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

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

doi:https://doi.org/10.5194/nhess-17-2143-2017

Articles | Volume 17, issue 12

https://doi.org/10.5194/nhess-17-2143-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

The use of remotely piloted aircraft systems (RPAS) in monitoring...

https://doi.org/10.5194/nhess-17-2143-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 12

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

Data sets

Surface morphological attributes derived from an Unmanned Aerial Vehicle (UAV) M. V. Peppa, J. P. Mills, P. Moore, P. E. Miller, and J. E. Chambers https://doi.org/10.17634/154300-58

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.