A review of the current state of 3D subsurface cartography for geotechnical ground characterization
DOI:
https://doi.org/10.54355/tbus/6.1.2026.0097Keywords:
3D subsurface mapping, geotechnical ground characterization, voxel models, implicit structural modeling, uncertainty and validationAbstract
Three-dimensional subsurface mapping is increasingly used to turn ground investigation evidence into continuous 3D models of soil layers and geotechnical properties that support decisions in ground characterization. This review summarizes the current state of 3D mapping for geotechnical purposes using a citation-guided selection based on Litmaps, resulting in a curated set of 27 studies. The literature is organized into a taxonomy aligned with the Litmaps clustering and grouped into six approach families: implicit or potential-field structural modeling, voxel models and voxel workflows, uncertainty-oriented stochastic and inversion or segmentation approaches, automation and urban-scale pipelines, geophysics-driven 3D modeling, and interoperability and engineering delivery. The comparative analysis shows that practical outcomes depend not only on the final model type but also on workflow design, including data harmonization, modeling rules, and update procedures. Credibility depends on validation methods matched to the target variable and on uncertainty outputs that show where the model is strongly supported by data and where it relies on extrapolation. The review also highlights model comparability as a key operational issue, since mismatches between neighboring models can arise from inconsistent conceptual rules, discretization differences, uneven data density, and asymmetric auxiliary constraints. The paper concludes with an applicability framework, including a decision flow and compact criteria, to guide selection, evaluation, and reporting of decision-grade 3D subsurface mapping products for geotechnical ground characterization.
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Copyright (c) 2026 Nurgul Alibekova, Aleksej Aniskin, Kairat Mukhambetkaliev, Indira Makasheva
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Ministry of Education and Science of the Republic of Kazakhstan
Grant numbers AP26198009
