Evaluation of landslide susceptibility of Sete Cidades Volcano (S. Miguel Island, Azores)

Abstract. Sete Cidades is an active central volcano with a summit caldera located in the westernmost part of S. Miguel Island (Azores). Since the settlement of the Island, in the 15th century, many landslide events occurred in this volcano, causing extensive damages in buildings and infrastructures. The study of historical records and the observation of new occurrences showed that landslides in the region have been triggered by heavy rainfall periods, earthquakes and erosion. In order to assess landslide susceptibility at Sete Cidades Volcano, landslide scars and associated deposits were mapped through aerial photographs and field surveys. The obtained data were inserted in a GIS to produce a landslide distribution map. It was concluded that the high density landslide areas are related with (1) major scarp faults, (2) the margin of fluvial channels, (3) the sea cliffs and (4) volcanic landforms, namely the caldera wall. About 73% of the mapped events took place in areas where pyroclastic deposits are the dominant lithology and more than 77% occurred where slopes are equal or higher than 20°. These two parameters were integrated and used to generate a preliminary susceptibility map. The incorporation of vulnerability data into the GIS allowed concluding that 30% of dwellings and most of the roads on Sete Cidades Volcano are located in areas where landslide susceptibility is high to very high. Such conclusion should be taken into account for emergency and land use planning.

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

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-020-01959-x ◽

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.

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Slope Stability Assessment and Landslide Susceptibility Map Production of Wadi Dhahr Area, Northwest of Sana’a, Yemen

Sultan Qaboos University Journal for Science [SQUJS] ◽

10.24200/squjs.vol23iss2pp120-136 ◽

2018 ◽

Vol 23 (2) ◽

pp. 120

Author(s):

Barahim Adnan A. ◽

Khanbari Khaled M. ◽

Algodami Amal F. ◽

Almadhaji Ziad A. ◽

Adris Ahmed M.

Keyword(s):

Slope Stability ◽

Land Use Planning ◽

Landslide Susceptibility ◽

Satellite Image ◽

Slope Angle ◽

Field Investigation ◽

Susceptibility Map ◽

Stability Assessment ◽

Landslide Susceptibility Map ◽

Modes Of Failure

A slope stability assessment of Wadi Dhahr area, located northwest of Sana’a the capital of Yemen, was carried out in this study. The study area consists of sandstone and volcanic rocks that are deformed by number of faults, joints and basaltic dykes. All the important factors affecting slope stability in the area such as slope angle, slope height, discontinuities measurements, weathering, vegetation cover, rainfall and previous landslides were evaluated. The study was conducted based on the integration of field investigation and satellite image processing. A landslide susceptibility map was produced with the Landslide Possibility Index (LP1) System, and the correlation values were computed between the factors measured and Landslide Possibility Index values. The fractures counted by satellite image were categorised according to their length and zones based on their concentrations. It was found that plain sliding and rockfall are the main modes of failure in the area, while rolling and toppling are rare. Some remedial measures are proposed to protect the slopes where it is needed, such as the removal of rock overhangs, unstable blocks and trees, and by supporting the toe of slopes and overhanging parts by retaining walls and erecting well sealed drainage conduits. The results will assist in slope management and land use planning in the area.

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Production of Landslide Susceptibility Map using Bayesian Probability Model

International Journal of 3-D Information Modeling ◽

10.4018/ij3dim.2015040102 ◽

2015 ◽

Vol 4 (2) ◽

pp. 16-33 ◽

Cited By ~ 1

Author(s):

Halil Akıncı ◽

Ayşe Yavuz Özalp ◽

Mehmet Özalp ◽

Sebahat Temuçin Kılıçer ◽

Cem Kılıçoğlu ◽

...

Keyword(s):

Land Use ◽

Land Use Planning ◽

Landslide Susceptibility ◽

Probability Model ◽

Bayesian Probability ◽

Slope Aspect ◽

Susceptibility Map ◽

Model Parameters ◽

Operating Characteristics ◽

Landslide Susceptibility Map

Artvin is one of the provinces in Turkey where landslides occur most frequently. There have been numerous landslides characterized as natural disaster recorded across the province. The areas sensitive to landslides across the province should be identified in order to ensure people's safety, to take the necessary measures for reducing any devastating effects of landslides and to make the right decisions in respect to land use planning. In this study, the landslide susceptibility map of the Central district of Artvin was produced by using Bayesian probability model. Parameters including lithology, altitude, slope, aspect, plan and profile curvatures, soil depth, topographic wetness index, land cover, and proximity to the road and stream were used in landslide susceptibility analysis. The landslide susceptibility map produced in this study was validated using the receiver operating characteristics (ROC) based on area under curve (AUC) analysis. In addition, control landslide locations were used to validate the results of the landslide susceptibility map and the validation analysis resulted in 94.30% accuracy, a reliable outcome for this map that can be useful for general land use planning in Artvin.

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Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models

Water ◽

10.3390/w11071402 ◽

2019 ◽

Vol 11 (7) ◽

pp. 1402 ◽

Cited By ~ 32

Author(s):

Nohani ◽

Moharrami ◽

Sharafi ◽

Khosravi ◽

Pradhan ◽

...

Keyword(s):

Land Use ◽

Landslide Susceptibility ◽

Vegetation Index ◽

Slope Angle ◽

Aerial Photographs ◽

Landslide Susceptibility Mapping ◽

Slope Aspect ◽

Susceptibility Map ◽

Conditioning Factors ◽

Bivariate Models

Landslides are the most frequent phenomenon in the northern part of Iran, which cause considerable financial and life damages every year. One of the most widely used approaches to reduce these damages is preparing a landslide susceptibility map (LSM) using suitable methods and selecting the proper conditioning factors. The current study is aimed at comparing four bivariate models, namely the frequency ratio (FR), Shannon entropy (SE), weights of evidence (WoE), and evidential belief function (EBF), for a LSM of Klijanrestagh Watershed, Iran. Firstly, 109 locations of landslides were obtained from field surveys and interpretation of aerial photographs. Then, the locations were categorized into two groups of 70% (74 locations) and 30% (35 locations), randomly, for modeling and validation processes, respectively. Then, 10 conditioning factors of slope aspect, curvature, elevation, distance from fault, lithology, normalized difference vegetation index (NDVI), distance from the river, distance from the road, the slope angle, and land use were determined to construct the spatial database. From the results of multicollinearity, it was concluded that no collinearity existed between the 10 considered conditioning factors in the occurrence of landslides. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used for validation of the four achieved LSMs. The AUC results introduced the success rates of 0.8, 0.86, 0.84, and 0.85 for EBF, WoE, SE, and FR, respectively. Also, they indicated that the rates of prediction were 0.84, 0.83, 0.82, and 0.79 for WoE, FR, SE, and EBF, respectively. Therefore, the WoE model, having the highest AUC, was the most accurate method among the four implemented methods in identifying the regions at risk of future landslides in the study area. The outcomes of this research are useful and essential for the government, planners, decision makers, researchers, and general land-use planners in the study area.

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Dormant and Active Landslides Classification Using Machine Learning Algorithms Coupled With Geological Field Inspection: Pohang Case Study

10.5194/egusphere-egu2020-6749 ◽

2020 ◽

Author(s):

Omar F. Althuwaynee ◽

In-Tak Hwang ◽

Hyuck-jin Park ◽

Swang-Wan Kim ◽

Ali Aydda

Keyword(s):

Machine Learning ◽

Landslide Susceptibility ◽

Field Work ◽

Google Earth ◽

Aerial Photographs ◽

Susceptibility Map ◽

Alluvial Deposits ◽

Basic Field ◽

Entire Study ◽

Extreme Gradient Boosting

<p>In 1998, intense rainfall events hit the Pohang state, south west of Korea, which results in highest number of landslides registered in this area (generally the area has a relatively short history of landslide inventorying). The current inventory was digitized using Aerial photographs (lack of photogeological stereoscopic analysis of the aerial images) and coupled with basic field verification (due to limit funding available). Leaving the applied susceptibility maps models performed, using this inventory, with high degree of uncertainty.&#160; Currently a research initiative carried to audit the landslide inventory using freely available aerial photographs and the time tuning function in Google earth for aerial archives. We notice some slopes area covered with deformed forest types that is similar in texture to that seen in digitized locations of landslides inventory. Due to long retune period of similar rainfall event, and with an assumption that the available landslides inventory might not complete. A certain hypothesis of additional investigation including field work to audit the landslides incidents is highly needed. In the current research, we assumed that, some dormant slopes caused by the 1998 event can be reactivated with the current extreme (uncontrolled) uses of slopes by human activities (constructions of real estate&#8217;s projects). To that end, a methodology of three main stages were proposed.</p><p>Stage one; Dormant susceptibility map (DSM) coupled with landslide susceptibility map will be produced. Machine learning supervised classification of eXtreme Gradient Boosting algorithms and Ensemble Random Forest, that run on tree-based classification assumption considering only active and dormant landslides as well as stable ground. Stage two; field work needs to be designed by geological and geotechnical experts to collect the doubtful locations by guidance of DSM and consider the new locations as dormant inventory. However, the areas of low dormant susceptibility (or mutual zones with Landslide susceptibility) will be recommended for advanced filed work and soil sampling test to complete the landslides identification of such highly urbanized area.&#160;Stage three; knowing the contour depths of diluvial and alluvial deposits can be useful for extracting areas that are more prone to landslides. Especially in the case of a rigid bedrock beneath the diluvial crust. Therefore, reconstructing the Quaternary formation thickness using boreholes repository and then represent the entire study area using CoKriging surface interpolation technique with elevation model. The current research results will provide us a better understanding of landcover stability conditions and their spatial prediction features.</p><div> <div>&#160;</div> <div>[email protected]</div> <div>[email protected]</div> </div>

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Using GIS & Multicriteria Decision analysis in landslide susceptibility mapping - a case study in Messinia prefecture area (SW Peloponnesus, Greece)

Bulletin of the Geological Society of Greece ◽

10.12681/bgsg.17240 ◽

2007 ◽

Vol 40 (4) ◽

pp. 1973 ◽

Cited By ~ 13

Author(s):

I. Ladas ◽

I. Fountoulis ◽

I. Mariolakos

Keyword(s):

Decision Analysis ◽

Land Use Planning ◽

Landslide Susceptibility ◽

Construction Projects ◽

Multicriteria Decision Analysis ◽

Combination Method ◽

Landslide Susceptibility Mapping ◽

Susceptibility Map ◽

Analytic Hierarchy ◽

Multicriteria Decision

The purpose of this study is to assess the susceptibility of landslides at the eastern part of Messinia prefecture using GIS and Multicriteria Decision Analysis. Analytic Hierarchy Process and Weighted Linear Combination method were used to create a landslide susceptibility map for the study area. The produced map provides valuable information concerning the stability conditions of the territory and may serve as the first step in a complete hazard assessment towards the mitigation of natural landslide disasters in Messinia Prefecture area. Particularly the intention is to transfer effectively information regarding slope stability to non-geologists who take decisions for future land use planning processes and major construction projects.

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Landslides density map of S. Miguel Island, Azores archipelago

Natural Hazards and Earth System Science ◽

10.5194/nhess-2-51-2002 ◽

2002 ◽

Vol 2 (1/2) ◽

pp. 51-56 ◽

Cited By ~ 17

Author(s):

P. Valadão ◽

J. L. Gaspar ◽

G. Queiroz ◽

T. Ferreira

Keyword(s):

Volcanic Eruptions ◽

Aerial Photographs ◽

Volcanic Complex ◽

Central Volcano ◽

Topographic Map ◽

Cinder Cones ◽

Azores Archipelago ◽

15Th Century ◽

Density Map ◽

Volcanic Islands

Abstract. The Azores archipelago is located in the Atlantic Ocean and is composed of nine volcanic islands. S. Miguel, the largest one, is formed by three active, E-W trending, trachytic central volcanoes with caldera (Sete Cidades, Fogo and Furnas). Chains of basaltic cinder cones link those major volcanic structures. An inactive trachytic central volcano (Povoação) and an old basaltic volcanic complex (Nordeste) comprise the easternmost part of the island. Since the settlement of the island early in the 15th century, several destructive landslides triggered by catastrophic rainfall episodes, earthquakes and volcanic eruptions occurred in different areas of S. Miguel. One unique event killed thousands of people in 1522. Houses and bridges were destroyed, roads were cut, communications, water and energy supply systems became frequently disrupted and areas of fertile land were often buried by mud. Based on (1) historical documents, (2) aerial photographs and (3) field observations, landslide sites were plotted on a topographic map, in order to establish a landslide density map for the island. Data obtained showed that landslide hazard is higher on (1) the main central volcanoes where the thickness of unconsolidated pyroclastic deposits is considerable high and (2) the old basaltic volcanic complex, marked by deep gullies developed on thick sequences of lava flows. In these areas, caldera walls, fault scarps, steep valley margins and sea cliffs are potentially hazardous.

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Application Of Logistic Regression Method To Produce Landslide Susceptibility Map: A Case Study Of Tetouan Mazari, Morocco

MATEC Web of Conferences ◽

10.1051/matecconf/201814902082 ◽

2018 ◽

Vol 149 ◽

pp. 02082

Author(s):

L. Ait Brahim ◽

M. Elmoulat

Keyword(s):

Logistic Regression ◽

Land Use Planning ◽

Landslide Susceptibility ◽

Accurate Method ◽

Slope Aspect ◽

Susceptibility Map ◽

Landslide Susceptibility Map ◽

Logistic Regression Method ◽

Validation Set

The main purpose of this study is to use logistic regression (RL) model to map landslide susceptibility in and around the area of Tetouan Mazari in the Northern Morocco. Parameters, such as lithology, slope gradient, slope aspect, faults, drainage lines, and hillshade, were considered. Landslide susceptibility map was produced using RL method and then compared and validated. Before the modeling and validation, the observed landslides were separated into two groups. The first group was for training, and the other group was for validation steps. The accuracy of the model was measured by fitting them to a validation set of observed landslides. For validation process, the half landslides remaining was used. The final map was classified into five classes: Very High (32%), High (40%), Medium (7%), Low (7%) and Nil (15%). According to these values logistic regression was determined to be one of the most accurate method to generate landslide susceptibility map. Last but not least, logistic regression model can be used to manage and mitigate hazards related to landslides and to aid in land-use planning for the city of Tetouan‥

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Landslide susceptibility mapping using fuzzy logic and multi-criteria evaluation techniques in the city of Quito, Ecuador

10.5194/nhess-2018-86 ◽

2018 ◽

Cited By ~ 1

Author(s):

Daniela Salcedo ◽

Oswaldo Padilla Almeida ◽

Byron Morales ◽

Theofilos Toulkeridis

Keyword(s):

Fuzzy Logic ◽

Landslide Susceptibility ◽

Field Work ◽

Aerial Photographs ◽

Landslide Susceptibility Mapping ◽

Susceptibility Map ◽

Map Algebra ◽

Causal Factors ◽

The City ◽

Evaluation Techniques

Abstract. Landslides are the most recurrent natural hazards in the Metropolitan District of Quito (DMQ), affecting sometimes lives but extremely frequently and severely the traffic and associated infrastructure. The present research proposes the calculation of the landslide susceptibility cartographic model in the city of Quito and its main highway, the Simón Bolívar avenue, using the Fuzzy logic and multicriteria evaluation techniques in geographic information systems (GIS). Based on the Today and the past son key to the future principle, landslides have been located using aerial photographs and field work. Based on the characteristics of historical landslides, photointerpreted and previous studies, the causal factors have been variable such as topography, structural geology, lithology, precipitation, water network, vegetation cover, among others. Each factor has been processed, analyzed and standardized according to its relationship to the occurrence of landslides, by means of a sinusoidal linked function that assigns to each element a degree of correlation [0, 1] to the diffuse set. The landslide vulnerability map has been obtained from the combination of causal factors by map algebra, such as weighting techniques that include the hierarchical analysis process (HAP) and the weighted linear line (WLL), whose validation considered the locations of inventoried landslides. According to the susceptibility map, 5 % of the direct study area has critical, 19 % high, 58 % average and 18 % low sensitivity. The quality of the results has been validated according to their standard error and adjustment value, being 0.216 and 78.4 %, respectively.

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LANDSLIDE SUSCEPTIBILITY MAPPING OF THE NORTHEASTERN PART OF ACHAIA PREFECTUREUSING ANALYTICAL HIERARCHICAL PROCESS AND GIS TECHNIQUES

Bulletin of the Geological Society of Greece ◽

10.12681/bgsg.11338 ◽

2017 ◽

Vol 43 (3) ◽

pp. 1637

Author(s):

D. Rozos ◽

D.G. Bathrellos ◽

D.H. Skilodimou

Keyword(s):

Land Use Planning ◽

Landslide Susceptibility ◽

Landslide Susceptibility Mapping ◽

Susceptibility Map ◽

Landslide Susceptibility Map ◽

Analytical Hierarchical Process ◽

Stability Of Slopes ◽

High Zone ◽

Integrated Technique ◽

The Individual

Landslides are one of the most frequent and disastrous natural hazards worldwide. Thus, the need of landslide susceptibility maps is of primary importance as they are both a useful tool for the land use planning and a necessary step for future development activities. This paper presents an integrated technique of analytical hierarchical process (AHP) and geographic information system (GIS) to create a landslide susceptibility map of the NE part of Achaia prefecture. The study area mainly consists of Neogene deposits and it is a part of the Corinthian graben, which characterized by intense neotectonic activity. Therefore, it is affected by many slope movements that usually cause serious damages in inhabitant areas and road networks. Based on field survey data analysis six parameters were chosen as major parameters that influence the stability of slopes to the direction of landslide manifestation. The AHP method identifies both the rate of the individual classes, and the weight of each factor. Spatial layers with their corresponding rates and weights were linearly combined to prepare the landslide susceptibility map, which includes four zones of slope movement’s susceptibility, namely a low, a moderate a high and a very high zone. The evaluation and final confirmation of the map was based on a great number of recorded landslides in the area.

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