Topic Editors

National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Dr. Yingying Tian
Institute of Geology, China Earthquake Administration, Beijing 100029, China
Dr. Xiaoyi Shao
Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China
National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
School of Civil Engineering and Architecture, Anhui University of Science and Technology, Huainan 232001, China

Database, Mechanism and Risk Assessment of Slope Geologic Hazards

Abstract submission deadline
30 November 2024
Manuscript submission deadline
28 February 2025
Viewed by
3418

Topic Information

Dear Colleagues,

The slope geo-disaster is a significant hazard in mountainous areas. With an extreme climate and tectonic events (i.e., rainfall, wildfire, earthquake, and snow or ice melting) becoming frequent, slope failures are becoming more and more common throughout the world. Landslides, debris flows, and avalanches are the three main sub-categories of slope instabilities. They cause serious casualties and economic loss by burying buildings and farmlands, blocking rivers, destroying roads and railways, and inducing fires. Thus, slope instability is the hot topic in earth science research. So far, the most effective way to explore the temporal and spatial distribution laws and cause mechanisms of slope failures has been based on disasters that have already happened. Though lots of related research has been published, it is necessary to keep our eyes on different kinds of slope failures in various places. This topic focuses on slope geo-disasters and collects articles on disaster detection and mapping, database compiling, cause mechanisms, susceptibility, and risk mapping. Topics of interest include, but are not limited to, the following:

  • New techniques to detect slope instability (including landslides, debris flows, and avalanches);
  • Database of slope instability hazards related to extreme events (e.g., rainfalls, earthquakes, or wildfires) or mountainous areas;
  • Characteristics and mechanisms of slope instabilities;
  • Numerical modeling and the whole life-circle analyses of large slope failure(s);
  • Susceptibility mapping and risk assessment of slope failures;
  • Post-failure evolution and prediction of slope geo-disasters temporally and spatially.

Prof. Dr. Chong Xu
Dr. Yingying Tian
Dr. Xiaoyi Shao
Dr. Zikang Xiao
Dr. Yulong Cui
Topic Editors

Keywords

  • slope geo-disaster
  • database
  • mechanism
  • susceptibility
  • risk
  • evolution
  • prediction
  • remote sensing
  • GIS
  • machine learning

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Big Data and Cognitive Computing
BDCC
3.7 4.9 2017 18.2 Days CHF 1800 Submit
Data
data
2.6 4.6 2016 22 Days CHF 1600 Submit
Environments
environments
3.7 5.9 2014 23.7 Days CHF 1800 Submit
Geosciences
geosciences
2.7 5.2 2011 23.6 Days CHF 1800 Submit
Remote Sensing
remotesensing
5.0 7.9 2009 23 Days CHF 2700 Submit

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Published Papers (3 papers)

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22 pages, 2093 KiB  
Article
Comparison of Rating Systems for Alberta Rock Slopes, and Assessment of Applicability for Geotechnical Asset Management
Geosciences 2023, 13(11), 348; https://doi.org/10.3390/geosciences13110348 - 14 Nov 2023
Viewed by 1219
Abstract
In 1999, Alberta Transportation and Economic Corridors (TEC) implemented the Geohazard Risk Management Program (GRMP) to identify, assess, monitor, and prioritize the mitigation of risk resulting from geohazard events at specific sites along the provincial highway network. The GRMP was developed to address [...] Read more.
In 1999, Alberta Transportation and Economic Corridors (TEC) implemented the Geohazard Risk Management Program (GRMP) to identify, assess, monitor, and prioritize the mitigation of risk resulting from geohazard events at specific sites along the provincial highway network. The GRMP was developed to address a variety of geohazard types including rockfall hazards that occur at natural and constructed (cut) highway backslopes. An evaluation of various methods for the condition assessment of rockfall geohazards, including TEC’s current GRMP risk rating system, has been completed with the intent of better understanding the suitability of each method as TEC transitions to a formalized GAM program. The GRMP risk rating values for selected rockfall geohazard sites along highway corridors in Alberta were compared to values developed from the results of five established rock mass and rock slope rating systems. The results of this study demonstrate that TEC’s current GRMP risk rating system is a viable tool for the condition assessment and performance monitoring of rockfall geohazards, which could be utilized within a formalized GAM program, further benefitting from years of recorded application in Alberta. Of the other rating systems tested, the rockfall hazard rating system (RHRS) showed a strong correlation with the GRMP risk rating while Q-Slope, the Geological Strength Index (GSI) and Rock Mass Rating (RMR) correlation were marginal but displayed a potential for use as condition assessment tools. The work presented in this paper provides the first evaluation of rock slope rating systems for rockfall hazards along corridors in Alberta, directly comparing them to the slope performance as observed by TEC in a quantitative manner. Full article
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21 pages, 15536 KiB  
Article
Analysis of the Controlling Effect of Excess Topography on the Distribution of Coseismic Landslides during the Iburi Earthquake, Japan, on 6 September 2018
Remote Sens. 2023, 15(20), 5035; https://doi.org/10.3390/rs15205035 - 20 Oct 2023
Viewed by 669
Abstract
Coseismic landslides cause changes in the hillside material, and this erosion process plays an important role in the evolution of the topography. Previous studies seldom involved research on the influence of excess topography on the occurrences of coseismic landslides. The Iburi earthquake, which [...] Read more.
Coseismic landslides cause changes in the hillside material, and this erosion process plays an important role in the evolution of the topography. Previous studies seldom involved research on the influence of excess topography on the occurrences of coseismic landslides. The Iburi earthquake, which occurred in Japan on 6 September 2018 and triggered a large number of landslides, provided a research example to explore the relationship between coseismic landslides and excess topography. We used the average slope of the lithology as the threshold slope of the corresponding stratum to calculate the excess topography of the different lithological units. Based on the advanced spaceborne thermal emission and reflection radiometer (ASTER) digital elevation model (DEM) with a resolution of 30 m, a quantitative analysis was conducted on the excess topography in the study area. The results indicate that the excess topography in the study area was mainly distributed in the valleys on both sides of the river, and the thickness of the excess topography on the high and steep ridges was generally greater than that at the foot of the slope, which has a relatively flat topography or a low elevation. In the area affected by the earthquake, approximately 94.66% of the coseismic landslides (with an area of approximately 28.23 m2) developed in the excess topography area, indicating that the distribution of the excess topography had a strong controlling influence on the spatial distribution of the coseismic landslides. The Iburi earthquake mainly induced shallow landslides, but the thickness of the landslide body was much smaller than the excess topography height in the landslides-affected area. This may imply that the excess topography was not completely removed by the coseismic landslides, and the areas where the earthquake landslides occurred still have the possibility of producing landslides in the future. Full article
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19 pages, 17130 KiB  
Article
Estimating the Quality of the Most Popular Machine Learning Algorithms for Landslide Susceptibility Mapping in 2018 Mw 7.5 Palu Earthquake
Remote Sens. 2023, 15(19), 4733; https://doi.org/10.3390/rs15194733 - 27 Sep 2023
Cited by 3 | Viewed by 757
Abstract
The Mw 7.5 Palu earthquake that occurred on 28 September 2018 (UTC 10:02) on Sulawesi Island, Indonesia, triggered approximately 15,600 landslides, causing about 4000 fatalities and widespread destruction. The primary objective of this study is to perform landslide susceptibility mapping (LSM) associated with [...] Read more.
The Mw 7.5 Palu earthquake that occurred on 28 September 2018 (UTC 10:02) on Sulawesi Island, Indonesia, triggered approximately 15,600 landslides, causing about 4000 fatalities and widespread destruction. The primary objective of this study is to perform landslide susceptibility mapping (LSM) associated with this event and assess the performance of the most widely used machine learning algorithms of logistic regression (LR) and random forest (RF). Eight controlling factors were considered, including elevation, hillslope gradient, aspect, relief, distance to rivers, peak ground velocity (PGV), peak ground acceleration (PGA), and lithology. To evaluate model uncertainty, training samples were randomly selected and used to establish the models 20 times, resulting in 20 susceptibility maps for different models. The quality of the landslide susceptibility maps was evaluated using several metrics, including the mean landslide susceptibility index (LSI), modelling uncertainty, and predictive accuracy. The results demonstrate that both models effectively capture the actual distribution of landslides, with areas exhibiting high LSI predominantly concentrated on both sides of the seismogenic fault. The RF model exhibits less sensitivity to changes in training samples, whereas the LR model displays significant variation in LSI with sample changes. Overall, both models demonstrate satisfactory performance; however, the RF model exhibits superior predictive capability compared to the LR model. Full article
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