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MC-H-Geo: A Multi-Scale Contextual Hierarchical Framework for Fine-Grained Lithology Classification.

Lang Liu1, Yanlin Shao1,2, Yaxiong Shao3

  • 1School of Geosciences, Yangtze University, Wuhan 430100, China.

Sensors (Basel, Switzerland)
|November 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces MC-H-Geo, an automated framework for lithological mapping using terrestrial laser scanning (TLS). It achieves high accuracy in classifying rock types from outcrop data, improving geological interpretations.

Keywords:
TLS point cloudsgeological mappinghierarchical modellithology classificationmulti-scale contextual learning

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Area of Science:

  • Geoscience
  • Remote Sensing
  • Artificial Intelligence

Background:

  • High-resolution lithological mapping is crucial for reservoir characterization and petroleum geology.
  • Distinguishing lithologies with subtle petrophysical contrasts from outcrop data presents a significant challenge.

Purpose of the Study:

  • To develop an automated framework for lithological classification from terrestrial laser scanning (TLS) point clouds.
  • To enhance the accuracy and geological consistency of outcrop interpretation.

Main Methods:

  • Proposed MC-H-Geo: a multi-scale contextual hierarchical framework.
  • Integrated a multi-scale contextual feature engine, gated expert classifier, and geological post-processing.
  • Utilized spectral, geometric, and textural descriptors with cross-scale differentials and stratigraphic continuity enforcement.

Main Results:

  • Achieved state-of-the-art performance on the Qianwangjiahe outcrop (OA = 94.3%, Macro F1 = 0.944).
  • Outperformed existing methods like PointNet++ (77.1%), SG-RFGeo (74.2%), and XGBoost (61.7%).
  • Identified sandstone-vegetation confusion in weathered zones as a limitation of TLS-only data.

Conclusions:

  • MC-H-Geo establishes an advanced framework for fine-grained lithological mapping.
  • Multi-sensor data fusion is identified as a promising approach for robust, geologically consistent outcrop interpretation.