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

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).

Robinia pseudoacacia L. Flower Analyzed by Using An Unmanned Aerial Vehicle (UAV)

“…UAV technology is a sustainable technology that provides high-resolution analyses and minimal environmental damage. Therefore, the methodology of this study and of other studies [39,51,52,65] should be further tested to determine whether it is applicable to other tree species of differing ages and in mixed-forest stands. One hypothesis is that older trees probably have a different vertical crown structure (more branch layers) and thus contribute a different proportion of captured flowers.…”

Earth Observations for Geohazards: Present and Future Challenges

“…Kropáček et al [25] monitor the displacements of a large landslide on the western escarpment of the Main Ethiopian Rift (Debre Sina) by means of a multisensor and multitechnique approach. Fernández et al [26] use Unmanned Aerial Vehicles imagery and high resolution photogrammetry to monitor horizontal and vertical displacements of a landslide affecting olive groves in La Guardia de Jaén (Spain). Finally, in Hsieh et al [27], the errors of digital terrain models (DTMs) derived using different techniques are discussed.…”

Unravelling earth flow dynamics with 3-D time series derived from UAV-SfM models

“…As such, UAV-SfM models can complement data on the internal structure and mass movements' dynamics that are commonly derived from geophysical and/or geotechnical methods (e.g. Fressard et al, 2016;Merritt et al, 2014;Perrone et al, 2014).…”

“…DEM differencing has been combined with image correlation techniques (COSICorr) to assess horizontal displacements and determine landslide dynamics (Lucieer et al, 2014;Turner et al, 2015). Recent UAV-based landslide studies included the assessment of point-based horizontal displacements from displacement vectors between corresponding features on pairs of orthophotos (Fernández et al, 2016;Peternel et al, 2017), and crosssection profiles to get an insight into the landslide's internal structure (Tanteri et al, 2017). Using ground-based images, Stumpf et al (2014) assessed the seasonal dynamics of the Super-Sauze landslide over a 2-year period, by using a 3-D change detection algorithm, i.e.…”

“…However, the potential of the SfM algorithm and the derived 3-D dense point clouds is not yet fully exploited for landslide monitoring. Time series of topographic data derived from UAV-SfM data are mainly used to compute DEMs of differences (DoD) from temporal pairs of topographic representations (Fernández et al, 2016;Huang et al, 2017;Peternel et al, 2017;Tanteri et al, 2017). DEM differencing has been combined with image correlation techniques (COSICorr) to assess horizontal displacements and determine landslide dynamics (Lucieer et al, 2014;Turner et al, 2015).…”