Landslide risk assessment and management by decision analytical procedure for Dereköy, Konya, Turkey

The Dereköy landslide threatening the town of Dereköy, Konya, Turkey is investigated in order to assess and manage the associated risk. Dereköy town, located 12 km west of Konya city center, which is the second largest city in central Anatolia, has been extending due to the demand for new settlement places in Konya for the last decade. As most of the town is situated on the slopes of Meram river valley, on which the slope movements are observed, the risk of landslide has been increasing due to these new settlements. In this study, the landslide risk in Dereköy is assessed by following the so-called decision analytical procedure. The risk is defined by multiplication of hazard and consequences of the hazard. The hazard, which is the probability of slope failure, is computed by using the first-order second-moment (FOSM) method. The possible consequences of a landslide in Dereköy are analyzed and their costs are assessed relative to each other. A decision tree for choosing among the possible alternatives for reducing the risk is constructed in order to manage the risk.     

Application of electrical resistivity tomography technique for investigation of landslides: a case from Turkey

Electrical resistivity imaging is a widely used tool in near surface geophysical surveys for investigation of various geological, environmental and engineering problems including landslide. In this study, an electrical resistivity tomography (ERT) survey was conducted in a landslide area, located in the Söke district of Aydın, Turkey. In 2003, the Neogene-aged units on the slope next to a newly built school building became unstable due to an excavation work and moved after a heavy rainfall. The resulting landslide partly covered the school. The authors carried out a 2-D resistivity survey along three profiles over the landslide mass using a Wenner configuration. It yielded useful information about the geometry and characteristics of the landslide. In addition, a 2-D synthetic resistivity modelling study was carried out to understand the response of the resistivity method to a landslide problem before the field surveys. Eight boreholes were also drilled in the landslide area. Both the drilling and resistivity results indicated the presence of a fault in the site. Also, the resistivity data from the line measured along the axis of the landslide revealed the surface of rupture.     

Analytic network process model for landslide hazard zonation

Various controlling factors such as lithology, slope angle, slope aspect, landuse, channel proximity etc. are generally considered for the landslide hazard assessment. Although outer dependence of these parameters to a landslide is inevitably taken into account, inter-dependence among the factors is seldom addressed. Analytic Network Process (ANP) is the multi-criteria decision making (MCDM) tool which takes into account such a complex relationship among parameters. In this research, an ANP model for landslide susceptibility is proposed, priority weights for each parameter controlling the landslide were determined, and a hazard map was prepared of an area in a fragile mountainous terrain in the eastern part of Nepal. The data used in the example were derived from published sources, aerial photographs and a topographic map. However, the procedures developed can readily incorporate additional information from more detailed investigations.     

A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas

Landslides are one of the most destructive phenomena of nature that cause damage to both property and life every year, and therefore, landslide susceptibility zonation (LSZ) is necessary for planning future developmental activities. In this paper, apart from conventional weighting system, objective weight assignment procedures based on techniques such as artificial neural network (ANN), fuzzy set theory and combined neural and fuzzy set theory have been assessed for preparation of LSZ maps in a part of the Darjeeling Himalayas. Relevant thematic layers pertaining to the causative factors have been generated using remote sensing data, field surveys and Geographic Information System (GIS) tools. In conventional weighting system, weights and ratings to the causative factors and their categories are assigned based on the experience and knowledge of experts about the subject and the study area to prepare the LSZ map (designated here as Map I). In the context of objective weight assignments, initially the ANN as the black box approach has been used to directly produce an LSZ map (Map II). In this approach, however, the weights assigned are hidden to the analyst. Next, the fuzzy set theory has then been implemented to determine the membership values for each category of the thematic layer using the cosine amplitude method (similarity method). These memberships are used as ratings for each category of the thematic layer. Assuming weights of each thematic layer as one (or constant), these ratings of the categories are used for the generation of another LSZ map (Map III). Subsequently, a novel weight assignment procedure based on ANN is implemented to assign the weights to each thematic layer objectively. Finally, weights of each thematic layer are combined with fuzzy set derived ratings to produce another LSZ map (Map IV). The maps I–IV have been evaluated statistically based on field data of existing landslides. Amongst all the procedures, the LSZ map based on combined neural and fuzzy weighting (i.e., Map IV) has been found to be significantly better than others, as in this case only 2.3% of the total area is found to be categorized as very high susceptibility zone and contains 30.1% of the existing landslide area.     

Ground deformation monitoring by using the Permanent Scatterers Technique: The example of the Oltrepo Pavese (Lombardia, Italy)

The applicability of the Permanent Scatterers Synthetic Aperture Radar Interferometry (PSInSAR) technique for detecting and monitoring ground displacements was tested in the Oltrepo Pavese territory (Northern Italy, southern Lombardia), which could be representative of similar geological contexts in the Italian Apennines. The study area, which extends for almost 1100 km², is characterized by a complex geological and structural setting and the presence of clay-rich sedimentary formations. These characteristics make the Oltrepo Pavese particularly prone to several geological hazards: shallow and deep landslides, subsidence and swelling/shrinkage of the clayey soils. The PSInSAR technique used in this study overcomes most of the limitations of conventional interferometric approaches by identifying, within the area of interest, a set of “radar benchmarks” (PS), where very precise displacement measurements can be carried out. More than 90,000 PS were identified by processing Synthetic Aperture Radar (SAR) images acquired from 1992 to 2001 by the European Remote Sensing satellites (ERS). The PSInSAR application at a sub-regional scale detected slow ground deformations ranging from + 5 to − 16 mm/year, and resulting from various processes (landslides, swelling/shrinkage of clay soils and water pumping). The PS displacements were analysed by collecting data obtained through geological, geomorphologic field surveys, geotechnical analysis of the soils and the information was integrated within a landslide inventory and the damaged building inventory. Despite the limited number of landslide bodies with PS (7% of the inventoried landslides), the PS data helped to revise the state of activity of several landslides. Furthermore, some previously unknown unstable slopes were detected. Two areas of uplift and two areas of subsidence were identified.     

Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry

This paper is addressed to readers without advanced knowledge of remote sensing. It illustrates some current and potential uses of satellite Synthetic Aperture Radar interferometry (InSAR) for landslide assessment. Data acquired by SAR systems can provide 3D terrain models and be used to assist in regional scale investigations, e.g. aimed at evaluation of susceptibility of slopes to failure. Under favourable environmental conditions, the innovative Permanent Scatterers (PS) technique, which overcomes several limitations of conventional SAR differential interferometry (DInSAR) applications in landslide studies, is suitable for monitoring slope deformations with millimetric precision. The PS technique combines the wide-area coverage typical of satellite imagery with the capability of providing displacement data relative to individual image pixels. With the currently available radar satellites, however, only very slow ground surface displacements can be reliably detected and measured. The presented case study of a landslide from the Liechtenstein Alps indicates that the most attractive and reliable contribution provided by this remote sensing technique lies in the possibility of (i.) wide-area qualitative distinction between stable and unstable areas and (ii.) qualitative (relative) hazard zonation of large, slow landslides based on the identification of segments characterised by different movement rates. Since only the radar line of sight projection of the displacements can be detected, a quantitative exploitation of the PS data is possible only where sufficient ground truth is available. In site specific or single landslide investigations the PS data can represent a very useful complementary data source with respect to the information acquired through ground based observations and in situ surveying. However, the difficulties associated with the feasibility assessments of the applicability of SAR data to local scale problems, as well as with the interpretation of PS results, require a close collaboration between landslide experts and specialists in advanced processing of radar satellite data. The interpretation of the exact geotechnical significance of small, radar sensed ground surface deformations is challenging, especially where ground truth is lacking. Although any ground deformation is potentially of interest to an engineering geologist, detection of movements in both vertical and horizontal directions is needed in the case of landslides to evaluate slope failure mechanisms. With their high radar viewing angles, however, the current space-borne systems can detect only a fraction of the horizontal component of movement. It is expected that the upcoming SAR dedicated missions with new sensors and different acquisition geometries, combined with the rapid developments in the field of advanced radar data processing, will allow a full 3D reconstruction of deformation data and help to further reduce the current limitations of the PS and similar DInSAR approaches.     

Topographical changes revealed by high-resolution airborne LiDAR data: The 1999 Tsaoling landslide induced by the Chi–Chi earthquake

The 1999 Chi–Chi earthquake triggered the catastrophic Tsaoling landslide in central Taiwan. We mapped the landslide area and estimated the landslide volume, using a high-resolution digital elevation model from airborne LiDAR (Light Detection And Ranging), aerial photographs and topographic maps. The comparison between scar and deposit volumes, about 0.126 km³ and 0.150 km³ respectively, suggests a coseismic volume increase of 19% due to decompaction during landsliding. In July 2003, the scar and deposit volumes were about 0.125 km³ and 0.110 km³ respectively. These estimates suggest that 4 years after the event, the volume of landslide debris removed by river erosion was nearly 0.040 km³. These determinations are confirmed by direct comparison between the most accurate topographic models of the post-landslide period, indicating a very high erosion rate at the local scale (0.01 km³/year) for the deposit area of the landslide. Such a large value highlights the importance of landslide processes for erosion and long-term denudation in the Taiwan mountain belt.     

Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium)

In this article a statistical multivariate method, i.e., rare events logistic regression, is evaluated for the creation of a landslide susceptibility map in a 200 km² study area of the Flemish Ardennes (Belgium). The methodology is based on the hypothesis that future landslides will have the same causal factors as the landslides initiated in the past. The information on the past landslides comes from a landslide inventory map obtained by detailed field surveys and by the analysis of LIDAR (Light Detection and Ranging)-derived hillshade maps. Information on the causal factors (e.g., slope gradient, aspect, lithology, and soil drainage) was extracted from digital elevation models derived from LIDAR and from topographical, lithological and soil maps. In landslide-affected areas, however, we did not use the present-day hillslope gradient. In order to reflect the hillslope condition prior to landsliding, the pre-landslide hillslope was reconstructed and its gradient was used in the analysis. Because of their limited spatial occurrence, the landslides in the study area can be regarded as “rare events”. Rare events logistic regression differs from ordinary logistic regression because it takes into account the low proportion of 1s (landslides) to 0s (no landslides) in the study area by incorporating three correction measures: the endogenous stratified sampling of the dataset, the prior correction of the intercept and the correction of the probabilities to include the estimation uncertainty. For the study area, significant model results were obtained, with pre-landslide hillslope gradient and three different clayey lithologies being important predictor variables. Receiver Operating Characteristic (ROC) curves and the Kappa index were used to validate the model. Both show a good agreement between the observed and predicted values of the validation dataset. Based on a qualified judgement, the created landslide susceptibility map was classified into four classes, i.e., very high, high, moderate and low susceptibility. If interpreted correctly, this classified susceptibility map is an important tool for the delineation of zones where prevention measures are needed and human interference should be limited in order to avoid property damage due to landslides.     

The landslides and tsunamis of the 30th of December 2002 in Stromboli analysed through numerical simulations

On the 30th of December 2002 two tsunamis were generated only 7 min apart in Stromboli, southern Tyrrhenian Sea, Italy. They represented the peak of a volcanic crisis that started 2 days before with a large emission of lava flows from a lateral vent that opened some hundreds of meters below the summit craters. Both tsunamis were produced by landslides that detached from the Sciara del Fuoco. This is a morphological scar and is the result of the last collapse of the northwestern flank of the volcanic edifice, that occurred less than 5 ka b.p. The first tsunami was due to a submarine mass movement that started very close to the coastline and that involved about 20×10⁶ m³ of material. The second tsunami was engendered by a subaerial landslide that detached at about 500 m above sea level and that involved a volume estimated at 4–9×10⁶ m³. The latter landslide can be seen as the retrogressive continuation of the first failure. The tsunamis were not perceived as distinct events by most people. They attacked all the coasts of Stromboli within a few minutes and arrived at the neighbouring island of Panarea, 20 km SSW of Stromboli, in less than 5 min. The tsunamis caused severe damage at Stromboli.In this work, the two tsunamis are studied by means of numerical simulations that use two distinct models, one for the landslides and one for the water waves. The motion of the sliding bodies is computed by means of a Lagrangian approach that partitions the mass into a set of blocks: we use both one-dimensional and two-dimensional schemes. The landslide model calculates the instantaneous rate of the vertical displacement of the sea surface caused by the motion of the underwater slide. This is included in the governing equations of the tsunami, which are solved by means of a finite-element (FE) technique. The tsunami is computed on two different grids formed by triangular elements, one covering the near-field around Stromboli and the other also including the island of Panarea.The simulations show that the main tsunamigenic potential of the slides is restricted to the first tens of seconds of their motion when they interact with the shallow-water coastal area, and that it diminishes drastically in deep water. The simulations explain how the tsunamis that are generated in the Sciara del Fuoco area, are able to attack the entire coastline of Stromboli with larger effects on the northern coast than on the southern. Strong refraction and bending of the tsunami fronts is due to the large near-shore bathymetric gradient, which is also responsible for the trapping of the waves and for the persistence of the oscillations. Further, the first tsunami produces large waves and runup heights comparable with the observations. The simulated second tsunami is only slightly smaller, though it was induced by a mass that is approximately one third of the first. The arrival of the first tsunami is negative, in accordance with most eyewitness reports. Conversely, the leading wave of the second tsunami is positive.     

Simulation of the stratospheric ozone and temperature response to the solar irradiance variability during sun rotation cycle

Despite substantial progress in atmospheric modeling, the agreement of the simulated atmospheric response to decadal scale solar variability with the solar signal in different atmospheric quantities obtained from the statistical analysis of the observations cannot be qualified as successful. An alternative way to validate the simulated solar signal is to compare the sensitivity of the model to the solar irradiance variability on shorter time scales. To study atmospheric response to the 28-day solar rotation cycle, we used the chemistry–climate model SOCOL that represents the main physical–chemical processes in the atmosphere from the ground up to the mesopause. An ensemble simulation has been carried out, which is comprised of nine 1-year long runs, driven by the spectral solar irradiance prescribed on a daily basis using UARS SUSIM measurements for the year 1992. The correlation of zonal mean hydroxyl, ozone and temperature averaged over the tropics with solar irradiance time series have been analyzed. The hydroxyl has robust correlations with solar irradiance in the upper stratosphere and mesosphere, because the hydroxyl concentration is defined mostly by the photolysis. The simulated sensitivity of the hydroxyl to the solar irradiance changes is in good agreement with previous estimations. The ozone and temperature correlations are more complicated because their behavior depends on non-linear dynamics and transport in the atmosphere. The model simulates marginally significant ozone response to the solar irradiance variability during the Sun rotation cycle, but the simulated temperature response is not robust. The physical nature of this is not clear yet. It seems likely that the temperature (and partly the ozone) daily fields possess their own internal variability, which is not stable and can differ from year to year reflecting different dynamical states of the system.