Assessment of Rock Slope Stability Using Mobile LiDAR-Aided Hybrid Classification Systems: A Comparative Analysis of SMR, Q-Slope, and RHI

ABSTRACT This study evaluates andesite rock slope stability in İzmir, Türkiye, using mobile LiDAR (iPhone 14Pro) and hybrid classification systems. The acquired 3D point cloud (1.7 × 106 points) demonstrated high spatial accuracy when validated against global navigation satellite system data. Automated analysis via discontinuity set extractor revealed that applying a “full-persistence” assumption artificially reduces mean discontinuity spacing by 40–70 percent compared with a realistic “non-persistence” model, drastically underestimating rock block sizes. Kinematic analysis indicated a 40 percent probability of wedge failure, primarily driven by the highly persistent J6 set (lmax = 16 m). To directly compare slope mass rating (SMR), Q-slope, and rock hazard index (RHI) outputs, a “normalized risk index (Rindex)” was utilized. SMR yielded an overly optimistic evaluation Rindex = 0.41, failing to capture the geometric severity of the critical wedge. In contrast, RHI successfully identified this localized hazard (“moderate risk,” Rindex = 0.51) by directly accounting for geometric continuity. The Q-slope system proved to be the most conservative (Rindex = 0.60), indicating that the current 72° slope requires a reduction to 57°. The findings demonstrate that integrating mobile LiDAR with geometry-sensitive systems such as RHI provides a more reliable, targeted hazard assessment than traditional approaches.

Authors

Institutions

Publication Details

Journal
Environmental and Engineering Geoscience
Published
2026-10-13
DOI
https://doi.org/10.21663/eeg-d-26-00001
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of Rock Slope Stability Using Mobile LiDAR-Aided Hybrid Classification Systems: A Comparative Analysis of SMR, Q-Slope, and RHI

Cem Kıncal, Enes KALHAN
Environmental and Engineering Geoscience
Landslides and related hazards
article

Assessment of Rock Slope Stability Using Mobile LiDAR-Aided Hybrid Classification Systems: A Comparative Analysis of SMR, Q-Slope, and RHI

Cem Kıncal, Enes KALHAN
article en

Abstract

ABSTRACT This study evaluates andesite rock slope stability in İzmir, Türkiye, using mobile LiDAR (iPhone 14Pro) and hybrid classification systems. The acquired 3D point cloud (1.7 × 106 points) demonstrated high spatial accuracy when validated against global navigation satellite system data. Automated analysis via discontinuity set extractor revealed that applying a “full-persistence” assumption artificially reduces mean discontinuity spacing by 40–70 percent compared with a realistic “non-persistence” model, drastically underestimating rock block sizes. Kinematic analysis indicated a 40 percent probability of wedge failure, primarily driven by the highly persistent J6 set (lmax = 16 m). To directly compare slope mass rating (SMR), Q-slope, and rock hazard index (RHI) outputs, a “normalized risk index (Rindex)” was utilized. SMR yielded an overly optimistic evaluation Rindex = 0.41, failing to capture the geometric severity of the critical wedge. In contrast, RHI successfully identified this localized hazard (“moderate risk,” Rindex = 0.51) by directly accounting for geometric continuity. The Q-slope system proved to be the most conservative (Rindex = 0.60), indicating that the current 72° slope requires a reduction to 57°. The findings demonstrate that integrating mobile LiDAR with geometry-sensitive systems such as RHI provides a more reliable, targeted hazard assessment than traditional approaches.

Environmental and Engineering Geoscience
Dokuz Eylül University (TR)
Openalex Percentile: Top 9%
Landslides and related hazards
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.