Susceptibility assessment of landslides caused by the wenchuan earthquake using a logistic regression model

The Wenchuan earthquake on May 12, 2008 caused numerous collapses, landslides, barrier lakes, and debris flows. Landslide susceptibility mapping is important for evaluation of environmental capacity and also as a guide for post-earthquake reconstruction. In this paper, a logistic regression model was developed within the framework of GIS to map landslide susceptibility. Qingchuan County, a heavily affected area, was selected for the study. Distribution of landslides was prepared by interpretation of multi-temporal and multi-resolution remote sensing images (ADS40 aerial imagery, SPOT5 imagery and TM imagery, etc.) and field surveys. The Certainly Factor method was used to find the influencial factors, indicating that lithologic groups, distance from major faults, slope angle, profile curvature, and altitude are the dominant factors influencing landslides. The weight of each factor was determined using a binomial logistic regression model. Landslide susceptibility mapping was based on spatial overlay analysis and divided into five classes. Major faults have the most significant impact, and landslides will occur most likely in areas near the faults. Onethird of the area has a high or very high susceptibility, located in the northeast, south and southwest, including 65.3% of all landslides coincident with the earthquake. The susceptibility map can reveal the likelihood of future failures, and it will be useful for planners during the rebuilding process and for future zoning issues.     

Integrated rockfall hazard and risk assessment along highways: An example for Jiuzhaigou area after the 2017 Ms 7.0 Jiuzhaigou earthquake,China

This work addresses the integrated assessment of rockfall(including landslides) hazards and risk for S301, Z120, and Z128 highways, which are important transportation corridors to the world heritage site Jiuzhai Valley National Park in Sichuan, China. The highways are severely threatened by rockfalls or landslide events after the 2017 Ms 7.0 Jiuzhaigou earthquake. Field survey(September 14-18 th, 2017, May 15-20 th, 2018, and September 9-17 th, 2018), unmanned aerial vehicle(UAV), and satellite image identified high-relief rockfalls and road construction rockfalls or landslides along the highway. Rockfall hazard is qualitatively evaluated using block count, velocity, and flying height through a 3D rockfall simulation at local and regional scales. Rockfall risk is quantitatively assessed with rockfall event probability, propagation probability, spatial probability, and vulnerability for different block volume classes. Approximately 21.5%, 20.5%, and 5.3% of the road mileage was found to be subject to an unacceptable(UA) risk class for vehicles along S301, Z120, and Z128 highways, respectively. Approximately 20.1% and 3.3% of the road mileage belong to the UA risk class for tourists along Z120 and Z128 highways, respectively. Results highlighted that high-relief rockfall events were intensively located at K50 to K55(Guanmenzi to Ganheba) and K70 to K72(Jiudaoguai to Shangsizhai Village) road mileages along S301 highway and KZ18 to KZ22(Five Flower Lake to Arrow Bamboo Lake) road mileages, KZ30(Swan Lake to Virgin Forests), and KY10.5 kilometers in Jiuzhai Valley. Rockfalls in these locations were classified under the UA risk class and medium to very high hazard index. Road construction rockfalls were located at K67(Jiuzhai Paradise) and K75–K76 kilometers along S301 highway and KZ12 to KZ14(Rhino Lake to Nuorilang Waterfall), KZ16.5 to KZ17.5(Golden Bell Lake), KY5(Lower Seasonal Lake), and KY14(Upper Seasonal Lake) kilometers along Z120 and Z128 highway in Jiuzhai Valley. Rockfalls in these areas were within a reasonable practicable risk to UA risk class and very low to medium hazard index. Finally, defensive measures, including flexible nets, concrete walls, and artificial tunnels, could be selected appropriately on the basis of the rockfall hazard index and risk class. This study revealed the integration between qualitative rockfall hazard assessment and quantitative rockfall risk assessment, which is crucial in studying rockfall prevention and mitigation.     

Characterization and spatial analysis of coseismic landslides triggered by the Luding Ms 6.8 earthquake in the Xianshuihe fault zone,Southwest China

On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km². The coseismic landslides primarily consisted of medium and small-sized landsli...     

Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed,Gansu Province,China

Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups, (i) training dataset and (ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages, distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.     

Uncertainty analysis on zonation maps of debris flow hazard in Yunnan Province, China

lINTRODUCTIONDebrisflowisoneofthesixprimarynaturalhaz-ards,whichinfluencesthedevelopmentofnationalso-cietyandeconomyinChina.Itsseverityissecondarytoflood,draught,earthquake,typhoon,butstrongerthanbiologicalhazards.Morethan3ooOodebrisflowcreeksarescatteredihthewholemountainousarea,andes-PeciallyconcentratedinsouthwestofChina.DebrisFlowInformationSystem(DFIS)operatedbytheInsti-tuteofMountainHazardsandEnvironmentoftheChi-neseAcademyofScienceshasalreadyestablishedadatabaseandcataloguec…     

Distribution patterns of landslides triggered by the 2022 MS 6.8 Luding earthquake,Sichuan, China

At 12:52 pm on September 5, 2022, an MS 6.8 earthquake occurred in Luding County, Sichuan Province, China. Based on high-resolution aerial photographs and satellite imageries obtained after the earthquake, as well as field investigation, a total of 8685 earthquake-triggered landslides(EQTLs) were interpreted. The landslides covered an area of 30.7km2, with a source area of 9.4 km2. These EQTLs were mainly distributed in areas with a seismic intensity of VIII and IX. Most of the landslides were s...     

Tectonic mechanism of the Suining (Ms5.0) earthquake, center of Sichuan Basin, China

On Jan.31 of 2010,the Suining earthquake occurred at Suining City whch is located the center of Sichuan Basin.It is unusual for the strong earthquake to occur at the center of Sichuan Basin with a stable geotectonic environment and a low-level historical seismicity.The macro-epicenter of the earthquake is located at Moxi town of Suining city,Sichuan province,China.The earthquake intensity of the epicenter area is degree VII,and the long axis of the isoseismal line trends in NE orientation.The Suining earthquake caused the collapse or destruction of 460 family houses.The earthquake focal mechanism solution and records of the near-field seismographic stations showed the earthquake occurred at the reverse fault at a depth 34 km.Based on the waveform and focal mechanism,we consider the Suning earthquake is triggered by the reverse fault and not by the gravitational collapse or man-made explosive sources.Basing on seismic refraction profile and borehole,we consider that the earthquake is triggered by the backthrust fault of Moxi anticline rooted in detachments at a depth 3-4 km.Furthermore,we infer that tectonic mechanism of the Suining(Ms5.0) Earthquake is driven by the horizontal crustal shortening and stress adjustment on a shallow detachment after the Wenchuan(Ms 8.0) earthquake.     

Activity evolution of landslides and debris flows after the Wenchuan earthquake in the Qipan catchment,Southwest China

The Wenchuan earthquake that occurred on 12 May 2008 induced numerous landslides. Loose landslide materials were deposited on hillslopes, and deep channels were easily remobilized and transformed into debris flows by extreme rainstorms. Twelve years after the Wenchuan earthquake, debris flows were still active in the Qipangou Ravine in the quake-hit area. In this paper, we continuously tracked the spatiotemporal evolution of the landslides and vegetation restoration and evaluated the evolution of debris flow activity in the Qipan catchment with the aid of a GIS platform and field investigations from 2008 to 2019. We observed that the area with active landslides increased sharply immediately following the earthquake, and then decreased with time; however, the total area of landslides continued to increase from 6.93 km2 in 2008 to 10.55 km2 in 2019. The active landslides shifted towards lower angles and higher elevations after 2013. Since 2009, the vegetation coverage has been gradually increasing and approaching the coverage present before the earthquake as of 2019. The landslide activity was high and the vegetation recovery rates were rapidly rising during the first five years after the earthquake; the recovery rates then slowed over time. Therefore, we divided the evolution that occurred during the post landslide period into an active period(2008-2013), a self-adjustment period(2013-2026) and a stable period(after 2026). We then proposed a quantitative model to determine the trends of landslide activity rates and NDVI values in the catchment, which indicated that the landslide activities and postseismic vegetation restoration rates in this catchment will return to preseismic levels within approximately two decades. We also analysed the runout volumes of the debris flows after the earthquakes(Diexi and Wenchuan) and the standard deviation of the vegetation coverage and predicted that the debris flow activities will last for an additional 50 years or more.     

A potential flood hazard caused by Tianchi volcano eruption in Changbai Mountain, Northeast China

Geohazards appear to be increasing in frequency globally. it is of necessity to actively manage these natural hazards to minimize loss of life and property. from an early warning perspective, this paper stresses the potential fatal flood hazard represented by the huge volume of water in tianchi lake, the unique geography of changbai mountain, and the limited flood control ability in the upstream of the songhua river. northeast asian countries should keep a watchful eye on the changbai volcano cooperatively, and chinese government especially needs to prepare plans for fighting a flood in advance.     

Two-dimensional numerical model for debris flows in the Jiangjia Gully, Yunnan Province

Debris flows are recurrent natural hazards in many mountainous regions.This paper presents a numerical study on the propagation of debris flows in natural erodible open channels,in which the bed erosion and sedimentation processes are important.Based on the Bingham fluid theory,a mathematical model of the two-dimensional non-constant debris flow is developed.The governing equations include the continuity and momentum conservation equations of debris flow,the sediment convection-diffusion equation,the bed erosion-deposition equation and the bed-sediment size gradation adjustment equation.The yield stress and shear stress components are included to describe the dynamic rheological properties.The upwind control-volume Finite Volume Method (FVM) is applied to discretize the convection terms.The improved SIMPLE algorithm with velocity-free-surface coupled correction is developed to solve the equations on non-orthogonal,quadrilateral grids.The model is applied to simulate a debris flow event in Jiangjia Gully,Yunnan Province and to predict the flow pattern and bed erosion-deposition processes.The results show the effectiveness of the proposed numercial model in debris flow simulation and potential hazard analysis.     

A township-level assessment of forest fragmentation using morphological spatial pattern analysis in Qujing,Yunnan Province,China

Forest fragmentation is an integral part of global change.Understanding forest fragmentation patterns and dynamics are of great significance for maintaining eco...     

Identifying the spatiotemporal characteristics of individual red bed landslides: a case study in Western Yunnan,China

Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach co...     

Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas.The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability.Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone,with similar topographical and geological conditions.The two earthquakes are both featured by thrust fault and similar seismic mechanism.This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake.Six influencing parameters were taken into consideration: distance from the seismic fault,slope gradient,lithology,distance from drainage,elevation and Peak Ground Acceleration(PGA).The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan,Baoxing and Tianquan counties.The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work.The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area.The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.     

Empirical-statistical models based on remote sensing for estimating the volume of landslides induced by the Wenchuan earthquake

The Wenchuan Ms 8.0 earthquake on May 12, 2008 induced a huge number of landslides. The distribution and volume of the landslides are very important for assessing risks and understanding the landslide - debris flow - barrier lake - bursts flood disaster chain. The number and the area of landslides in a wide region can be easily obtained by remote sensing technique, while the volume is relatively difficult to obtain because it requires some detailed geometric information of slope failure surface and sub-surface. Different empirical models for estimating landslide volume were discussed based on the data of 107 landslides in the earthquake-stricken area. The volume data of these landslides were collected by field survey. Their areas were obtained by interpreting remote sensing images while their apparent friction coefficients and height were extracted from the images unifying DEM (digital elevation model). By analyzing the relationships between the volume and the area, apparent friction coefficients, and the height, two models were established, one for the adaptation of a magnitude scale landslide events in a wide range of region, another for the adaptation in a small scope. The correlation coefficients (R2) are 0.7977 and 0.8913, respectively. The results estimated by the two models agree well with the measurement data.     

Alpine Ecosystems of Northwest Yunnan, China： an Initial Assessment for Conservation

Implementing conservation actions on-the-ground is not a straightforward process,especially when faced with high scientific uncertainty due to limited available information. This is especially acute in regions of the world that harbor many unique species that have not been well studied,such as the alpine zone of the Hengduan Mountains of Northwest Yunnan (NWY),a global biodiversity hotspot and site of The Nature Conservancy’s Yunnan Great Rivers Project. We conducted a quantitative,but rapid regional-level assessment of the alpine flora across NWY to provide a broad-based understanding of local and regional patterns of the alpine flora,the first large-scale analysis of alpine biodiversity patterns in this region. Multivariate analyses were used to classify the major plant community types and link community patterns to habitat variables. Our analysis indicated that most species had small distributions and/or small population sizes. Strong patterns emerged with higher diversity in the more northern mountains,but beta diversity was high,averaging only 10% among sites. The ordinations indicated that elevation and geographic location were the dominant environ-mental gradients underlying the differences in the species composition among communities. The high beta diversity across the alpine of these mountains implies that conservation strategies ultimately will require the protection of large numbers of species over a large geographical area. However,prioritiza-tion should be given to areas where potential payoffs are greatest. Sites with high species richness also have a greater number of endemic species,and,by focusing efforts on these sites,conservation investments would be maximized by protecting the greatest number of unique species.     

确定性系数与随机森林模型在云南芒市滑坡易发性评价中的应用

编制科学的滑坡易发性分区图,可以有效降低灾害带来的损失。以云南省芒市为研究区,利用确定性系数模型（certainty factor,简称CF）方法计算各个因子的敏感值,作为随机森林（random forests,简称RF）的分类数据,选取合适的训练数据和最优化的模型参数进行模型预测,从而对研究区进行滑坡易发性评价分区。采用频率比方法将连续性因子离散化,从而通过确定性系数计算因子不同区间的滑坡易发性,同时利用CF先验模型,对研究区负样本进行选取。通过计算袋外误差得到最优化的RF参数,随后利用RF模型对研究区模型进行训练及预测。绘制ROC曲线和三维遥感影像对预测模型结果分别进行定量和定性评价,结果表明,所得到的模型精度为91%,优于随机抽样得到的结果。最后,采用平均基尼不纯度减少和平均准确度下降两种计算方法计算、评价了研究区各个因子的重要性。基于以上对研究区进行的滑坡易发性评价结果,可以为该区灾害风险评估和管理提供依据。      

Investigation and Assessment of Landslides and Debris Flows in Sichuan Province of China by Remote Sensing Technique

Taking TM images, ETM images, SPOT images, aerial photos and other remote sensing data as fundamental sources, this research makes a thorough investigation on landslides and debris flows in Sichuan Province, China, using the method of manual interpretation and taking topography maps as references after the processes of terrain correction, spectral matching, and image mosaic. And then, the spatial characteristics of landslides and debris flows in the year of 2005 are assessed and made into figures. The environmental factors which induce landslides and debris flows such as slope, vegetation coverage, lithology, rainfall and so on are obtained by GIS spatial analysis method. Finally, the relationships of landslides or debris flows with some environmental factors are analyzed based on the grade of each environmental factor. The results indicate： 1） The landslides and debris flows are mainly in the eastern and southern area of Sichuan Province, however, there are few landslides and debris flows in the western particularly the northwestern Sichuan. 2） The landslides and debris flows of Sichuan Province are mostly located in the regions with small slope degree. The occurring rate of debris flow reduces with the increase of the vegetation coverage degree, but the vegetation coverage degree has little to do with the occurrence of landslide. The more rainfall a place has, the easier the landslides and debris flows take place.     

The catastrophe forecast of the annual sidement transport by debris flow in Jiangjia Gully,Yunnan Province,China

On the basis of the observational data on the annual sediment transport by debris flow in recent 8 years, appling the catastrophe forecast method of Grey System Theory, this study has established the catastrophe model of the annual sediment transport by debris flow in Jiangjia Gully. It has forecasted the next potential catastrophic year in which the annual sediment transport will be over the catastrophic. threshold 2 million m3. Furthermore, it has introduced the "equal dimension-new information model", which makes the forecast be done continuously.     

Optimization of causative factors using logistic regression and artificial neural network models for landslide susceptibility assessment in Ujung Loe Watershed,South Sulawesi Indonesia

Landslide susceptibility maps(LSMs) play a vital role in assisting land use planning and risk mitigation. This study aims to optimize causative factors using logistic regression(LR) and an artificial neural network(ANN) to produce a LSM. The LSM is produced with 11 causative factors and then optimized using forward-stepwise LR(FSLR), ANN, and their combination(FSLR-ANN) until eight causative factors were found for each method. The ANN method produced superior validation results compared with LR. The ROC values for the training data set ranges between 0.8 and 0.9. On the other hand, validation with the percentage of landslide fall into LSM class high and very high, ANN method was higher(92.59%) than LR(82.12%). FSLR-ANN with nine causative factors gave the best validation results with respect to area under curve(AUC) values, and validation with the percentage of landslide fall into LSM class high and very high. In conclusion, ANN was found to be better than LR when producing LSMs. The best Optimization was combination of FSLR-ANN with nine causative factors and AUC success rate 0.847, predictive rate 0.844 and validation with landslide fall into high and very high class with 91.30%. It is an encouraging preliminary model towards a systematic introduction of FSLR-ANN model for optimization causative factors in landslide susceptibility assessment in the mountainous area of Ujung Loe Watershed.     

Size and spatial distribution of landslides induced by the 2015 Gorkha earthquake in the Bhote Koshi river watershed

The Mw 7.8 Gorkha earthquake in Nepal on April 25, 2015, produced thousands of landslides in the Himalayan mountain range. After the earthquake, two field investigations along Araniko Highway were conducted. Then, using remote sensing technology and geographic information system(GIS)technology, 1481 landslides were identified along the Bhote Koshi river. Correlations between the spatial distribution of landslides with slope gradient and lithology were analyzed. The power-law relationship of the size distribution of earthquake-induced landslides was examined in both the Higher Himalaya and Lesser Himalaya. Possible reasons for the variability of the power exponent were explored by examining differences in the geological situations of these areas. Multi-threshold cellular automata were introduced to model the complexity of system components. Most of the landslides occurred at slope gradients of 30°–40°, and the landslide density was positively correlated with slope gradient. Landslides in hard rock areas were more common than in soft rock areas. The cumulative number-area distribution of landslides induced by the Gorkha earthquake exhibited a negative power-law relationship, but the power exponents were different: 1.13 in the Higher Himalaya, 1.36 and Lesser Himalaya. Furthermore,the geological conditions were more complex and varied in the Lesser Himalaya than in the Higher Himalaya, and the cellular automata simulation results indicated that, as the complexity of system components increased, the power exponent increased.Therefore, the variability of the power exponent of landslide size distribution should ascribe to the complexity of geological situations in the Bhote Koshi river watershed.