Next Article in Journal
More Than Meets the Eye: Using Sentinel-2 to Map Small Plantations in Complex Forest Landscapes
Next Article in Special Issue
Quantitative Assessment for Detection and Monitoring of Coastline Dynamics with Temporal RADARSAT Images
Previous Article in Journal
Deep Learning with Unsupervised Data Labeling for Weed Detection in Line Crops in UAV Images
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
Remote Sens. 2018, 10(11), 1688; https://doi.org/10.3390/rs10111688

Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria)

1
Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Technikerstr. 21a, 6020 Innsbruck, Austria
2
Institute of Geography, University of Innsbruck, Innrain 52f, 6020 Innsbruck, Austria
3
Laserdata GmbH, Technikerstr. 21a, 6020 Innsbruck, Austria
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 27 August 2018 / Revised: 17 October 2018 / Accepted: 23 October 2018 / Published: 26 October 2018
(This article belongs to the Special Issue Mass Movement and Soil Erosion Monitoring Using Remote Sensing)
Full-Text   |   PDF [47686 KB, uploaded 26 October 2018]   |  

Abstract

Deep-seated gravitational slope deformations (DSGSDs) endanger settlements and infrastructure in mountain areas all over the world. To prevent disastrous events, their activity needs to be continuously monitored. In this paper, the movement of the Reissenschuh DSGSD in the Schmirn valley (Tyrol, Austria) is quantified based on point clouds acquired with a Riegl VZ®-6000 long-range laser scanner in 2016 and 2017. Geomorphological features (e.g., block edges, terrain ridges, scarps) travelling on top of the landslide are extracted from the acquired point clouds using morphometric attributes based on locally computed eigenvectors and -values. The corresponding representations of the extracted features in the multi-temporal data are exploited to derive 3D displacement vectors based on a workflow exploiting the iterative closest point (ICP) algorithm. The subsequent analysis reveals spatial patterns of landslide movement with mean displacements in the order of 0.62 ma 1 , corresponding well with measurements at characteristic points using a differential global navigation satellite system (DGNSS). The results are also compared to those derived from a modified version of the well-known image correlation (IMCORR) method using shaded reliefs of the derived digital terrain models. The applied extended ICP algorithm outperforms the raster-based method particularly in areas with predominantly vertical movement. View Full-Text
Keywords: DSGSD; landslide monitoring; laser scanning; remote sensing; geomorphological breaklines; Reissenschuh landslide DSGSD; landslide monitoring; laser scanning; remote sensing; geomorphological breaklines; Reissenschuh landslide
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Pfeiffer, J.; Zieher, T.; Bremer, M.; Wichmann, V.; Rutzinger, M. Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria). Remote Sens. 2018, 10, 1688.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top