scholarly journals Landslide susceptibility assessment in the Peloritani Mts. (Sicily, Italy) and clues for tectonic control of relief processes

2013 ◽  
Vol 13 (4) ◽  
pp. 949-963 ◽  
Author(s):  
G. De Guidi ◽  
S. Scudero
Keyword(s):  
Spatial Data ◽  
Landslide Susceptibility ◽  
Landscape Evolution ◽  
Statistical Technique ◽  
Slope Instability ◽  
Tectonic Activity ◽  
Medium Term ◽  
Tectonic History ◽  
Susceptibility Model ◽  
Morphological Processes

Abstract. Many destructive shallow landslides hit villages in the Peloritani Mountains area (Sicily, Italy) on 1 October 2009 after heavy rainfall. The collection of several types of spatial data, together with a landslide inventory, allows the assessment of the landslide susceptibility by applying a statistical technique. The susceptibility model was validated by performing an analysis in a test area using independent landslide information, the results being able to correctly predict more than 70% of the landslides. Furthermore, the susceptibility analysis allowed the identification of which combinations of classes, within the different factors, have greater relevance in slope instability, and afterwards associating the most unstable combinations (with a short–medium term incidence) with the endogenic processes acting in the area (huge regional uplift, fault activity). Geological and tectonic history are believed to be key to interpreting morphological processes and landscape evolution. Recent tectonic activity was found to be a very important controlling factor in landscape evolution. A geomorphological model of cyclical relief evolution is proposed in which endogenic processes are directly linked to superficial processes. The results are relevant both to risk reduction and the understanding of active geological dynamics.

scholarly journals Applicability of Susceptibility Model for Rock and Loess Earthquake Landslides in the Eastern Tibetan Plateau

2021 ◽  
Vol 13 (13) ◽  
pp. 2546
Author(s):  
Xinyi Guo ◽  
Bihong Fu ◽  
Jie Du ◽  
Pilong Shi ◽  
Qingyu Chen ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Disaster Relief ◽  
Coupling Model ◽  
Scientific Data ◽  
Eastern Tibetan Plateau ◽  
Loess Landslide ◽  
Rock Landslide ◽  
Susceptibility Model ◽  
Prediction Capability ◽  
Better Than

It is crucial to explore a suitable landslide susceptibility model with an excellent prediction capability for rapid evaluation and disaster relief in seismic regions with different lithological features. In this study, we selected two typical seismic events, the Jiuzhaigou and Minxian earthquakes, which occurred in the Alpine karst and loess regions, respectively. Eight influencing factors and five models were chosen to calculate the susceptibility of landslide, including the information (I) model, certainty factor (CF) model, logistic regression (LR) model, I + LR coupling model, and CF + LR coupling model. Then, the accuracy and the landslide susceptibility distribution of these models were assessed by the area under curve (AUC) and distribution criteria. Finally, the model with high accuracy and good applicability for the rock landslide or loess landslide regions was optimized. Our results showed that the accuracy of the coupling model is higher than that of the single models. Except for the LR model, the landslide susceptibility distribution for the above-mentioned models is consistent with universal cognition. The coupling models are generally better than their single models. Among them, the I + LR model can obtain the best comprehensive results for assessing the distribution and accuracy of both rock and loess landslide susceptibility, which is helpful for disaster relief and policy-making, and it can also provide useful scientific data for post-seismic reconstruction and restoration.

scholarly journals From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations

2021 ◽  
Author(s):  
Luguang Luo ◽  
Luigi Lombardo ◽  
Cees van Westen ◽  
Xiangjun Pei ◽  
Runqiu Huang
Keyword(s):  
Ground Motion ◽  
Land Use Planning ◽  
Landslide Susceptibility ◽  
Additive Model ◽  
Slope Instability ◽  
Susceptibility Map ◽  
Jiuzhaigou Earthquake ◽  
Full Spectrum ◽  
The Past ◽  
Time Invariant

AbstractThe vast majority of statistically-based landslide susceptibility studies assumes the slope instability process to be time-invariant under the definition that “the past and present are keys to the future”. This assumption may generally be valid. However, the trigger, be it a rainfall or an earthquake event, clearly varies over time. And yet, the temporal component of the trigger is rarely included in landslide susceptibility studies and only confined to hazard assessment. In this work, we investigate a population of landslides triggered in response to the 2017 Jiuzhaigou earthquake ($$M_w = 6.5$$ M w = 6.5 ) including the associated ground motion in the analyses, these being carried out at the Slope Unit (SU) level. We do this by implementing a Bayesian version of a Generalized Additive Model and assuming that the slope instability across the SUs in the study area behaves according to a Bernoulli probability distribution. This procedure would generally produce a susceptibility map reflecting the spatial pattern of the specific trigger and therefore of limited use for land use planning. However, we implement this first analytical step to reliably estimate the ground motion effect, and its distribution, on unstable SUs. We then assume the effect of the ground motion to be time-invariant, enabling statistical simulations for any ground motion scenario that occurred in the area from 1933 to 2017. As a result, we obtain the full spectrum of potential coseismic susceptibility patterns over the last century and compress this information into a hazard model/map representative of all the possible ground motion patterns since 1933. This backward statistical simulations can also be further exploited in the opposite direction where, by accounting for scenario-based ground motion, one can also use it in a forward direction to estimate future unstable slopes.

Unmanned Aerial Vehicle (UAV) time-lapse monitoring of the instability processes affecting Varano Hill: A case study of the ancient Roman site of Villa Arianna

2021 ◽  
Author(s):  
Renato Somma ◽  
Alfredo Trocciola ◽  
Daniele Spizzichino ◽  
Alessandro Fedele ◽  
Gabriele Leoni ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Data ◽  
Morphological Evolution ◽  
Archaeological Site ◽  
Pilot Project ◽  
Time Lapse ◽  
3D Models ◽  
Slope Instability ◽  
Test Case ◽  
Slope Instabilities

<p>The archaeological site of Villa Arianna - located on Varano Hill, south of Vesuvius - offer tantalizing information regarding first-century AD resilience to hydrogeological risk. Additionally, the site provides an important test case for mitigation efforts of current and future geo-hazard. Villa Arianna, notable in particular for its wall frescoes, is part of a complex of Roman villas built between 89 BC and AD 79 in the ancient coastal resort area of Stabiae. This villa complex is located on a morphological terrace that separates the ruins from the present-day urban center of Castellammare di Stabia. The Varano hill is formed of alternating pyroclastic deposits, from the Vesuvius Complex, and alluvial sediments, from the Sarno River. The area, in AD 79, was completely covered by PDCs from the Plinian eruption of Vesuvius. Due to the geomorphological structure the slope is prone to slope instability phenomena that are mainly represented by earth and debris flows, usually triggered by heavy rainfall. The susceptibility is worsened by changes in hydraulic and land-use conditions mainly caused by lack of maintenance of mitigation works. Villa Arianna is the subject of a joint pilot project of the INGV-ENEA-ISPRA that includes non-invasive monitoring techniques such as the use of UAVs to study the areas of the slope at higher risk of instability. The project, in particular, seeks to implement innovative mitigation solutions that are non-destructive to the cultural heritage. UAVs represent the fastest way to produce high-resolution 3D models of large sites and allow archaeologists to collect accurate spatial data that can be used for 3D GIS analyses. Through this pilot project, we have used detailed 3D models and high-resolution ortho-images for new analyses and documentation of the site and to map the slope instabilities that threatens the Villa Arianna site. Through multi-temporal analyses of different data acquisitions, we intend to define the detailed morphological evolution of the entire Varano slope. These analyses will allow us to highlight priority areas for future low-impact mitigation interventions.</p>

scholarly journals LANDSLIDE SUSCEPTIBILITY ASSESSMENT THROUGH FUZZY LOGIC INFERENCE SYSTEM (FLIS)

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 355-360 ◽  
Author(s):  
T. Bibi ◽  
Y. Gul ◽  
A. Abdul Rahman ◽  
M. Riaz
Keyword(s):  
Fuzzy Logic ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Landslide Susceptibility Mapping ◽  
Hazard Mapping ◽  
Complex Nature ◽  
Susceptibility Map ◽  
Likelihood Ratios ◽  
Regular Feature ◽  
Inference System

Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensive loss of life and property in the district located at the foothills of Himalaya. Keeping in view the situation it is concluded that besides structural approaches the non-structural approaches such as hazard and risk assessment maps are effective tools to reduce the intensity of damage. A landslide susceptibility map is base for engineering geologists and geomorphologists. However, it is not easy to produce a reliable susceptibility map due to complex nature of landslides. Since 1980s, several mathematical models have been developed to map landslide susceptibility and hazard. Among various models this paper is discussing the effectiveness of fuzzy logic approach for landslide susceptibility mapping in District Mansehra, Pakistan. The factor maps were modified as landslide susceptibility and fuzzy membership functions were assessed for each class. Likelihood ratios are obtained for each class of contributing factors by considering the expert opinion. The fuzzy operators are applied to generate landslide susceptibility maps. According to this map, 17% of the study area is classified as high susceptibility, 32% as moderate susceptibility, 51% as low susceptibility and areas. From the results it is found that the fuzzy model can integrate effectively with various spatial data for landslide hazard mapping, suggestions in this study are hope to be helpful to improve the applications including interpretation, and integration phases in order to obtain an accurate decision supporting layer.

scholarly journals Relationships between landslides and land use changes in the Sanbagawa and Mikabu Belts, Shikoku, Japan

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Roxanne Lai ◽  
Takashi Oguchi
Keyword(s):  
Land Use ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Abandonment ◽  
Crystalline Schist ◽  
Agricultural Abandonment ◽  
Landslide Kinematics

<p><strong>Abstract.</strong> Changing land use is an increasingly important issue as human habits, behaviors, and needs change. There has been an increase in land and agricultural abandonment in some places of the world. In Japan, movement of the population from rural to urban areas have resulted in much land and agricultural abandonment. In 2016, a land ministry survey showed that 4.1 million hectares of land in Japan had unclear ownership, with farmland making up 16.9% of the total. As vegetation cover changes after land abandonment, this temporal and spatial effect may have important effects on geomorphic processes such as landslide susceptibility and landslide kinematics.</p><p>Here we track long-term land use changes over vegetated landslide areas of the Sanbagawa and Mikabu Belts of Shikoku Island, Japan. The Sanbagawa and Mikabu Belts are metamorphic belts that run across Southwest Japan, and are home to numerous large crystalline schist landslides, including the widely-studied slow but continuously moving Zentoku landslide. Villages and communities have been built on these landslide areas due to historical and cultural factors, as well as the fertility of the soil. Consequently, given the changing land uses including land abandonment in these landslide areas over time, we use long-term high-resolution land cover vegetation datasets to examine first the long-term land use changes, and then use statistical methods to explore their relationships with landslide susceptibility and kinematics. Mapping of spatial data and their analysis using GIS constitute a core part of the research. The results suggest interconnections between land use changes and land movement.</p>

scholarly journals Efficacy of using radar-derived factors in landslide susceptibility analysis: case study of Koslanda, Sri Lanka

2019 ◽  
Vol 19 (8) ◽  
pp. 1881-1893 ◽  
Author(s):  
Ahangama Kankanamge Rasika Nishamanie Ranasinghe ◽  
Ranmalee Bandara ◽  
Udeni Gnanapriya Anuruddha Puswewala ◽  
Thilantha Lakmal Dammalage
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Prediction Models ◽  
Low Cost ◽  
Information Value ◽  
Spatial Data Analysis ◽  
Optical Remote Sensing ◽  
Analytic Hierarchy ◽  
Technological Developments

Abstract. Through the recent technological developments of radar and optical remote sensing in (i) the areas of temporal, spectral, spatial, and global coverage; (ii) the availability of such images either at a low cost or free of charge; and (iii) the advancement of tools developed in image analysis techniques and GIS for spatial data analysis, there is a vast potential for landslide studies using remote sensing and GIS as tools. Hence, this study aimed to assess the efficacy of using radar-derived factors (RDFs) in identifying landslide susceptibility using the bivariate information value method (InfoVal method) and the multivariate multi-criteria decision analysis based on the analytic hierarchy process statistical analysis. Using identified landslide causative factors, four landslide prediction models – bivariate with and without RDFs as well as multivariate with and without RDFs – were generated. Twelve factors such as topographical, hydrological, geological, land cover and soil plus three RDFs are considered. The weight of index for landslide susceptibility is calculated by using the landslide failure map, and susceptibility regions are categorized into four classes as very low, low, moderate, and high susceptibility to landslides. With the integration of RDFs, boundary detection between high- and very-low-susceptibility regions are increased by 7 % and 4 % respectively.

scholarly journals Combined rock slope stability and shallow landslide susceptibility assessment of the Jasmund cliff area (Rügen Island, Germany)

2009 ◽  
Vol 9 (3) ◽  
pp. 687-698 ◽  
Author(s):  
A. Günther ◽  
C. Thiel
Keyword(s):  
Slope Stability ◽  
Landslide Susceptibility ◽  
Slope Failure ◽  
Rock Slope ◽  
Shallow Landslide ◽  
Material Strength ◽  
Spatial Integration ◽  
Inventory Data ◽  
Susceptibility Analysis ◽  
Susceptibility Model

Abstract. In this contribution we evaluated both the structurally-controlled failure susceptibility of the fractured Cretaceous chalk rocks and the topographically-controlled shallow landslide susceptibility of the overlying glacial sediments for the Jasmund cliff area on Rügen Island, Germany. We employed a combined methodology involving spatially distributed kinematical rock slope failure testing with tectonic fabric data, and both physically- and inventory-based shallow landslide susceptibility analysis. The rock slope failure susceptibility model identifies areas of recent cliff collapses, confirming its value in predicting the locations of future failures. The model reveals that toppling is the most important failure type in the Cretaceous chalk rocks of the area. The shallow landslide susceptibility analysis involves a physically-based slope stability evaluation which utilizes material strength and hydraulic conductivity data, and a bivariate landslide susceptibility analysis exploiting landslide inventory data and thematic information on ground conditioning factors. Both models show reasonable success rates when evaluated with the available inventory data, and an attempt was made to combine the individual models to prepare a map displaying both terrain instability and landslide susceptibility. This combination highlights unstable cliff portions lacking discrete landslide areas as well as cliff sections highly affected by past landslide events. Through a spatial integration of the rock slope failure susceptibility model with the combined shallow landslide assessment we produced a comprehensive landslide susceptibility map for the Jasmund cliff area.

scholarly journals Developing an Accessible Landslide Susceptibility Model Using Open-Source Resources

2018 ◽  
Vol 10 (2) ◽  
pp. 293 ◽  
Author(s):  
Kyungjin An ◽  
Suyeon Kim ◽  
Taebyeong Chae ◽  
Daeryong Park
Keyword(s):  
Open Source ◽  
Landslide Susceptibility ◽  
Susceptibility Model
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