The archeological record of La Roche-à-Pierrot (France) is central to debates on the Middle to Upper Paleolithic transition. To this day, it is the only site to have provided a relatively complete Neandertal skeleton associated with an industry identified as transitional, the Châtelperronian, which had been attributed until then to

The site of La Roche-à-Pierrot in Saint-Césaire (France) is central to one of the most keenly-debated topics in paleoanthropology and Paleolithic archeology: the disappearance of Neandertals and their replacement by

Because archeological phenomena have an intrinsic spatial component, the tools used to study geospatial data and information play a key role (

One way to study archeological sequences and deposit geometry relies on digital visualization systems to facilitate the creation, presentation, and exploration of stratigraphic relationships (

The present work proposes a new visual analytics tool and spatial statistics to explore archival archeological data. In the context of the La Roche-à-Pierrot excavations, selection of a georeferenced 3D web-based representation followed the rationale put forward by Galeazzi et al. (

The archeological site of La Roche-à-Pierrot is located in the town of Saint-Césaire, about ten kilometers east of the city of Saintes in Charente-Maritime, Southwestern France. It is located around 35 meters a.s.l., and 2–4 meters above the current floodplain of the Coran River (

Digital terrain model (left) and topographic map (right) of the La Roche-à-Pierrot archeological site with the location of the excavation grid and reference section of Lévêque’s excavation area, as well as the position of current fieldwork. Note the location of the reference section at the base of an Upper Turonian limestone cliff.

Reference section (left) and sequence (right) of the archeological stratigraphy of La Roche-à-Pierrot (after

The excavations at Saint-Césaire used a one-square-meter grid system and proceeded by 50 × 50 cm^{2} sub-squares and 5 or 10 cm spits (

Example of the cover and contents of the excavation notebooks filled out during Lévêque’s fieldwork (square H5) and example of the labels associated with the bags of non-piece plotted faunal remains (inset).

The starting point of the present project was the encoding in a spreadsheet of the provenience of all of the non-piece plotted fauna from the original excavations. In a second stage, we compared this information with that of the excavation notebooks, in order to confirm the congruence between the information noted on the fauna bag labels and the field observations written in the notebooks (

Process flowchart from data to interactive visualization.

Where two or more levels were identified in a single spit, only the uppermost level according to Lévêque’s archeostratigraphy (

Thanks to the detailed recording methods adopted by F. Lévêque at Saint-Césaire, we finally produced 4729 spreadsheet entries, each corresponding to a 50 × 50 × 5 cm spit. This covers a surface area of 205 sub-squares (51.25 m2) and a total thickness per sub-square varying from 5 cm (in C3 III and I3 II, close to the cliff) to 2.25 m (in D5 III, E5 III, and E5 IV), for an estimated total volume of 62.55 m3 of excavated sediments.

The first 3D visualization of the archeological stratigraphy of Saint-Césaire was produced using the Qgis2threejs plugin (

3D structure representation of the yellow and gray principal stratigraphic sequences of La Roche-à-Pierrot.

To produce effective visualizations and identify each of the 16 stratigraphic levels clearly, color ranges were chosen following the rules of graphic semiology (

Color scheme selected for the levels of Lévêque’s archeological stratigraphy, see

Spatial analysis can provide tools for a better understanding of where inconsistencies are located and we proposed to adapt local measurements of spatial association (

A matrix with line standardization: for a given spit, the weight given to each of its neighbors was divided by the sum of the weights of its neighbors. While easy to interpret, this standardization method implies competition between neighbors, since the fewer neighbors a spit has, the more weight each carries. Indices computed using this standardization method vary between 0 and 1.

A matrix with global standardization: the sum of all of the weights equals the number of spits. This standardization method averts edge effects since the calculation is not only based on the direct neighbors of each spit (whose number can vary from 0 to 26) but it also takes the whole of the entities into account.

Illustration of the construction of a contiguity matrix and of the two standardization methods used to produce spatial weight matrices applied to the computation of spatial analysis indices.

Based on the 3D matrices computed in an R script (

Methods used to define the similarity index (SI) and coherence index (CI). A: graphical representation using theoretical data; B: mathematical formulas.

The value of the coherence index provides insight into the alignment of the location of each spit with the stratigraphic level assigned to it. The similarity index (SI) takes into account only the first condition of the CI and informs on the homogeneity of the stratigraphic levels.

The main purpose of the present application is to give the researchers on the La Roche-à-Pierrot Collective Research Project greater autonomy to explore the site deposits within the three geographic dimensions and across the index values as calculated above. For example, this approach may provide information that could supplement field observations and/or collection-based assumptions of potential reworking. To this end, the interactive application was duplicated: one for indices calculated with line standardization (

First window of the visualization application with the 3D reconstruction of Lévêque’s archeological sequence (left) and the number of spits per stratigraphic level (right).

Windows 2 and 3 are designed to a similar model: they provide 3D visualizations of the considered index (SI in window 2 and CI in window 3) with available interactive selection of different dimension values (i.e. according to depth, sagittal and frontal bands of the grid system) on one hand (

Second window of the visualization application, part one (example of the similarity index [SI] computed with the line standardization method). Top: choice of dimension values; middle: 3D visualization of index values (left) and distribution charts of the spit numbers by index value and of the index values by depth for the selected spits (right); bottom: 3D visualization of stratigraphic levels (left) and distribution charts of the spit numbers by level and of the index values by level for the selected spits (right).

Second window of the visualization application, part two (example of the similarity index [SI] computed with the line standardization method). Top: choice of index values; middle: 3D visualization of index values (left) and distribution charts of the spit numbers by depth and of the depths by index value for the selected spits (right); bottom: 3D visualization of levels (left) and distribution charts of the spit numbers by level and of the index values by level for the selected spits (right).

This 3D visualization model and associated indices make it possible to highlight quickly the areas of the site with particular patterns.

Window of visualization of the coherence index. Top: overview of the indices of the whole site with every option selected; bottom left: selection of the representation of the coherence indices by spit based on specific depths, sagittal and frontal bands (red arrows); bottom right: same grid selection as on the bottom left, but with a different depth selection (red arrows).

To gain a better understanding of how the indices vary within the archeological site, charts were produced according to the three spatial dimensions (one chart per dimension;

Distribution of the similarity index values computed using the line (left) and global (right) standardization methods according to different dimensions (top: sagittal band; middle: frontal band; bottom: depth level).

Distribution of the coherence index values computed using the line (left) and global (right) standardization methods according to different dimensions (top: sagittal band; middle: frontal band; bottom: depth level).

As expected (cf. 2.3), we observe a correlation between the index values (SI and CI) and the average number of cells (spits) taken into account to calculate them, which is particularly visible at the edges of the site (

For line standardization, it is worth noting that the average of the similarity indices was lower than that of the coherence indices (0.56 and 0.73, respectively), which seems consistent insofar as the calculation methods allow a greater likelihood of one of the neighbors of the considered spit having a value of 1 when computing the neighborhood matrix of the CI than of the SI (

In the value distribution chart by sagittal band (from east to west), the indices appear to be very homogeneous and always quite close to the average for the deposit as a whole. Additionally, the edge effect is very prominent with line standardization.

As far as the distance from the cliff is concerned, a decrease in index values was identified starting from sagittal bands 5/6. Importantly, the slope break observed previously on the overall visualization of the deposits lies precisely in these bands (with Saint-Césaire 1 being located in band 4).

Regarding the depth chart, it is apparent that there is a drop in the indices from a depth of –1.6 m downwards, with a concentration of low values between –2.0 and –3.0 m for the similarity indices, and an additional substantial drop between –2.5 and –3.0 m for the coherence indices.

Geovisualization tools and 3D spatial statistics offer new analytical perspectives in providing useful information about the geometry of deposits and their coherence. In cases where inconsistencies are observed, the use of appropriate indices, such as the similarity and coherence indices, allows taphonomical inferences to be made and any bias potentially related to the topography, spatial heterogeneity of the deposits, excavation history, or primary data acquisition/recording to be discussed.

The two calculated indices, SI and CI, provide complementary elements for understanding the structure of the site. The similarity index informs strictly of the resemblance between each sub-square and its neighborhood, while the coherence index can test this resemblance with respect to a pre-established spatial organization (here, the archeological sequence). While interpretation of the SI is easy for high or very low values, it becomes more subtle for intermediate values, and the complementarity of the CI then takes on its full meaning. For instance, a sub-square with a rather low SI value may be located in a coherent position with regard to the archeological sequence, which will be revealed by a rather high CI value (

The neighborhood matrix standardization modes used here are also complementary. While line standardization gives more weight to observations located at the edge of the study area (therefore with a small number of neighbors), for global standardization, on the contrary, the observations located in the center of the study area, with a large number of neighbors, are subject to more external influences than the peripheral areas. In our case, this implies that line standardization produces high index values at the edges of the site and that the values become lower with global standardization. However, such differences in value do not imply an opposite interpretation, but rather a complementary one: with line standardization, high index values clearly indicate either a strong similarity or a strong coherence, which must be mitigated by the low values obtained with a global standardization.

Combination of the two indices and two modes of standardization therefore allows a more refined and moderate interpretation of site organization.

As outlined above, the method for constructing the neighborhood matrix (line

Influence of site topography on the average number of cells used to compute the index matrices (theoretical data).

In addition, the various excavation seasons have revealed the presence of limestone blocks in the lithosequence, which are likely to generate empty spaces (no spits). Around the edges of these voids, the number of spits taken into account decreases again, as does their average number, thereby acting on the calculation of the index values (

Influence of site topography and the presence of blocks on the average number of cells used to compute the index matrices (theoretical data).

It seems important to provide some perspective on the archeological stratigraphy drawn up by Miskovsky and Lévêque (

Visualization of the highest range of coherence indices of La Roche-à-Pierrot (left) and map of the site area excavated by F. Lévêque with location of the sectors with mechanical and clandestine excavation disturbances in level EJF (right; modified from

In addition to the matrix chromatic distinction between the yellow and gray sequences, there are probably differences in terms of fine-grained sediment inputs and varying degrees of admixture between allochthonous (sandy clay/clayey sand) and autochthonous (carbonated silty sands/sands or limestone blocks) sedimentary sources along the slope. Macroscopically, the chromatic differences in the matrix of the deposits and in lithofacies composition could therefore be associated with the spatial variability of the proportions of each of the sedimentary sources.

It is also necessary to take into account the 3D geometry of the lithofacies, whose characteristics vary spatially, not only in color but also in texture and structure, depending on the depositional processes (such as mass movement, debris fall, runoff) and post-depositional factors (e.g. bioturbation) that could be involved in site formation. A residual slope currently exists in the distal part of the deposits. Although locally anthropoturbated by historical human activities, it testifies to a gradual Pleistocene sedimentary accretion that took place on a weathered limestone substratum. The topography of the latter may have influenced the final geometry of the deposits, and thereby contributed to the spatial variability of the depths from which finds that were initially assigned to the same archeological level originated.

All these elements may explain, at least in part, the spatial variability of both the similarity and coherence indices, and why defining spatially-coherent levels from the proximal to distal parts of the site is difficult when using Lévêque’s reference section. Lévêque (

Identification of the archeological sequence on the basis of a fixed reference section (

In addition to these problems inherent in the excavation, the archives of F. Lévêque and A. Backer report anthropoturbations of the deposits (

The tools developed in this research provide a new descriptive and analytical approach for investigating archeological data retrieved from archives by 3D georeferenced visualization of primary recordings and also by computing spatial statistics using the Queen contiguity of the archeological sequence. Computation of both the similarity and coherence indices allows the geometry of the deposits and spatial inconsistencies to be outlined and then discussed in light of the original archeostratigraphic model of the site, as illustrated here with La Roche-à-Pierrot.

The descriptive and analytical possibilities offered by the new approach are not limited to use with spit data, but will allow other sources of archival data to be integrated, such as piece-plotted elements. In addition, the new tool presented here can be combined with the development of a virtual application at La Roche-à-Pierrot (VRPB;

The digital workflow and related tools presented here for visualizing and analyzing the stratigraphic attributes and geospatial information at La Roche-à-Pierrot will certainly be useful for other archeological projects where excavation archives and/or archeological stratigraphy data are available. The present methodology highlights novel avenues for future research, such as the design of applications and analytical tools that could assist in expanding analyses by incorporating the computation of the spatial autocorrelation (

Although geovisualization tools and 3D spatial statistics may present some practical and specific technical limitations, they also provide valuable information for discussing site formation processes, whether anthropogenic or natural. Ultimately, these new tools will allow us to reassess and enhance primary information from old excavations that may not have been conducted to today’s standards. More specifically, they will revive the legacy of past excavations and increase the importance of formerly excavated sites in the archeological record.

We are thankful to C. Schwab, curator of the Paleolithic and Mesolithic collections of the Musée d’Archéologie nationale (MAN, Saint-Germain-en-Laye, France), for granting us access to the Saint-Césaire faunal collection. We are grateful to C. Jouys-Barbelin and S. Morinière from the Resource center of the MAN, in charge of the curation of F. Lévêque’s archives, for their help and support in accessing the original excavation notebooks. We also thank E. Morin (Trent University) for sharing information with us about F. Lévêque’s excavations. HR received funding from the CSUN Competition for Research, Scholarship and Creative Activity Awards and from several research-supporting programs of the College of Social and Behavioral Sciences of CSUN (Research Competition, Summer Research Stipend, and Research Fellowship). The Collective Research Project of La Roche-à-Pierrot is funded by the Direction régionale des affaires culturelles of the Nouvelle-Aquitaine Region and by the Charente-Maritime Department, France. Finally, we thank the TGIR Huma-Num team (

The authors have no competing interests to declare.