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

Viewed

Total article views: 3,245 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,836 1,281 128 3,245 126 143
  • HTML: 1,836
  • PDF: 1,281
  • XML: 128
  • Total: 3,245
  • BibTeX: 126
  • EndNote: 143
Views and downloads (calculated since 13 Jun 2017)
Cumulative views and downloads (calculated since 13 Jun 2017)

Viewed (geographical distribution)

Total article views: 3,245 (including HTML, PDF, and XML) Thereof 3,078 with geography defined and 167 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 08 Aug 2025
Download
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.
Share
Altmetrics
Final-revised paper
Preprint