Evaluation of stream-like landslide activity based on the monitoring results

2021 ◽  
pp. 1217-1222
Author(s):  
L. Petro ◽  
E. Polaščinová ◽  
P. Wagner
Keyword(s):  
2013 ◽  
Author(s):  
John Regan ◽  
Erin Leidy ◽  
Natasha Markuzon ◽  
Catherine Slesnick ◽  
Eddie Vaisman
Keyword(s):  

2011 ◽  
Vol 10 (1) ◽  
pp. 3-6
Author(s):  
Viorel-Ilie Arghius ◽  
Corina Arghius ◽  
Alexandru Ozunu ◽  
Eugen Nour ◽  
Gheorghe Rosian ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Andre C. Kalia

<p>Landslide activity is an important information for landslide hazard assessment. However, an information gap regarding up to date landslide activity is often present. Advanced differential interferometric SAR processing techniques (A-DInSAR), e.g. Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) are able to measure surface displacements with high precision, large spatial coverage and high spatial sampling density. Although the huge amount of measurement points is clearly an improvement, the practical usage is mainly based on visual interpretation. This is time-consuming, subjective and error prone due to e.g. outliers. The motivation of this work is to increase the automatization with respect to the information extraction regarding landslide activity.</p><p>This study focuses on the spatial density of multiple PSI/SBAS results and a post-processing workflow to semi-automatically detect active landslides. The proposed detection of active landslides is based on the detection of Active Deformation Areas (ADA) and a subsequent classification of the time series. The detection of ADA consists of a filtering of the A-DInSAR data, a velocity threshold and a spatial clustering algorithm (Barra et al., 2017). The classification of the A-DInSAR time series uses a conditional sequence of statistical tests to classify the time series into a-priori defined deformation patterns (Berti et al., 2013). Field investigations and thematic data verify the plausibility of the results. Subsequently the classification results are combined to provide a layer consisting of ADA including information regarding the deformation pattern through time.</p>


Author(s):  
Nicholas J. Roberts ◽  
Bernhard Rabus ◽  
Reginald L. Hermanns ◽  
Marco-Antonio Guzmán ◽  
John J. Clague ◽  
...  

2014 ◽  
Vol 9 ◽  
pp. 54-63 ◽  
Author(s):  
Guido Rianna ◽  
Alessandra Zollo ◽  
Paolo Tommasi ◽  
Matteo Paciucci ◽  
Luca Comegna ◽  
...  

2013 ◽  
Vol 17 (3) ◽  
pp. 947-959 ◽  
Author(s):  
D. M. Krzeminska ◽  
T. A. Bogaard ◽  
J.-P. Malet ◽  
L. P. H. van Beek

Abstract. The importance of hydrological processes for landslide activity is generally accepted. However, the relationship between precipitation, hydrological responses and movement is not straightforward. Groundwater recharge is mostly controlled by the hydrological material properties and the structure (e.g., layering, preferential flow paths such as fissures) of the unsaturated zone. In slow-moving landslides, differential displacements caused by the bedrock structure complicate the hydrological regime due to continuous opening and closing of the fissures, creating temporary preferential flow paths systems for infiltration and groundwater drainage. The consecutive opening and closing of fissure aperture control the formation of a critical pore water pressure by creating dynamic preferential flow paths for infiltration and groundwater drainage. This interaction may explain the seasonal nature of the slow-moving landslide activity, including the often observed shifts and delays in hydrological responses when compared to timing, intensity and duration of precipitation. The main objective of this study is to model the influence of fissures on the hydrological dynamics of slow-moving landslide and the dynamic feedbacks between fissures, hydrology and slope stability. For this we adapt the spatially distributed hydrological and slope stability model (STARWARS) to account for geotechnical and hydrological feedbacks, linking between hydrological response of the landside and the dynamics of the fissure network and applied the model to the hydrologically controlled Super-Sauze landslide (South French Alps).


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