Where the Hills Slide Slowly: A LiDAR-Based Morphometric Framework for Landslide Instability Regimes in Soft-Rock Terrains

Deep-seated landslide complexes are widespread in soft-rock hill-country landscapes, yet their regional morphometric organisation and controlling factors remain insufficiently quantified. This study uses high-resolution (1 m) airborne LiDAR-derived terrain data integrated with geological and drainage-network datasets to investigate landslide complexes in the eastern Tararua District, New Zealand. A relative, unit-based morphometric framework is applied to compare terrain derivatives (including slope, aspect, and multi-scale relative relief) between mapped landslides and their host geological units. To isolate intrinsic lithological controls from geomorphic influences, the analysis is restricted to landslides occurring entirely within a single geological unit. The results indicate that lithology exerts first-order control on landslide morphometry, while fluvial incision and valley confinement regulate landslide initiation and persistence. Landslides are preferentially associated with low- to mid-order channels, indicating strong hillslope–channel coupling within a young, actively uplifting landscape. A conceptual threshold framework is proposed, showing that landslides develop where lithological susceptibility and relief amplification jointly exceed stability thresholds. By integrating geological information with LiDAR-based morphometric analysis, this study provides a transferable framework for distinguishing instability regimes and improving understanding of sediment dynamics and landscape evolution in soft-rock terrains.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2026-04-11
DOI
https://doi.org/10.3390/rs18081135
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

Where the Hills Slide Slowly: A LiDAR-Based Morphometric Framework for Landslide Instability Regimes in Soft-Rock Terrains

Szabolcs Kósik, Callum Rees
Remote Sensing
Landslides and related hazards
article

Where the Hills Slide Slowly: A LiDAR-Based Morphometric Framework for Landslide Instability Regimes in Soft-Rock Terrains

Szabolcs Kósik, Callum Rees
article en

Abstract

Deep-seated landslide complexes are widespread in soft-rock hill-country landscapes, yet their regional morphometric organisation and controlling factors remain insufficiently quantified. This study uses high-resolution (1 m) airborne LiDAR-derived terrain data integrated with geological and drainage-network datasets to investigate landslide complexes in the eastern Tararua District, New Zealand. A relative, unit-based morphometric framework is applied to compare terrain derivatives (including slope, aspect, and multi-scale relative relief) between mapped landslides and their host geological units. To isolate intrinsic lithological controls from geomorphic influences, the analysis is restricted to landslides occurring entirely within a single geological unit. The results indicate that lithology exerts first-order control on landslide morphometry, while fluvial incision and valley confinement regulate landslide initiation and persistence. Landslides are preferentially associated with low- to mid-order channels, indicating strong hillslope–channel coupling within a young, actively uplifting landscape. A conceptual threshold framework is proposed, showing that landslides develop where lithological susceptibility and relief amplification jointly exceed stability thresholds. By integrating geological information with LiDAR-based morphometric analysis, this study provides a transferable framework for distinguishing instability regimes and improving understanding of sediment dynamics and landscape evolution in soft-rock terrains.

Remote SensingVol. 18(8)
Environment Canterbury (NZ), Palmerston North City Council (NZ), Massey University (NZ)
Life in Land
Openalex Percentile: Top 21%
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.