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Volume 14
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10.3390/geosciences14020029
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Article

Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study

by
Andrés Cristóbal
1,
Xurxo Rigueira
1,
Ignacio Pérez-Rey
1,2,*,
Xian Estévez-Ventosa
1,3,
María Pazo
1,
Maria Lia Napoli
4,
Brais X. Currás
5 and
Leandro R. Alejano
1
1
Grupo de Xestión Segura e Sostible de Recursos Minerais, CINTECX, Departamento de Enxeñaría dos Recursos Naturais e Medio Ambiente, Universidade de Vigo, 36310 Vigo, Spain
2
Division of Soil and Rock Mechanics, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
3
Escuela Superior de Ingeniería y Tecnología, Universidad Internacional de La Rioja (UNIR), Av. La Paz 137, 26006 Logroño, Spain
4
Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, 10124 Torino, Italy
5
Departamento de Arqueología, Instituto de Historia, Consejo Superior de Investigaciones Científicas (CSIC), 28037 Madrid, Spain
*
Author to whom correspondence should be addressed.
Geosciences 2024, 14(2), 29; https://doi.org/10.3390/geosciences14020029
Submission received: 19 December 2023 / Revised: 16 January 2024 / Accepted: 24 January 2024 / Published: 26 January 2024
(This article belongs to the Topic Complex Rock Mechanics Problems and Solutions)
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Abstract

The mechanical behavior of block-in-matrix materials is heavily dependent on their block content. This parameter is in most cases obtained through visual analyses of the ground through digital imagery, which provides the areal block proportion (ABP) of the area analyzed. Nowadays, computer vision models have the capability to extract knowledge from the information stored in these images. In this research, we analyze and compare classical feature-detection algorithms with state-of-the-art models for the automatic calculation of the ABP parameter in images from surface and underground outcrops. The outcomes of this analysis result in the development of a framework for ABP calculation based on the Segment Anything Model (SAM), which is capable of performing this task at a human level when compared with the results of 32 experts in the field. Consequently, this model can help reduce human bias in the estimation of mechanical properties of block-in-matrix materials as well as contain underground technical problems due to mischaracterization of rock block quantities and dimensions. The methodology used to obtain the ABP at different outcrops is combined with estimates of the rock matrix properties and other characterization techniques to mechanically characterize the block-in-matrix materials. The combination of all these techniques has been applied to analyze, understand and try, for the first time, to model Roman gold-mining strategies in an archaeological site in NW Spain. This mining method is explained through a 2D finite-element method numerical model.
Keywords: block-in-matrix materials; computer vision; Segment Anything Model; areal block proportion (ABP) block-in-matrix materials; computer vision; Segment Anything Model; areal block proportion (ABP)

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MDPI and ACS Style

Cristóbal, A.; Rigueira, X.; Pérez-Rey, I.; Estévez-Ventosa, X.; Pazo, M.; Napoli, M.L.; Currás, B.X.; Alejano, L.R. Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study. Geosciences 2024, 14, 29. https://doi.org/10.3390/geosciences14020029

AMA Style

Cristóbal A, Rigueira X, Pérez-Rey I, Estévez-Ventosa X, Pazo M, Napoli ML, Currás BX, Alejano LR. Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study. Geosciences. 2024; 14(2):29. https://doi.org/10.3390/geosciences14020029

Chicago/Turabian Style

Cristóbal, Andrés, Xurxo Rigueira, Ignacio Pérez-Rey, Xian Estévez-Ventosa, María Pazo, Maria Lia Napoli, Brais X. Currás, and Leandro R. Alejano. 2024. "Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study" Geosciences 14, no. 2: 29. https://doi.org/10.3390/geosciences14020029

APA Style

Cristóbal, A., Rigueira, X., Pérez-Rey, I., Estévez-Ventosa, X., Pazo, M., Napoli, M. L., Currás, B. X., & Alejano, L. R. (2024). Automatic Characterization of Block-In-Matrix Rock Outcrops through Segmentation Algorithms and Its Application to an Archaeo-Mining Case Study. Geosciences, 14(2), 29. https://doi.org/10.3390/geosciences14020029

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