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New Visual Analytics Tool and Spatial Statistics to Explore Archeological Data: The Case of the Paleolithic Sequence of La Roche-à-Pierrot, Saint-Césaire, France Cover

New Visual Analytics Tool and Spatial Statistics to Explore Archeological Data: The Case of the Paleolithic Sequence of La Roche-à-Pierrot, Saint-Césaire, France

Open Access
|Mar 2022

Figures & Tables

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Figure 1

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.

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Figure 2

Reference section (left) and sequence (right) of the archeological stratigraphy of La Roche-à-Pierrot (after Lévêque 1997). The red triangle indicates the location of the Saint-Césaire 1 Neandertal remains.

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Figure 3

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).

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Figure 4

Process flowchart from data to interactive visualization.

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Figure 5

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

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Figure 6

Color scheme selected for the levels of Lévêque’s archeological stratigraphy, see Figure 2. EJ is a grouping of undifferentiated layers from the ensemble jaune and EGPS is a facies of EGP.

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Figure 7

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.

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Figure 8

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

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Figure 9

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).

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Figure 10

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).

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Figure 11

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).

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Figure 12

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).

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Figure 13

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).

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Figure 14

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).

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Figure 15

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

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Figure 16

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

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Figure 17

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 Backer 1994).

DOI: https://doi.org/10.5334/jcaa.81 | Journal eISSN: 2514-8362
Language: English
Submitted on: Aug 2, 2021
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Accepted on: Jan 21, 2022
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Published on: Mar 3, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Armelle Couillet, Hélène Rougier, Dominique Todisco, Josserand Marot, Olivier Gillet, Isabelle Crevecoeur, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.