2002
DOI: 10.1016/s0169-555x(01)00098-8
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The use of Global Positioning System techniques for the continuous monitoring of landslides: application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France)

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Cited by 288 publications
(193 citation statements)
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References 31 publications
(39 reference statements)
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“…These landslides display distinct seasonal velocity changes, with periods of increased velocity that correspond to periods of elevated porewater pressures. Numerous other landslides in this region (31,32), and elsewhere that similar environmental conditions (i.e., tectonics, lithology, and climate) prevail, display similar displacement patterns and are likely driven by comparable stress perturbations (3,33,34).…”
Section: [4]mentioning
confidence: 93%
See 1 more Smart Citation
“…These landslides display distinct seasonal velocity changes, with periods of increased velocity that correspond to periods of elevated porewater pressures. Numerous other landslides in this region (31,32), and elsewhere that similar environmental conditions (i.e., tectonics, lithology, and climate) prevail, display similar displacement patterns and are likely driven by comparable stress perturbations (3,33,34).…”
Section: [4]mentioning
confidence: 93%
“…These boundary conditions can be interpreted to represent steady long-term motion induced by loading due to headscarp slumping at the upper boundary and toe erosion at the lower boundary. The slip-rate gradient is chosen to simulate velocity variations along the sliding surface that are commonly observed (22,33). We recognize that many landslides display more complex slip gradients but neglect such complications here to focus upon the most essential underlying controls.…”
Section: Methodsmentioning
confidence: 99%
“…However, it is mainly tensile fracturing that dominates the fissure formation at the free surface of the Super-Sauze landslide Stumpf et al, 2013). The long-term field monitoring and airborne ortho-photo or UAVbased ortho-mosaic analysis (Malet et al, 2002;Malet, 2003;Niethammer et al, 2012) allow for the identifying of the typical surface fissure patterns and their distribution across the landslide. It can be observed that the spatial distribution of fissure patterns is not changing significantly in time despite continuous landslide activity.…”
Section: Mechanical Feedbackmentioning
confidence: 99%
“…Current landslide forecast is based on empirical formula (e.g., Saito 1965), linear forecast (Rennie 2010), nonlinear forecast (Feng et al 2010;Li et al 2012), phenomenon forecast (Xu et al 2008), GPS forecast (Malet et al 2002), and monitoring forecast (Giovanni et al 2011). Although many landslide forecast models and criteria have been proposed, landslide forecast practice has shown that the existing forecast models can not accurately forecast landslide deformations.…”
Section: Introductionmentioning
confidence: 99%