets visible in the texturised meshes. The coordinate ref-
erences in the ETRS89 29 N system resulting from the field measure-
ments for each model were then imported to Metashape and assigned to
the corresponding markers. After updating the transform, and to
improve the visual quality of the final outputs, new textures were built
from photographs without coded targets.

For the 2023 campaign, which lacked coded targets, georeferencing
was performed using the coordinates extracted from homologous points
from the March 2014 georeferenced model. The process of finding the
homologous points was a manual, supervised task that consisted of the
visual search of fixed points (e.g., quartz or feldspar crystals, stone
edges) in the two sets. A final total of 6 points were kept and used for
georeferencing the 2023 model.

2.2.4. Outputs

Two main outputs stem from the previous steps: orthomosaics and
digital elevation models (DEMs). The first were created following the
Build Orthomosaic menu in Agisoft. The pixel size was set at 1 mm for all
the models, and the ETRS89 29 N reference system was used. The
resulting output was improved by checking for fuzzy areas, excluding
blurred images and assigning sharper photographs among those avail-
able for such areas. Finally, the orthomosaics were exported as un-
compressed TIFF images.

<footnote n="2">² The long-term changes operated in the site since its construction in the Neolithic have been substantial; here, we use "short-term" and "long-term" only as a methodological convention to refer to the time-span of our work.</footnote>

<footnote n="3">³ https://www.agisoft.com/pdf/metashape-pro_2.0_en.pdf.</footnote>
<caption>**Table 1**</caption>

Main parameters of the Guidoiro Areoso M3 3D models and of the Metashape processing. These data refer to the original, uncut, photogrammetric models acquired in Metashape before undergoing processing and model fitting in QGIS. The models are available as supplementary material to this article (3D PDF files).

<table><thead><tr><th>Model name</th><th>Total images uploaded</th><th>Selected accuracy for alignment</th><th>Aligned images</th><th>Quality and face level for the model</th><th>Source data</th><th>Depth filtering</th><th>Resulting faces</th><th>Resulting vertices</th></tr></thead><tbody><tr><td>2013_09</td><td>150</td><td>High</td><td>148</td><td>High</td><td>Depth maps</td><td>Aggressive</td><td>4,353,186</td><td>2,177,659</td></tr><tr><td>2014_03</td><td>122</td><td>High</td><td>122</td><td>High</td><td>Depth maps</td><td>Aggressive</td><td>2,115,773</td><td>1,059,165</td></tr><tr><td>2014_09</td><td>198</td><td>High</td><td>197</td><td>High</td><td>Depth maps</td><td>Aggressive</td><td>3,917,839</td><td>1,959,847</td></tr><tr><td>2023_04</td><td>217</td><td>High</td><td>216</td><td>High</td><td>Depth maps</td><td>Aggressive</td><td>11,288,220</td><td>5,646,791</td></tr></tbody></table>

The DEMs were created from the mesh following the Build DEM menu in Agisoft. As previously described, the ETRS89 29 N reference system was used, and the model resolution was set at 1 mm.

While the photogrammetric workflow is highly automated in this software, and the literature aids non-expert users in creating 3D models (Jones and Church, 2020), in the case of exporting orthomosaics and DEMs, cartographic concepts such as 'coordinate reference system' (CRS) or spatial resolution must be properly understood.

## 2.3. Processing and model fitting

### 2.3.1. Raster clipping and identification of homologous points via QGIS

The orthomosaics were added to the QGIS as raster layers, and the coordinate reference system (CRS) was specified. A polygon layer with the same area of interest for the four rasters (25th September 2013, 10th March 2014, 22nd September 2014 and 27th April 2023) was created. The four rasters were clipped accordingly using the "Extract by Mask" tool in QGIS. To obtain the best match between the four models, a specific procedure for increasing the accuracy of the model fitting was

<figure><img src="image_9.png" /><figcaption>**Fig. 5.** Orthomosaics showing the homologous points identified for model fitting through orientation analysis (circular statistics). A) September 2013, B) March 2014, C) September 2014, D) April 2023. Only 12 out of the total of 25 points could be found for the April 2023 model due to changes in the site.</figcaption></figure>
used. All of the clipped orthomosaics were loaded in four different QGIS projects along with their corresponding DEMs to identify homologous points. This process was a manual, supervised task that consisted of the visual search of fixed points (e.g., quartz or feldspar crystals and stone edges) in all four images. A point vector layer was created for each raster. A total of 25 shared homologous points were identified for the three first rasters, and 12 were identified for the raster corresponding to 2023 (due to long-term changes in the archaeological site) (Fig. 5). The X and Y coordinates were added to each of the vector layer attribute tables using the built-in "Add X/Y fields to layer" tool in QGIS. The Z coordinate was added to the vector layer attribute tables with the "Sample Raster Values" tool in QGIS, using the point vector layer as the input and the corresponding MDE as a reference.

### 2.3.2. Displacement vectors

At this stage, we have the X, Y and Z coordinates of the fixed points located in the four datasets, taking into account that the 2014-03 model is considered a reference; this is because this is the time of year when the area is most covered with sand, with the least visible ground surface and, therefore, this model provides the least number of fixed points available for measurements.

Next, the goal is to check if these georeferenced models have undergone any horizontal displacement that prevents a correct fit between models.

For this purpose, we established three sets of horizontal vectors with initial nodes at the X and Y coordinates of the stable points of the 2013-09, 2014-09 and 2023-04 models and, as final nodes, the same points in the 2014-03 model, which is the reference model.

As a vector has a modulus and azimuth, it is possible to analyse not only the displacement in distance but also the displacement in orientation. For the analysis in orientation, it is necessary to apply circular statistics, which address the treatment of angular data (which are cyclical) represented on a circle of unit radius, as opposed to linear data, which are presented on the real line (Mardia and Jupp, 2000). The authors have not found references on the application of circular statistics related to adjusting the referencing of 3D models for coastal erosion, but this kind of analysis is already used in the study of stone pavement formation in deserts (Dietze and Kleber, 2012) or in modelling the seasonality of extreme coastal water levels (Veatch and Villarini, 2020).

The main circular statistics used are the mean direction and the circular standard deviation, which are used as measures of central tendency and dispersion, respectively, to study the distribution of the azimuths of the displacement vectors (Fisher 1995; Polo and Felicisimo, 2010). These distributions, in an ideal case, can be uniform, where all directions from 0° to 360° are equally likely. However, there are data distributions that are highly concentrated around a preferred direction. In this case, the reason for this concentration has to be determined. Circular statistics were performed with the software Oriana,<fnref n="4" /> which is designed to work with circular data (e.g., angles and directions) that require different treatments than linear data (Fig. 6). Finally, the Z-coordinate differences were calculated and analysed using a spreadsheet.

### 2.3.3. Model fitting procedure

The corrected coordinates with the mean model displacement observed in X, Y and Z were subsequently applied in Metashape to the original markers used for georeferencing. Meshes were georeferenced again with these corrected coordinates. This did not apply to the 2014-03 model, the model used as a reference, which remained unchanged. New orthomosaics and DEMs for each of the corrected models were created and exported. The rasters were clipped to match the same area of interest as mentioned in Section 2.3.1.

## 2.4. Model analysis

Only once these previous steps were completed could we confidently perform spatial analysis and comparisons of the four DEMs.

### 2.4.1. Masks

To improve the analysis and visualisation of the differences in the models obtained, two types of masks were created. First, all the visible orthostats were masked and excluded from the analysis because they constitute fixed elements with a given height above the ground. A vector polygon layer was then created for the orthostats in each model; this included a 0.005 m (5 mm) buffer around each of the polygons to prevent any deformation in the model at the orthostat level from interfering with the floor analysis.

Second, differential dune vegetation, mainly grasses and creepers, was visible in the models in the form of poorly modelled artificial heaps. Even though this type of vegetation plays a positive role against erosion (i.e., contributing to dune sand retention), it had to be excluded from the analysis; for this purpose, a vector polygon layer mask was created in each model.

These masking procedures mean that the resulting values for Z differences between the models are valid for a given percentage of the total surface area of the DEMs (see Calculation and Results).

### 2.4.2. Z difference: absolute and reclassified values

The DEMs were subsequently compared in pairs using the "Raster Calculator" function in QGIS. The formula used was "raster DEM B" - "raster DEM A", where DEM A was the raster corresponding to the most recent fieldwork campaign (e.g., "M3_2013_09" - "M3_2014_03" for the difference between the September 2013 and March 2014 models of monument M3 in Guidoiro Areoso). The result is a raster with negative values for those areas that have been subject to erosion (i.e., sediment loss, stone displacement) and with positive values for those areas subject to accretion (i.e., sediment deposition, stone displacement). Values equal to zero correspond to pixels that have not been subject to change.

Subsequently, the orthostats and vegetation masks (see 2.4.1. above) are applied to the resulting raster data using the "Clip raster by map layer" tool in QGIS.

Finally, to optimise the results, the raster values were reclassified into three categories: "-1" (erosion; values ranging from -9999 m to -0.01 m), "0" (unchanged; values ranging from -0.01 m to 0.01 m) and "1" (accretion; values ranging from 0.01 m to 9999 m).

# 3. Calculation and results: erosion monitoring of the Guidoiro Areoso M3 megalithic monument

## 3.1. Model fitting calculation

For calculation of the model fit, as explained above, three sets of horizontal vectors were generated with initial nodes at the X and Y coordinates of the stable points of the 2013-09, 2014-09 and 2023-04 models, respectively, and as final nodes, the same points were used in the 2014-03 model. All vectors were moved to a common origin without changing azimuth or displacement, allowing us to visualise the distribution of the vectors (see Fig. 6). The statistical analysis of both the azimuths and displacements are shown in Table 2.

Considering the azimuth analysis, the distributions 2013_09-2014_03 and 2023_04-2014_03 exhibit similar angular distributions with preferred directions of approximately 35.372° and 215.236°, respectively, and low circular standard deviations. The distribution 2014_09-2014_03 shows an unreliable preferred direction due to the high circular deviation and the dispersion of the angular values. These preferred directions could show a bias problem if these displacements were significant. Since the displacements (moduli of the vectors) have small mean values (7 mm, 2 mm and 16 mm, respectively), the displacements in X, Y and Z were corrected according to these

<footnote n="4">⁴ https://www.kovcomp.co.uk/index.html.</footnote>
<figure><img src="image_10.png" /><figcaption>**Fig. 6.** Displacement vectors (software Oriana) by pairs: A) September 2013 to March 2014, B) September 2014 to March 2014, C) April 2023 to March 2014. The March 2014 model appears last, as it is the reference (destination) model for this analysis.</figcaption></figure>

**Table 2**

Statistical analysis of both azimuths and displacements. The analysis shows the displacement of each of the seasonal models (2013_09, 2014_09, and 2023_04) in relation to the reference model (2014_03).

<table><thead><tr><th></th><th>2013_09-2014_03</th><th>2014_09-2014_03</th><th>2023_04-2014_03</th></tr></thead><tbody><tr><td>Mean azimuth</td><td>35.372°</td><td>8.713°</td><td>215.236°</td></tr><tr><td>Circular Standard Deviation</td><td>8.222°</td><td>100.451°</td><td>5.12°</td></tr><tr><td>Mean displacement</td><td>-0.007 m</td><td>0.002 m</td><td>0.016 m</td></tr><tr><td>Standard deviation of displacement</td><td>0.005 m</td><td>0.001 m</td><td>0.003 m</td></tr><tr><td>Mean difference in Z</td><td>-0.007 m</td><td>0.006 m</td><td>0.001 m</td></tr><tr><td>Standard deviation of difference in Z</td><td>0.005 m</td><td>0.003 m</td><td>0.001 m</td></tr><tr><td>Number of values</td><td>25</td><td>25</td><td>12</td></tr></tbody></table>

values. In any case, performing this type of angular analysis when replicating the proposed workflow on another dataset is recommended to rule out any bias issues in the orientation of the vectors.

As described in Section 2.4, after correction, the analysis and comparison of the four DEMs were performed via QGIS. The results allow us to assess the evolution of the site at different time intervals with high spatial resolution.

## 3.2. Short-term evolution of the site: 6-month to one-year intervals

The DEMs were analysed by pairing following a chronological sequence. For the 6-month intervals, this process was performed for the September 2013 to March 2014 and for the March 2014 to September 2014 models. For the one-year interval: September 2013 to September 2014. The corresponding vegetation and orthostat masks were summed for each pair of DEMs; the valid analytic surface could thus be calculated (Fig. 7).

As a result, three raster files were obtained that account for changes in the site, expressed in numeric (Z difference) and classified (erosion, unchanged, accretion) values.

From September 2013 to March 2014, an episode of sand deposition covered most of the site (Fig. 8). The analysis thus revealed a predominance of positive values (27.566 m², 98.65% of the valid analytic surface for these two models), with very few areas having suffered from loss (0.045 m², 0.16%). These areas mostly correspond to loose stones visible on the surface of the September 2013 model that were displaced by March 2014. The analysis also revealed that a small surface area (0.331 m², 1.18%) remained unchanged.

From March 2014 to September 2014, the sand retreated across virtually the whole valid surface for the analysis (25.454 m², 97.37%;

Fig. 9). Small stone displacements on the surface are again noticeable and are represented by positive values within the megalithic chamber and close to the orthostats on the northeastern side of the area of interest (0.086 m², 0.32%). Finally, 2.29% (0.6 m²) of the surface area remained unchanged. These last areas correspond to two types of features: first, the tips of small stones—mostly visible in the centre of the area of interest—not initially fully covered by the sand deposition episode of the winter of 2013/2014; second, sand retained in the northern corner of the area of interest as a result of the microtopography of the site (higher elevation and farther from the high-water mark) and of the presence of grass.

The one-year evolution of the site is particularly interesting. From September 2013 to September 2014, the evolution of the floor level and the complexity of the erosion/accretion processes became evident (Fig. 10). Positive values (8.154 m², 33.18% of the valid analytic surface) account for a small increase in sand deposition, especially around the orthostats, of up to c. +8 cm and for the presence of a few stones now appearing in different areas as a result of stone displacement but also, and more importantly, of sediment loss at the floor level. This erosion process affects 26.67% (6.556 m²) of the surface and includes the erosion of the substrate and the displacement or disappearance of several stones that were visible in the September 2013 model. Some of these stones were of considerable size (c. 40 × 30 cm), such as those in the eastern corner of the area of interest; their weight can be estimated between c. 23 kg and 45 kg, considering their visible dimensions and the mass of a cubic metre of granite (c. 2750 kg/m³). Finally, 40.13% (9.864 m²) of the surface remained mostly unchanged; this corresponds to several stones still embedded in the substrate and to areas of this substrate that did not suffer from significant loss.

## 3.3. Long-term evolution of the site: 10-year interval

Weather conditions prevented us from obtaining a record of the site in September/October 2023, which would have provided an exact match to the first fieldwork campaign in September 2013. Nonetheless, the April 2023 model still constitutes a very good reference both for the long-term evolution of the site and for the methodological scope of this paper.

The September 2013 to April 2023 DEMs were compared to analyse the overall evolution at the floor level and the evolution of the seasonal (winter/spring) sand deposition episodes. The calculation procedure was the same as that for the 6-month to one-year intervals, and the orthostats and vegetation masks were summed for the pair of DEMs.

The analysis showed that even though the seasonal sand deposition has not completed its cycle (the northern half of the site was still covered with sand in April), the loss at the exposed floor level was significant (55.71% of the 24.07 m² valid analytic surface for this pair; Fig. 11). The
<figure><img src="image_11.png" /><figcaption>Fig. 7. Examples of vegetation and orthostat masks and valid analytic surfaces; September 2013 and March 2014.</figcaption></figure>

<figure><img src="image_12.png" /><figcaption>Fig. 8. Guidoiro Areoso M3 site evolution, September 2013 to March 2014. Absolute and reclassified values.</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>Fig. 9. Guidoiro Areoso M3 site evolution, March 2014 to September 2014. Absolute and reclassified values.</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>Fig. 10. Guidoiro Areoso M3 site evolution, September 2013 to September 2014. Absolute and reclassified values.</figcaption></figure>

exposed southeastern area shows several stone displacements and an overall floor height loss during this 10-year interval. Excluding the height represented in the analysis by the displaced stones, this loss at the floor level ranges between c. 2–9 cm, which represents a mean loss between c. 0.2 and 0.9 cm per year. While this could result in a relatively slow erosion rate, it is important to note that this part of the islet is less exposed to weathering than others, especially the northern flanks where monument M4 and monument M5—the one destroyed in 2013—as well as the Bronze Age cists stood. Additionally, despite the seasonal sand deposition episodes, this analysis showed that the erosion was constant and irreversible. From a geomorphological point of view, there has also been an increased deficit in the whole sedimentary system (Blanco-Chao et al., 2020); this deficit affects the islet and has an incidence in the archaeological sites it houses. Nonetheless, it is interesting to note that some stones in the southern area that were present in the 2013 model are still preserved in 2023, showing that the sediments are still sound in some areas and that the site's integrity is not immediately threatened. The long-term analysis also showed that the orthostats have not suffered from any horizontal displacement (e.g., leaning) in the last 10 years,

which means that they are still embedded in the sediments at a convenient depth and that, as of April 2023, they are structurally sound.

## 4. Discussion

Photogrammetry is an efficient, easy-to-use tool for recording and analysing the issue of erosion that is becoming popular (Howland et al., 2018; Fernández et al., 2022b; Fonseca Moro and Pérez Pavón 2022); however, our proposal presents a comprehensive workflow considering the necessity of generating high-quality models to study erosion processes. These processes typically occur at the scale of centimetres or millimetres, making it essential to identify, consider, and minimize sources of error at each step of the protocol, (detailed 3D recording, photo addition and alignment, sparse cloud and mesh, georeferencing, etc.).

While precise geopositioning constitutes an important part of the workflow, we have shown that it is still possible to accurately georeference and fit models obtained from photographs lacking reference targets in the field; this allows for rapid data surveys even in the absence
<figure><img src="image_15.png" /><figcaption>Fig. 11. Guidoiro Areoso M3 site evolution, September 2013 to April 2023. Absolute and reclassified values.</figcaption></figure>

of specialised topographic equipment, something that can occur in the event of assessment field campaigns, of access to specific locations (remote, steep ...) and of surveys made by members of the community in the context of public science programmes (e.g., Daire et al., 2012). The integration of such models in the analysis not only does not compromise the results at all but, we contend, constitutes a complement that strengthens the overall capacity to conduct photogrammetry monitoring despite different field data capture procedures, provided that the model used as a reference is consistent, as was the case here.

As a novelty, the use of circular statistics has been introduced to ensure whether all the georeferenced models considered have undergone any horizontal displacement that prevents a correct fit between them. Circular statistics deals with data that can be represented as points on the circumference of a unit circle. Here, we go further by considering these horizontal displacements as error vectors, with magnitudes (displacements in distance) and azimuths (displacements in orientation). If the statistical analysis of linear data is the usual approach in these kinds of adjustments, the application of circular statistics is crucial for detecting displacements in orientation.

While direct 3D analysis of the photogrammetric mesh can be performed (López-Romero et al., 2017; Fernández et al., 2022b), in this work we chose to focus on 2.5D analysis of the resulting DEMs; this allows for accurate, easy-to-read outputs that can be obtained through well-established and accessible GIS procedures (e.g., map algebra in open source software).

The analysis performed on the Guidoiro Areoso monument M3 is a representative example of this. The results can be read in terms of short- and long-term erosion processes, and the different outputs can be used as tools for spatial, quantitative and qualitative analysis. We observed different trends in sand deposition, stone displacement and sediment loss at the floor level, which also confirmed that the orthostats, a structural part of the site, have not been affected by any displacement. All of these factors have allowed us to propose an interpretation of how the site has evolved. It is important to note that seasonal episodes of sand deposition can be misleading. The observed increase in such deposits in some periods of the year could at first sight be considered indicative of positive behaviour in the environmental context of the site, which is in the direction of a favourable preservation scenario. However, as the sand retreats seasonally, the floor level—composed of consolidated dune sand and archaeological layers—is irreversibly eroded; the 10-year evolution of the site is quite explicit about this, showing that the site suffers from active erosion. Although the situation at this particular site

is not critical, changes in erosion rates, seasonal sand deposition and the occurrence of extreme weather events cannot guarantee integrity in the short to medium term.

## 5. Conclusions

Considering the whole process and results, how appropriate is the methodology for our initial objectives (erosion monitoring analysis, rapid assessments, etc.)? We believe that the procedures presented here address the scientific and methodological needs we had when we began working in these coastal areas and, specifically, when we began considering the application of erosion monitoring procedures back in 2013. First, a detailed three-dimensional recording of the site was obtained, generating complementary information in the form of orthomosaics and digital elevation models. Second, a comprehensive and extrapolable workflow for erosion monitoring has been proposed and applied to the specific case of the Guidoiro Areoso megalithic monument M3. Finally, short (6-month to 1-year intervals) and long (10-year intervals) erosion monitoring were analysed. Future work campaigns could be added to the study of coastal erosion at this site. The work has also highlighted that there are protocols that must be more thoroughly addressed (e.g., greater attention in the field recording, avoiding footprints, algae deposits and other unwanted elements to be visible in the photographs).

This photogrammetry erosion monitoring workflow constitutes but a step in our wider approach to coastal archaeological sites at risk (Daire et al., 2012; López-Romero et al., 2013). However, this approach is a key element in the overall assessment of the sites and includes a regular archaeological survey of the coastal band and the intertidal area, a vulnerability assessment via a dedicated form (Vulnerability Evaluation Form-VEF), the engagement of the local community in the research process and dialogue with wider society and relevant stakeholders.

Even though it has been implemented for the analysis of coastal cultural heritage (i.e., archaeological sites), this workflow is also useful for the analysis of other contexts and sites that are essential for our understanding of past human societies, such as coastal palaeoenvironmental archives that are subject to the same erosion processes (e.g., Domínguez-Almansa et al., 2021).

## CRediT authorship contribution statement

Juan Mencía: Writing – original draft, Software, Methodology,
Investigation, Formal analysis, Data curation. **María-Eugenia Polo:** Writing – original draft, Visualization, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Ángel Manuel Felicísimo:** Writing – review & editing, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Conceptualization. **Marie-Yvane Daire:** Writing – review & editing, Validation, Supervision, Methodology, Investigation, Funding acquisition, Conceptualization. **Alejandro Güimil-Fariña:** Writing – review & editing, Methodology, Investigation, Data curation. **Patricia Mañana-Borrazás:** Writing – review & editing, Methodology, Investigation, Data curation. **Xosé Ignacio Vilaseco Vázquez:** Writing – review & editing, Methodology, Investigation, Data curation. **Elías López-Romero:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

## Declaration of competing interest

None.

## Acknowledgements

Funding: This work was supported by the European Commission Marie Curie Project n°328753 (FP7-PEOPLE-2012-IEF, eSCOPES - *Evolving spaces: coastal landscapes of the Neolithic in the European Land's Ends*, PI E. López-Romero, Durham University, UK, 2013–2015); the Cluster of Excellence LaScArBx – ANR-10-LABX-52 (Junior Chair project *The memory of place: meaning, evolution and resignification of space in the Neolithic of Western Europe*, PI E. López-Romero, Université de Bordeaux, France, 2017–2019); the Spanish National Research Council (PIE Incorporación CSIC, *Paisajes culturales de la prehistoria reciente*, PI E. López-Romero, IAM-CSIC, 2022-2023); and the AleRT programme (*Archéologie, Littoral et Réchauffement Terrestre* project, PIs M.-Y. Daire and E. López-Romero, 2006-pr).

Juan Mencía held a research contract funded by the “Programa Investigo” (*NextGenerationEU, Plan de Recuperación, Transformación y Resiliencia, Junta de Extremadura, 2022–2023*) during the completion of this work.

The authors also thank Chris Scarre (Durham University, UK), Sylvie Maleret (LabEx LaScArBx, France), the Institute of Heritage Sciences (Incipit, CSIC, Spain), the CReAAH and the AMARAI Association (France) for their support at different stages of the research process. Thanks are also due to the two anonymous reviewers for their detailed and helpful comments on an earlier draft of this paper.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.daach.2024.e00373.

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