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Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes

Lookup NU author(s): Dr Maria-Valasia Peppa, Professor Jon Mills, Professor Philip Moore

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that morphological attribute of openness, amongst others, can provide to surface deformation analysis. Image cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys.


Publication metadata

Author(s): Peppa MV, Mills JP, Moore P, Miller PE, Chambers JE

Publication type: Article

Publication status: Published

Journal: Natural Hazards and Earth System Sciences

Year: 2017

Volume: 17

Issue: 12

Pages: 2143-2150

Online publication date: 04/12/2017

Acceptance date: 25/10/2017

ISSN (print): 1561-8633

ISSN (electronic): 1684-9981

Publisher: Copernicus GmbH

URL: https://doi.org/10.5194/nhess-2017-201

DOI: 10.5194/nhess-2017-201

Data Source Location: http://dx.doi.org/10.17634/154300-58


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