Rill Erosion and Drainage Development in Post-Landslide Settings Using UAV–LiDAR Data

Accurate microtopography data are an important input for characterizing small-scale rill erosion and its progression following disturbances. UAV–LiDAR systems are increasingly accessible and have successfully been used to measure microtopography data for several applications. Yet, the use of UAV–LiDAR systems for rill erosion studies in post-landslide landscapes have not been well investigated. Therefore, the purpose of this study was to implement and evaluate a UAV–LiDAR-based workflow to capture the microtopography of a post-landslide landscape, and by doing so, to help to determine best practices for UAV–LiDAR-based rill analysis. A commercial UAV–LiDAR system was used to map three post-landslide slopes and generate digital elevation models with a 1 cm-per-pixel ground resolution. Using data captured over multiple years, temporal rill development was assessed by comparing rill cross-sections and calculating changes to rill density and erosion volume. A flow-accumulation algorithm was adopted to automatically extract the rill network. We found that a flow accumulation algorithm with a threshold value of 5000 detected the rill network with overall accuracies of >88% and F1-scores of >93%. Vertical cross-sections of individual rills revealed an increase in the depth and width of rills over a one-year period. This study demonstrates that a commercial UAV–LiDAR system can effectively describe microtopography in a post-landslide landscape and facilitate analysis of small-scale rill characteristics and the progression of rill erosion.

Authors

Institutions

Publication Details

Journal
Soil Systems
Published
2025-05-01
DOI
https://doi.org/10.3390/soilsystems9020042
Citations
1
Primary Topic
Soil erosion and sediment transport
Type
article
Field-Weighted Citation Impact
1.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rill Erosion and Drainage Development in Post-Landslide Settings Using UAV–LiDAR Data

Saleh Alsulamy, Ram Avtar, Albertus S. Louw, Deha Agus Umarhadi et al.
1 citations
Soil Systems
Soil erosion and sediment transport
1.19
article

Rill Erosion and Drainage Development in Post-Landslide Settings Using UAV–LiDAR Data

Saleh Alsulamy, Ram Avtar, Albertus S. Louw, Deha Agus Umarhadi, Xinyu Chen, Yunus Ali Pulpadan, Md. Alamgir Hossen Bhuiyan
article en
1 citations

Abstract

Accurate microtopography data are an important input for characterizing small-scale rill erosion and its progression following disturbances. UAV–LiDAR systems are increasingly accessible and have successfully been used to measure microtopography data for several applications. Yet, the use of UAV–LiDAR systems for rill erosion studies in post-landslide landscapes have not been well investigated. Therefore, the purpose of this study was to implement and evaluate a UAV–LiDAR-based workflow to capture the microtopography of a post-landslide landscape, and by doing so, to help to determine best practices for UAV–LiDAR-based rill analysis. A commercial UAV–LiDAR system was used to map three post-landslide slopes and generate digital elevation models with a 1 cm-per-pixel ground resolution. Using data captured over multiple years, temporal rill development was assessed by comparing rill cross-sections and calculating changes to rill density and erosion volume. A flow-accumulation algorithm was adopted to automatically extract the rill network. We found that a flow accumulation algorithm with a threshold value of 5000 detected the rill network with overall accuracies of >88% and F1-scores of >93%. Vertical cross-sections of individual rills revealed an increase in the depth and width of rills over a one-year period. This study demonstrates that a commercial UAV–LiDAR system can effectively describe microtopography in a post-landslide landscape and facilitate analysis of small-scale rill characteristics and the progression of rill erosion.

Soil SystemsVol. 9(2)
Universitas Gadjah Mada (ID), Indian Institute of Science Education and Research Mohali (IN), Longyan University (CN), Hokkaido University (JP), King Khaled Hospital (SA), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 21%
Soil erosion and sediment transport
1.19
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.