Landslides in the Ethiopian highlands and the Rift margins

Bekele, Afework; Dramis, F.; Fubelli, Giandomenico; Umer, Mohammed; Asrat, Asfawossen

doi:10.1016/j.jafrearsci.2009.06.006

Cited by 81 publications

(48 citation statements)

References 25 publications

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“…However, taking into account that the main triggering factor of landslides on the rift margin is rainfall [19,21,55] we can suppose that the main movement of the Debre Sina landslide occurred in two phases after the rainy periods of 2005 and 2006. This agrees with the findings of [24] who carried out interviews with local inhabitants.…”

Section: Evolution Of the Slope Failurementioning

confidence: 99%

“…Slopes of the Ethiopian Highlands are frequently affected by landslides of various types, which often lead to eviction of inhabitants, damage to housing, infrastructure and arable land and even loss of human lives [19,20]. Most of the landslides in this region, including the largest ones, are triggered by heavy precipitation occurring at the end of the rainy periods in July and August [21], whereas earthquakes mainly trigger fast moving slope failures such as rock slides, topples and falls [19].…”

Section: Introductionmentioning

confidence: 99%

“…Most of the landslides in this region, including the largest ones, are triggered by heavy precipitation occurring at the end of the rainy periods in July and August [21], whereas earthquakes mainly trigger fast moving slope failures such as rock slides, topples and falls [19]. An extraordinarily large slope failure occurred in the Yizaba locality of the Tarmaber area north of the town of Debre Sina (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

et al. 2015

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Frequently occurring landslides in Ethiopia endanger rapidly expanding settlements and infrastructure. We investigated a large landslide on the western escarpment of the Main Ethiopian Rift close to Debre Sina. To understand the extent and amplitude of the movements, we derived vectors of horizontal displacements by feature matching of very high resolution satellite images (VHR). The major movements occurred in two phases, after the rainy seasons in 2005 and 2006 reaching magnitudes of 48˘10.1 m and 114˘7.2 m, respectively. The results for the first phase were supported by amplitude tracking using two Envisat/ASAR scenes from the 31 July 2004 and the 29 October 2005. Surface changes in vertical direction were analyzed by subtraction of a pre-event digital elevation model (DEM) from aerial photographs and post-event DEM from ALOS/PRISM triplet data. Furthermore, we derived elevation changes using satellite laser altimetry measurement acquired by the ICESat satellite. These analyses allowed us to delineate the main landslide, which covers an area of 6.5 km 2 , shallow landslides surrounding the main landslide body that increased the area to 8.5 km 2 , and the stable area in the lower part of the slope. We assume that the main triggering factor for such a large landslide was precipitation cumulated over several months and we suspect that the slope failure will progress towards the foot of the slope.

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Section: Evolution Of the Slope Failurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

et al. 2015

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“…Marjanovi c et al (2011) and San (2014) documented that SVM implicitly maps the original input areas into a high-dimensional feature space, using the training data-set. The optimal hyperplane in the feature space is determined by maximizing the boundaries (Abebe et al 2010;Pradhan 2013). Support vectors are defined as the training points that are closest to the optimal hyperplane.…”

Section: Support Vector Machine (Svm)mentioning

confidence: 99%

Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study)

Mahalingam

Olsen

O'Banion

2016

Geomatics, Natural Hazards and Risk

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Landslides are a significant geohazard, which frequently result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping using GIS and remote sensing can help communities prepare for these damaging events. Current mapping efforts utilize a wide variety of techniques and consider multiple factors. Unfortunately, each study is relatively independent of others in the applied technique and factors considered, resulting in inconsistencies. Further, input data quality often varies in terms of source, data collection, and generation, leading to uncertainty. This paper investigates if lidar-derived data-sets (slope, slope roughness, terrain roughness, stream power index, and compound topographic index) can be used for predictive mapping without other landslide conditioning factors. This paper also assesses the differences in landslide susceptibility mapping using several, widely used statistical techniques. Landslide susceptibility maps were produced from the aforementioned lidar-derived data-sets for a small study area in Oregon using six representative statistical techniques. Most notably, results show that only a few factors were necessary to produce satisfactory maps with high predictive capability (area under the curve >0.7). The sole use of lidar digital elevation models and their derivatives can be used for landslide mapping using most statistical techniques without requiring additional detailed data-sets that are often difficult to obtain or of lower quality.

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“…Mechanisms of the detachment include natural climate conditions, such as freezing-thawing [2], anthropogenic activities, such as blasting for slope excavation, seismic activities [3] and slow time-dependent deformation of the slope materials [4]. Not only does rockfall threaten the manmade environment, it also generates loss of human life and property within its influence area seriously because it behaves suddenly, frequently and randomly [5,6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Potential Rockfalls on a Highway at High Slopes in Cold-Arid Areas (Northwest Xinjiang, China)

Yang

Shang

et al. 2017

Sustainability

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Abstract:In the steep mountainous areas in northwest Xinjiang, where rock mass is broken seriously due to intense freeze thaw weathering, rockfall is one of the most common geological hazards on highway high slopes. Engineering geological investigations on geological hazards along a segment of the G219 highway was conducted, indicating that rockfalls on the high slopes threaten the safety of vehicles on the highway seriously. In this study, a combination of field investigations, laboratory experiments and numerical simulation methods was performed to identify unstable high slopes, simulate the rockfall trajectories and assess the rockfall hazard in the study area. The results show that there are five high slopes (i.e., W01, W02, . . . , W05) where rockfall hazard is extremely serious. Considering both the total kinetic energy and the accumulation rate of blocks, rockfall influence area zonation was performed, leading to the conclusions that the sections of highway on W01 to W05 are located at the medium-intensity low-accumulation zone, high-intensity medium-accumulation zone, high-intensity low-accumulation zone, high-intensity low-accumulation zone and medium-intensity high-accumulation zone, respectively. Based on the analysis, a zonation map was accomplished, which could help engineers select effective mitigation measures against rockfalls to avoid casualty and property losses.

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Landslides in the Ethiopian highlands and the Rift margins

Cited by 81 publications

References 25 publications

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study)

Analysis of Potential Rockfalls on a Highway at High Slopes in Cold-Arid Areas (Northwest Xinjiang, China)

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