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Remote Sens. 2016, 8(10), 837; doi:10.3390/rs8100837

Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques

1
Department of Cartographic, Geodetic and Photogrammetric Engineering, University of Jaén, Campus de las Lagunillas s/n, 23071 Jaén, Spain
2
Centre for Advanced Studies in Earth Sciences (CEACTierra), University of Jaén, Campus de las Lagunillas s/n, 23071 Jaén, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Zhenhong Li, Roberto Tomas, Norman Kerle and Prasad S. Thenkabail
Received: 30 June 2016 / Revised: 20 September 2016 / Accepted: 29 September 2016 / Published: 13 October 2016
(This article belongs to the Special Issue Earth Observations for Geohazards)
View Full-Text   |   Download PDF [52269 KB, uploaded 13 October 2016]   |  

Abstract

This paper deals with the application of Unmanned Aerial Vehicles (UAV) techniques and high resolution photogrammetry to study the evolution of a landslide affecting olive groves. The last decade has seen an extensive use of UAV, a technology in clear progression in many environmental applications like landslide research. The methodology starts with the execution of UAV flights to acquire very high resolution images, which are oriented and georeferenced by means of aerial triangulation, bundle block adjustment and Structure from Motion (SfM) techniques, using ground control points (GCPs) as well as points transferred between flights. After Digital Surface Models (DSMs) and orthophotographs were obtained, both differential models and displacements at DSM check points between campaigns were calculated. Vertical and horizontal displacements in the range of a few decimeters to several meters were respectively measured. Finally, as the landslide occurred in an olive grove which presents a regular pattern, a semi-automatic approach to identifying and determining horizontal displacements between olive tree centroids was also developed. In conclusion, the study shows that landslide monitoring can be carried out with the required accuracy—in the order of 0.10 to 0.15 m—by means of the combination of non-invasive techniques such as UAV, photogrammetry and geographic information system (GIS). View Full-Text
Keywords: Unmanned Aerial Vehicle (UAV); photogrammetric techniques; Structure from Motion (SfM); landslide evolution; olive grove Unmanned Aerial Vehicle (UAV); photogrammetric techniques; Structure from Motion (SfM); landslide evolution; olive grove
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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).

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MDPI and ACS Style

Fernández, T.; Pérez, J.L.; Cardenal, J.; Gómez, J.M.; Colomo, C.; Delgado, J. Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sens. 2016, 8, 837.

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