Articles | Volume 17, issue 12
https://doi.org/10.5194/nhess-17-2143-2017
https://doi.org/10.5194/nhess-17-2143-2017
Brief communication
 | 
04 Dec 2017
Brief communication |  | 04 Dec 2017

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

Maria V. Peppa, Jon P. Mills, Phil Moore, Pauline E. Miller, and Jonathan E. Chambers

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 the 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.

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Short summary
Unmanned aerial vehicles can provide digital elevation models and orthomosaics of high spatio-temporal resolution to enable landslide monitoring. The study examines the additional value that morphological attribute of openness can provide to surface deformation combining with image-cross-correlation functions alongside DEM differencing. The paper demonstrates the automated quantification of a landslide's motion over time with implications for the wider interpretation of landslide kinematics.
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