Investigation of Riverbank Peat Erosion in a small Alpine catchment by Multi-Temporal Point Cloud Change Analysis and Time Series Clustering

Abstract. Peatlands play an important role as local carbon sinks and climate archives in natural environments. In addition to degradation by human activities, peatlands can also be affected by geomorphological processes such as fluvial erosion. This study used a collection of multi-temporal 3D point clouds to investigate such a situation in a valley of the Central Alps (Austria), where a dynamically migrating river is eroding peat. To detect time periods and locations where strong erosion occurred and to quantify the local peat erosion rate over the years 2006 to 2024, 3D point clouds from airborne laser scanning (ALS), uncrewed aerial vehicle laser scanning (ULS), and uncrewed aerial vehicle photogrammetry (UPH) were used (i) in a pair-wise Multiscale Model-to-Model Cloud Comparison (M3C2) change detection and quantification and (ii) in a time-series clustering approach. In the most dynamic sections of the river bank, the mean rate of peat erosion over the eighteen-year period was −0.12 ± 0.03 m/year. Moreover, the relationship between peatland erosion and main channel migration is investigated based on a set of surface elevation transects and multi-temporal mapping of the main channels. Overall, these methods provided detailed insights into the dynamics and functioning of local geomorphological processes, such as lateral undercutting with subsequent toppling and sliding of the peat bank.

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Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2025-07-14
DOI
https://doi.org/10.5194/isprs-annals-x-g-2025-937-2025
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Investigation of Riverbank Peat Erosion in a small Alpine catchment by Multi-Temporal Point Cloud Change Analysis and Time Series Clustering

Jiapan Wang, János Mészáros, Rasoul Eskandari, E.C. Rowe et al.
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Remote Sensing and LiDAR Applications
article

Investigation of Riverbank Peat Erosion in a small Alpine catchment by Multi-Temporal Point Cloud Change Analysis and Time Series Clustering

Jiapan Wang, János Mészáros, Rasoul Eskandari, E.C. Rowe, Andreas Mayr, Changhong Lin, Martin Rutzinger, Laura Obrecht, Jules Salzinger
article en

Abstract

Abstract. Peatlands play an important role as local carbon sinks and climate archives in natural environments. In addition to degradation by human activities, peatlands can also be affected by geomorphological processes such as fluvial erosion. This study used a collection of multi-temporal 3D point clouds to investigate such a situation in a valley of the Central Alps (Austria), where a dynamically migrating river is eroding peat. To detect time periods and locations where strong erosion occurred and to quantify the local peat erosion rate over the years 2006 to 2024, 3D point clouds from airborne laser scanning (ALS), uncrewed aerial vehicle laser scanning (ULS), and uncrewed aerial vehicle photogrammetry (UPH) were used (i) in a pair-wise Multiscale Model-to-Model Cloud Comparison (M3C2) change detection and quantification and (ii) in a time-series clustering approach. In the most dynamic sections of the river bank, the mean rate of peat erosion over the eighteen-year period was −0.12 ± 0.03 m/year. Moreover, the relationship between peatland erosion and main channel migration is investigated based on a set of surface elevation transects and multi-temporal mapping of the main channels. Overall, these methods provided detailed insights into the dynamics and functioning of local geomorphological processes, such as lateral undercutting with subsequent toppling and sliding of the peat bank.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-G-2025
AIT Austrian Institute of Technology GmbH (AT), National Yang Ming Chiao Tung University (TW), Universität Innsbruck (AT), University of Cambridge (GB), Scientific Committee on Antarctic Research (GB), Institute of Geography (KZ), Institute for Soil Sciences (HU), HUN-REN Centre for Agricultural Research (HU), Institute of Geography of the Slovak Academy of Sciences (SK), Technical University of Munich (DE), Politecnico di Milano (IT)
Universität Innsbruck
Openalex Percentile: Top 84%
Remote Sensing and LiDAR Applications
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