Journal articles on the topic 'Risk analysis of landslides'
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1
Han, Meng, Xiao Yi Fan, and Jian Ping Qiao. "Background Factors Analysis and Risk Evaluation Based on Fuzzy Theory in Wenchuan Seismic Landslides." Applied Mechanics and Materials 204-208 (October 2012): 2698–704. http://dx.doi.org/10.4028/www.scientific.net/amm.204-208.2698.
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Earthquake is one of the most important external factors causes landslide, the geological and topographical conditions of the slope itself is the most important internal factors which induce landslide on landslide’s size and probability. These factors can be described as background factors impact the seismic landslides. Through the analysis and statistics on seismic landslides’ data in this paper, five directions were studied. These are lithology, slope height, slope angel, slope shape and slope direction. The influence features on number, area and volume of the five background factors show the contribution rate and risk degree. Using fuzzy theory to carry out quantitative and semi-quantitative analysis on these factors, the weights of the five background factors can be determined. Then using the risk evaluation on a specific landslide according to the principle of maximum membership, the result shows this method is reasonable.
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Salvati, P., C. Bianchi, F. Fiorucci, P. Giostrella, I. Marchesini, and F. Guzzetti. "Perception of flood and landslide risk in Italy: a preliminary analysis." Natural Hazards and Earth System Sciences Discussions 2, no. 5 (May 15, 2014): 3465–97. http://dx.doi.org/10.5194/nhessd-2-3465-2014.
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Abstract. Inundations and landslides are widespread phenomena in Italy, where they cause severe damage and pose a threat to the population. Little is known on the perception of the population of landslides and floods. This is surprising, as an accurate perception is important for the successful implementation of many risk reduction or adaptation strategies. In an attempt to fill this gap, we have conducted two national surveys to measure the perception of landslide and flood risk of the population of Italy. The surveys were executed in 2012 and 2013, performing for each survey approximately 3100 computer assisted telephone interviews. The samples of the interviewees were statistically representative for a national scale quantitative assessment. The interviewees were asked questions designed to obtain information on their: (i) perception of natural, environmental, and technological risks, (ii) direct experience or general knowledge on the occurrence of landslides and floods in their municipality, (iii) perception of the possible threat posed by landslides and floods to their safety, (iv) general knowledge on the number of victims caused by landslides or floods, and on (v) the factors that they considered important to control landslide and flood risks in Italy. The surveys revealed that the population of Italy fears technological risks more than natural risks. Of the natural risks, earthquakes were considered more dangerous than floods, landslides, and volcanic eruptions. Examination of the temporal and geographical distribution of the responses revealed that the occurrence of recent damaging events influenced risk perception locally, and that the perception persisted longer for earthquakes and decreased more rapidly for landslides and floods. We justify the differentiation with the diverse consequences of the risks. The interviewees considered inappropriate land management the main cause of landslide and flood risk, followed by illegal construction, abandonment of the territory, and climate change. Comparison of the risk perception with actual measures of landslide and flood risk, including the number of fatal events, the number of fatalities, and the mortality rates, revealed that in most of the Italian regions the perception of the threat did not match the long-term risk posed by landslides and floods to the population. This outcome points to the need to fostering the understanding of the population of landslide and flood hazards and risks in Italy.
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Salvati, P., C. Bianchi, F. Fiorucci, P. Giostrella, I. Marchesini, and F. Guzzetti. "Perception of flood and landslide risk in Italy: a preliminary analysis." Natural Hazards and Earth System Sciences 14, no. 9 (September 29, 2014): 2589–603. http://dx.doi.org/10.5194/nhess-14-2589-2014.
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Abstract. Inundations and landslides are widespread phenomena in Italy, where they cause severe damage and pose a threat to the population. Little is known about the public perception of landslide and flood risk. This is surprising, as an accurate perception is important for the successful implementation of many risk reduction or adaptation strategies. In an attempt to address this gap, we have conducted two national surveys to measure the perception of landslide and flood risk amongst the population of Italy. The surveys were conducted in 2012 and 2013, and consisted of approximately 3100 computer-assisted telephone interviews for each survey. The samples of the interviewees were statistically representative for a national-scale quantitative assessment. The interviewees were asked questions designed to obtain information on (i) their perception of natural, environmental, and technological risks, (ii) direct experience or general knowledge of the occurrence of landslides and floods in their municipality, (iii) perception of the possible threat posed by landslides and floods to their safety, (iv) general knowledge on the number of victims affected by landslides or floods, and on (v) the factors that the interviewees considered important for controlling landslide and flood risks in Italy. The surveys revealed that the population of Italy fears technological risks more than natural risks. Of the natural risks, earthquakes were considered more dangerous than floods, landslides, and volcanic eruptions. Examination of the temporal and geographical distributions of the responses revealed that the occurrence of recent damaging events influenced risk perception locally, and that the perception persisted longer for earthquakes and decreased more rapidly for landslides and floods. We explain the difference by the diverse consequences of the risks. The interviewees considered inappropriate land management the main cause of landslide and food risk, followed by illegal construction, abandonment of the territory, and climate change. Comparison of the risk perception with actual measures of landslide and flood risk, including the number of fatal events, the number of fatalities, and the mortality rates, revealed that in most of the Italian regions, the perception of the threat did not match the long-term risk posed to the population by landslides and floods. This outcome points to a need to foster an understanding of the public towards landslide and flood hazards and risks in Italy.
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Dai, Huayan, Hong Zhang, Huayang Dai, Chao Wang, Wei Tang, Lichuan Zou, and Yixian Tang. "Landslide Identification and Gradation Method Based on Statistical Analysis and Spatial Cluster Analysis." Remote Sensing 14, no. 18 (September 9, 2022): 4504. http://dx.doi.org/10.3390/rs14184504.
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As a type of earth observation technology, interferometric synthetic aperture radar (InSAR) is increasingly widely used in the field of geological disaster detection. However, the application of InSAR in low-coherence areas, such as alpine canyon areas and vegetation coverage areas, is subject to considerable limitations. How to accurately identify landslides from InSAR measurement data in these areas remains the subject of several challenges and shortcomings. Based on statistical analysis and spatial cluster analysis, in this paper, we propose an automatic landslide identification and gradation method suitable for low-coherence areas. The proposed method combines the small baseline subset InSAR (SBAS-InSAR) method and the interferogram stacking (stacking-InSAR) method to obtain a deformation map in the study area, using statistical analysis and spatial cluster analysis to extract deformation regions and landslide polygons to propose a landslide screening model (LSM) based on multivariate features to screen landslides and reduce the interference of noise in landslide identification, in addition to proposing a landslide gradation model (LGM) based on signum function to grade the identified landslides and provide support to distinguish landslides with different deformation degrees. The method was applied to landslide identification in the upper section of the Jinsha River basin, and 47 potential landslides were identified, including 15 high-risk landslides and 13 landslides endangering villages. The experimental results show that the proposed method can identify landslides accurately and hierarchically in low-coherence areas, providing support for geological hazard investigation agencies and local departments.
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Kahar, Muhammad Afiq Abdul, Hamzah Hussin, Nadia Ramli, and Muhammad Fahmi Abdul Ghani. "Landslide Analysis Approaches in Tropical Environment Region for Disaster Risk Reduction." IOP Conference Series: Earth and Environmental Science 1102, no. 1 (November 1, 2022): 012025. http://dx.doi.org/10.1088/1755-1315/1102/1/012025.
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Landslides are natural disasters that befall practically in almost every country worldwide. Since the behaviour of the Earth is varied and the influencing factors that induce landslides are not constant, there seems to be no precise technique for assessing and forecasting the occurrence of landslides. This study selected the Cameron Highlands district, situated in Pahang, Malaysia, which accentuates reviewing numerous methods by the preceding local researcher to analyse and assess landslide incidence. A country like Malaysia is highly vulnerable to landslides due to its geographical features of high and lowlands, relatively intense precipitation, and locality in the distribution of tropical rain forests typified by dense vegetation, hot and humid temperatures throughout the year. In comprehending the landslide, most prior researchers employed numerous approaches and methods, where three qualitative methods (acceptable accuracy), two semi-quantitative methods (78% to 86% accuracy) and five quantitative methods (86% to 98% accuracy) were identified. These methods appraise multiple parameters and employ various techniques for factor research and understanding, where each method has its own set of benefits and shortcomings. The diversity of the landslide scale requires specific research in determining landslide mapping, whether by inventory, susceptibility, hazard, or risk. An application of the programme and software platform can forecast the accuracy of landslide occurrence modelling for future landslide mitigation planning. Based on the review findings, GIS and remote sensing play a crucial part in translating spatial data for more accessible analysis in furthering the research, as supported by field survey results. Each method comprising various techniques indicates that overall accuracy is applicable for the landslide analysis approaches.
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Nai, Wang, Lan Min Wang, Zhong Xia Yuan, and Wang Qian. "Characteristic and Stability Analysis for Loess Seismic Landslide in Valley City." Advanced Materials Research 594-597 (November 2012): 1856–63. http://dx.doi.org/10.4028/www.scientific.net/amr.594-597.1856.
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In the light of heavy seismic landslide disasters in the valley city of loess area, 104 typical loess landslides caused by the 1654 Tianshui(Ms 8.0), 1718 Tongwei(Ms 7.5) and 1920 Haiyuan(Ms 8.5) earthquakes were studied, main landslide type and basic characteristics of seismic landslide in the valley city were analyzed. The landslides in the valley city of loess area are divided into three types: homogeneous loess landslide, loess interface landslide and loess-mudstone cutting layer landslide. Through the investigation and analysis of earthquake risk, the suggestion about the 22 dangerous landslides in Tianshui is given. The study is expected to supply scientific basis for seismic landslide disaster prevention and reduction in valley city of loess area.
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Kwak, Jae Hwan, and Kon Joon Bhang. "Analysis of Landslide Risk Considering Extreme Precipitation Conditions for Gyeonggi-do Gwangju Region." Crisis and Emergency Management: Theory and Praxis 17, no. 9 (September 30, 2021): 81–89. http://dx.doi.org/10.14251/crisisonomy.2021.17.9.81.
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South Korea is featured by the rugged topography that is composed of mountains about 68% of the country and the weather that rainfall is mostly concentrated during the summer. These topographic and meteorological features have caused disasters such as landslide and avalanche from mountains every year. Especially, urban expansion caused urban boundaries to get closer to steep slopes of mountains and residents are seriously exposed to disasters such as landslides so appropriate measures should be required. We, however, are facing the limitations in prevention and mitigation of landslide disasters due to the complexity of the causes of landslides like human factors as well as natural ones. To reduce the limitations, we generated of a hazard map by landslide for Gwangju City, Gyeonggi-do with an assumption of an extreme rainfall situation based on the infinite slope stability analysis model. To derive the landslide hazard map, we collected soil samples from the places where landslides actually occurred and constructed physical data by experiments and derived a landslide hazard map based on 5 rainfall scenarios. The accuracy of the result was evaluated by comparing the reference of the landslide hazard maps published by Korean Ministry of Forest.
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Tang, Dong Qi, and Jiang Bing Peng. "Statistical Analysis of Excavation Model of the Loess Landslide Developmental Characteristics." Applied Mechanics and Materials 744-746 (March 2015): 601–5. http://dx.doi.org/10.4028/www.scientific.net/amm.744-746.601.
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In recent years, with the increasing of excavation activity, caused the landslide more and more increasing, the landslide occurred gradually aroused public concern. For typical loess landslides caused by excavation, respectively from the distribution features of the landslide, landslide characteristics after wall, slope high on the impact of landslides and landslides trailing edge fracture characteristics were analyzed. Statistics show that the engineering loess landslides in the distribution respectively are selectivity of landform, strata of selectivity and zonal distribution. The excavation methods are rapid excavation and “eating” excavation. Landslide back wall angle is between 60-80°. The height of the scarp is between 3-20m, controlled by the thickness of the Malan loess. The slope high is more than 60m, with the increase of height. The risk of slide is higher. Trailing edge crack development is “wild goose feather” type and “bilateral ears” type. It provides conditions for trailing edge of evolution.
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Su, Xiaojun, Yi Zhang, Xingmin Meng, Mohib Ur Rehman, Zainab Khalid, and Dongxia Yue. "Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR." Remote Sensing 14, no. 19 (September 30, 2022): 4907. http://dx.doi.org/10.3390/rs14194907.
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The Hunza Valley, in the northwestern Karakoram Mountains, North Pakistan, is a typical region with many towns and villages, and a dense population and is prone to landslides. The present study completed landslide identification, updating a comprehensive landslide inventory and analysis. First, the ground surface deformation was detected in the Hunza Valley by SBAS-InSAR from ascending and descending datasets, respectively. Then, the locations and boundaries were interpreted and delineated, and a comprehensive inventory of 118 landslides, including the 53 most recent InSAR identified active landslides and 65 landslides cited from the literature, was completed. This study firstly named all 118 landslides, considering the demand for globally intensive research and hazard mitigation. Finally, the deformation, spatial–topographic development, and distribution characteristics in the Hunza Valley scale and three large significant landslides were analyzed. Information on 72 reported landslides was used to construct an empirical power law relationship linking landslide area (AL) to volume (VL) (VL = 0.067 × AL1.351), and this formula predicted the volume of 118 landslides in this study. We discovered that the landslides from the literature, which were interpreted from optical images, had lower levels of velocity, area, elevation, and height. The SBAS-InSAR-detected active landslide was characterized by higher velocity, larger area, higher elevation, larger slope gradient, larger NDVI (normalized difference vegetation index), and greater height. The melting glacier water and rainfall infiltration from cracks on the landslide’s upper part may promote the action of a push from gravity on the upper part. Simultaneously, the coupling of actions from river erosion and active tectonics could have an impact on the stability of the slope toe. The up-to-date comprehensive identification and understanding of the characteristics and mechanism of landslide development in this study provide a reference for the next step in landslide disaster prevention and risk assessment.
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Froude, Melanie J., and David N. Petley. "Global fatal landslide occurrence from 2004 to 2016." Natural Hazards and Earth System Sciences 18, no. 8 (August 23, 2018): 2161–81. http://dx.doi.org/10.5194/nhess-18-2161-2018.
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Abstract. Landslides are a ubiquitous hazard in terrestrial environments with slopes, incurring human fatalities in urban settlements, along transport corridors and at sites of rural industry. Assessment of landslide risk requires high-quality landslide databases. Recently, global landslide databases have shown the extent to which landslides impact on society and identified areas most at risk. Previous global analysis has focused on rainfall-triggered landslides over short ∼ 5-year observation periods. This paper presents spatiotemporal analysis of a global dataset of fatal non-seismic landslides, covering the period from January 2004 to December 2016. The data show that in total 55 997 people were killed in 4862 distinct landslide events. The spatial distribution of landslides is heterogeneous, with Asia representing the dominant geographical area. There are high levels of interannual variation in the occurrence of landslides. Although more active years coincide with recognised patterns of regional rainfall driven by climate anomalies, climate modes (such as El Niño–Southern Oscillation) cannot yet be related to landsliding, requiring a landslide dataset of 30+ years. Our analysis demonstrates that landslide occurrence triggered by human activity is increasing, in particular in relation to construction, illegal mining and hill cutting. This supports notions that human disturbance may be more detrimental to future landslide incidence than climate.
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Muryani, Chatarina, Sorja Koesuma, Yasin Yusup, Pipit Wijayanti, and Andian Hidayat. "Risk analysis of landslide disaster in Pati Regency, Central Java Province." Journal of Physics: Conference Series 2498, no. 1 (May 1, 2023): 012001. http://dx.doi.org/10.1088/1742-6596/2498/1/012001.
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Abstract Landslide is one of the disasters that often occurs in Pati Regency. This study aims to analyze the risk of landslides in Pati Regency. The landslide risk index in Pati Regency is carried out by analyzing three components: the hazard index, vulnerability, and capacity according to BNPB head regulation No. 2 the year 2012 concerning General Guidelines for Disaster Risk Assessment. The results showed a high landslide risk index in 49 villages out of 406 throughout Pati Regency. The sub-districts with the highest landslide risk index are Sukolilo District with nine villages and Gunungwungkal with seven villages. The high-risk index in the area is influenced by the high danger of landslides and the lack of existing capacity. The recommended recommendations include installing EWS, socializing knowledge on disaster preparedness, improving emergency response management, increasing community participation, evaluating RTRW, and reviewing vegetation types.
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Kim, Man-Il, and Seung-Jae Lee. "An Analysis of Landslide Risk Using the Change in the Volumetric Water Content Gradient in the Soil Layer Per Unit Time of Effective Cumulative Rainfall." Water 15, no. 9 (April 27, 2023): 1699. http://dx.doi.org/10.3390/w15091699.
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The topographical characteristics of South Korea are coupled with heavy rain and typhoons concentrated from July to September, which take up two-thirds of the country’s annual precipitation, causing substantial damage from slope failures, landslides, debris flows, and other mountain disasters. This study uses the Land-Atmosphere Modeling Package (LAMP) data to study the area, which has been affected by numerous landslides in the past. Specifically, to analyze the likelihood of slope failure, this study simulates the rainfall events in the area at the time of the landslides as well as changes in the volumetric water content in the soil layer and uses the changes in the volumetric water content per unit time, which are affected by the effective cumulative rainfall within the soil layer. To that end, this study assesses the risk of landslides based on how rainwater infiltration in the saturation depth changes the saturation depth ratio and compares the results with the landslide spots in the past. Moreover, this study analyzes the landslide risk by applying the saturation depth ratio (Ht) to an infinite slope stability analysis model. The landslide threshold proposed in this study was obtained by analyzing the rainfall events that caused the landslides in the study area using the LAMP model. It can then be concluded that, when compared with the spatial information on the previous landslides, if the change in the volumetric water content per unit time during the first and second rainfall events is 0.7, a landslide may occur. These results indicated that the landslide risk increases the volumetric water content in the soil layer, along with the congruence between past landslide risk points and spatial landslide risks.
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Song, Chang-Ho, Ji-Sung Lee, and Yun-Tae Kim. "Analysis of Landslide Susceptibility Using Deep Neural Network." Journal of the Korean Society of Hazard Mitigation 21, no. 3 (June 30, 2021): 141–50. http://dx.doi.org/10.9798/kosham.2021.21.3.141.
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Landslides in Korea are caused by various factors, such as topographic characteristics, geology, and climate change, and they cause significant damage to property and human life. It is necessary to analyze landslide susceptibility to identify the location of landslide occurrence precisely and respond to the risk of landslides. In this study, the probability of landslide occurrence was calculated through a landslide sensitivity analysis using a deep neural network based on eight conditioning factors and 26 landslide data. In addition, verification was performed using the ROC method. The landslide susceptibility obtained using a deep neural network showed a success rate of 70% and a prediction rate of 81.7%, indicating that the prediction rate was 11.7% higher than the success rate. In addition, a landslide susceptibility map for estimating the probability of landslide occurrence was plotted using the geometric spacing method. The chi-square test results indicated that the landslide susceptibility map obtained in this study was statistically significant. The location of landslides can be identified more accurately using the proposed method.
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Anugrahanto, Yohanes Dwi, Dewi Liesnoor Setyowati, and Erni Suharini. "Household Preparedness to Reducing Landslide Disaster Risk in Sepakung Village." International Journal of Research and Review 8, no. 8 (August 26, 2021): 618–27. http://dx.doi.org/10.52403/ijrr.20210882.
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Landslides are one of the natural disasters that often occur in Indonesia. Throughout 2019, Indonesia experienced 1483 landslides. Indonesian people need to have preparedness in dealing with disasters. Sepakung village is included in a landslide-prone area in Semarang regency, Central Java. This study aims to analyze the preparedness of the people of Sepakung village who live around landslide-prone points. The research method used is quantitative with a descriptive percentage analysis technique. The population of this research is the residents of Sepakung village. The sampling technique used is purposive sampling. Data collection techniques using observation, questionnaires, and documentation. The data processing results show that the experience of dealing with landslides for the residents of Sepakung village is quite good. This is shown from the average descriptive percentage score reaching 65.909091. The attitude of the respondent's vigilance is included in the very good category, with a descriptive score of the percentage getting 85%. All respondents in this study agreed that awareness of landslides needs to be increased during the rainy season. Knowledge of landslides that are owned needs to be increased again, especially for knowledge about the signs of landslides, disaster mitigation, early warning systems, and evacuation routes. Keywords: disaster, disaster risk reduction, preparedness, landslide.
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Ibrahim, Muhammad Bello, Zahiraniza Mustaffa, Abdul-Lateef Balogun, and H. H. Indra Sati. "Landslide Risk Analysis Using Machine Learning Principles: A Case Study of Bukit Antrabangsa Landslide Incidence." Journal of Hunan University Natural Sciences 49, no. 5 (May 30, 2022): 112–26. http://dx.doi.org/10.55463/issn.1674-2974.49.5.13.
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A quantitative analysis of landslides was carried out in this research to ascertain the risk that will be incurred on housing development built along hillside slopes. The study uses results from the most recent landslides analysis of GIS data and soft computing techniques to describe a concept for determining risk in a housing development situated on the hillside. The concepts presented by this study are timely, which means that computations define the time in which the housing development becomes vulnerable to landslides. The general idea enclosed in this research was to merge recent landslides analysis with real-life situations. The study location for this research was an already developed area situated along the hillside slopes of Bukit Antrabangsa, Malaysia. The approach includes predicting landslides using a novel machine-learning algorithm ensemble, the random subspace technique. The prediction process relates to the probability of occurrence of the slides responsible for the vulnerability of the housing development. A landslides prediction technique that employs GIS data to develop a geospatial database and machine learning algorithms for predicting future occurrences was used to produce the landslides inventory. The study area’s landslide inventory was then used as reference locations to predict landslide occurrence under the influence of ten landslide predisposing factors. Prediction results were evaluated for accuracy using the ROC (receiver operator characteristics) and calculated the AUC (area under the curve). Other parameters used to decide the quality of the models include the RSME (root-mean-square error), the MAE (mean absolute error), and the F-measure. The results obtained from the statistical analysis of the model show that the model has high predictive and success rates. The soft computing results now gave ways to obtain a timely probability of occurrence of the slides using a deterministic approach. The analysis was concluded by providing a conceptual equation to determine the timely probability of the slides using the available hazard information.
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Guillard-Gonçalves, C., J. L. Zêzere, S. Pereira, and R. A. C. Garcia. "Assessment of physical vulnerability of buildings and analysis of landslide risk at the municipal scale: application to the Loures municipality, Portugal." Natural Hazards and Earth System Sciences 16, no. 2 (February 3, 2016): 311–31. http://dx.doi.org/10.5194/nhess-16-311-2016.
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Abstract. This study offers a semi-quantitative assessment of the physical vulnerability of buildings to landslides in a Portuguese municipality (Loures), as well as the quantitative landslide risk analysis computed as the product of the landslide hazard by the vulnerability and the economic value of the buildings. The hazard was assessed by combining the spatiotemporal probability and the frequency–magnitude relationship of the landslides. The physical vulnerability assessment was based on an inquiry of a pool of European landslide experts and a sub-pool of landslide experts who know the study area, and the answers' variability was assessed with standard deviation. The average vulnerability of the basic geographic entities was compared by changing the map unit and applying the vulnerability to all the buildings of a test site, the inventory of which was listed on the field. The economic value was calculated using an adaptation of the Portuguese Tax Services approach, and the risk was computed for different landslide magnitudes and different spatiotemporal probabilities. As a rule, the vulnerability values given by the sub-pool of experts who know the study area are higher than those given by the European experts, namely for the high-magnitude landslides. The obtained vulnerabilities vary from 0.2 to 1 as a function of the structural building types and the landslide magnitude, and are maximal for 10 and 20 m landslide depths. However, the highest risk was found for the landslides that are 3 m deep, because these landslides combine a relatively high frequency in the Loures municipality with a substantial potential damage.
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Sui, Haoyue, Tianming Su, Ruilin Hu, Dong Wang, and Zhengwei Zheng. "Study on the Risk Assessment Method of Rainfall Landslide." Water 14, no. 22 (November 14, 2022): 3678. http://dx.doi.org/10.3390/w14223678.
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Quantitative risk assessment of landslides has always been the focus and difficulty in the field of landslide research. In this paper, taking Mayang County, Hunan Province as an example, the risk assessment of rainfall-induced landslides was carried out from the regional and individual scales. On the regional scale, the risk factors of geological disasters were analyzed. Based on the slope unit, the risk analysis of slope geological disasters and the vulnerability risk assessment of hazard-bearing bodies were carried out to form the block plan. On an individual scale, based on the analysis of rainfall extreme value, the variation law of landslide seepage field and stability under different rainfall recurrence periods was simulated. Then, the vulnerability of the disaster-bearing body was studied according to the analysis of the impact range and the field investigation. Combined with the evaluation results of landslide hazard and vulnerability of the disaster-bearing body, the life and economic risks under different working conditions were further obtained. Therefore, the research results could provide not only a reference for the risk assessment of rainfall-induced landslides in other regions but also a theoretical basis for the early warning and prediction of landslide disasters.
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Feng, Lanqian, Mingming Guo, Wenlong Wang, Yulan Chen, Qianhua Shi, Wenzhao Guo, Yibao Lou, Hongliang Kang, Zhouxin Chen, and Yanan Zhu. "Comparative Analysis of Machine Learning Methods and a Physical Model for Shallow Landslide Risk Modeling." Sustainability 15, no. 1 (December 20, 2022): 6. http://dx.doi.org/10.3390/su15010006.
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Shallow landslides restrict local sustainable socioeconomic development and threaten human lives and property in loess tableland. Therefore, the appropriate creation of risk maps is critical for mitigating shallow landslide disasters. The first task to be done was to evaluate the vulnerability of shallow landslides based on a machine learning model (random forest (RF), a support vector machine (SVM) and logistic regression (Log)), and a physical model (SINMAP) in the loess tableland area. By comparing the differences, the best method for evaluating the vulnerability of shallow landslide was selected. The nonlinear response relationship between shallow landslides and environmental factors was quantified based on the frequency ratio. Multicollinearity analysis was used to identify 10 factors that were applied on ML to construct the spatial distribution model. The SINMAP model used a DEM and soil physical parameters to determine the stability coefficient of the study area. The results showed that (1) shallow landslides in Dongzhiyuan mainly occurred on shady slopes with an elevation of 1068–1249 m, a slope gradient of 36°–60° and a concave shape. The stream power and stream transport indexes increased with increasing rainfall erosion, making shallow landslides likely. The susceptibility of shallow landslides changed parabolically with the change in the NDVI and mainly occurred in grassland and shrubland. (2) The four methods performed similarly in predicting the sensitivity of shallow landslides. The high-incidence areas were on both sides of eroded gully slopes. The tableland and gully bottom areas were not prone to shallow landslides. (3) The highest area under the curve (AUC) values were generated from the RF training and validation datasets of 0.92 and 0.93, respectively, followed by SVM AUC values of 0.91 and 0.92, respectively; Log AUC values of 0.91 and 0.89, respectively, and the SINMAP model AUC values of 0.69 and 0.74, respectively. In conclusion, the RF model best predicted the susceptibility of shallow landslides in the study area. The results provide a scientific basis for disaster mitigation on the Loess Plateau.
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Cotecchia, Federica, Francesca Santaloia, and Vito Tagarelli. "Towards A Geo-Hydro-Mechanical Characterization of Landslide Classes: Preliminary Results." Applied Sciences 10, no. 22 (November 10, 2020): 7960. http://dx.doi.org/10.3390/app10227960.
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Nowadays, landslides still cause both deaths and heavy economic losses around the world, despite the development of risk mitigation measures, which are often not effective; this is mainly due to the lack of proper analyses of landslide mechanisms. As such, in order to achieve a decisive advancement for sustainable landslide risk management, our knowledge of the processes that generate landslide phenomena has to be broadened. This is possible only through a multidisciplinary analysis that covers the complexity of landslide mechanisms that is a fundamental part of the design of the mitigation measure. As such, this contribution applies the “stage-wise” methodology, which allows for geo-hydro-mechanical (GHM) interpretations of landslide processes, highlighting the importance of the synergy between geological-geomorphological analysis and hydro-mechanical modeling of the slope processes for successful interpretations of slope instability, the identification of the causes and the prediction of the evolution of the process over time. Two case studies are reported, showing how to apply GHM analyses of landslide mechanisms. After presenting the background methodology, this contribution proposes a research project aimed at the GHM characterization of landslides, soliciting the support of engineers in the selection of the most sustainable and effective mitigation strategies for different classes of landslides. This proposal is made on the assumption that only GHM classification of landslides can provide engineers with guidelines about instability processes which would be useful for the implementation of sustainable and effective landslide risk mitigation strategies.
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Hao, Lina, Cees van Westen, Tapas Ranjan Martha, Pankaj Jaiswal, and Brian G. McAdoo. "Constructing a complete landslide inventory dataset for the 2018 monsoon disaster in Kerala, India, for land use change analysis." Earth System Science Data 12, no. 4 (November 16, 2020): 2899–918. http://dx.doi.org/10.5194/essd-12-2899-2020.
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Abstract. Event-based landslide inventories are important for analyzing the relationship between the intensity of the trigger (e.g., rainfall, earthquake) and the density of the landslides in a particular area as a basis for the estimation of the landslide probability and the conversion of susceptibility maps into hazard maps required for risk assessment. They are also crucial for the establishment of local rainfall thresholds that are the basis of early warning systems and for evaluating which land use and land cover changes are related to landslide occurrence. The completeness and accuracy of event-based landslide inventories are crucial aspects to derive reliable results or the above types of analyses. In this study, we generated a relatively complete landslide inventory for the 2018 monsoon landslide event in the state of Kerala, India, based on two inventories that were generated using different methods: one based on an object-based image analysis (OBIA) and the other on field surveys of damaging landslides. We used a collaborative mapping approach based on the visual interpretation of pre- and post-event high-resolution satellite images (HRSIs) available from Google Earth, adjusted the two inventories, and digitized landslides that were missed in the two inventories. The reconstructed landslide inventory database contains 4728 landslides consisting of 2477 landslides mapped by the OBIA method, 973 landslides mapped by field survey, 422 landslides mapped both by OBIA and field methods, and an additional 856 landslides mapped using the visual image (Google Earth) interpretation. The dataset is available at https://doi.org/10.17026/dans-x6c-y7x2 (van Westen, 2020). Also, the location of the landslides was adjusted, based on the image interpretation, and the initiation points were used to evaluate the land use and land cover changes as a causal factor for the 2018 monsoon landslides. A total of 45 % of the landslides that damaged buildings occurred due to cut-slope failures, while 34 % of those having an impact on roads were due to road cut-slope failures. The resulting landslide inventory is made available for further studies.
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Kien, Nguyen Trung, The Viet Tran, Vy Thi Hong Lien, Pham Le Hoang Linh, and Nguyen Quoc Thanh. "Landslide Susceptibility Mapping Based on the Combination of Bivariate Statistics and Modified Analytic Hierarchy Process Methods: A Case Study of Tinh Tuc Town, Nguyen Binh District, Cao Bang Province, Vietnam." Journal of Disaster Research 16, no. 4 (June 1, 2021): 521–28. http://dx.doi.org/10.20965/jdr.2021.p0521.
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Tinh Tuc town, Cao Bang province, Vietnam is prone to landslides due to the complexity of its climatic, geological, and geomorphological conditions. In this study, in order to produce a landslide susceptibility map, the modified analytical hierarchy process and landslide susceptibility analysis methods were used together with the layers, including: landslide inventory, slope, weathering crust, water storage, geology, land use, and distance from the road. In the study area, 98% of landslides occurred in highly or completely weathered units. Geology, land use, and water storage data layers were found to be important factors that are closely related with the occurrence of landslides. Although the weight of the “distance from the road” factor has a low value, the weight of layer “<100 m” has a high value. Therefore, the landslide susceptibility index very high is concentrated along the roads. For the validation of the predicted result, the landslide susceptibility map was compared with the landslide inventory map containing 47 landslides. The outcome shows that about 90% of these landslides fall into very high susceptibility zones.
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Zou, Yong, and Chao Zheng. "A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides." Applied Sciences 12, no. 9 (April 25, 2022): 4333. http://dx.doi.org/10.3390/app12094333.
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The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
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Zou, Yong, and Chao Zheng. "A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides." Applied Sciences 12, no. 9 (April 25, 2022): 4333. http://dx.doi.org/10.3390/app12094333.
Full textAbstract:
The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
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Zou, Yong, and Chao Zheng. "A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides." Applied Sciences 12, no. 9 (April 25, 2022): 4333. http://dx.doi.org/10.3390/app12094333.
Full textAbstract:
The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
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Zahor, Zahor, and Nestory E. Yamungu. "Geographical Information Systems (GIS) and Remote Sensing (RS) Analysis for Landslides Susceptibility Mapping." University of Dar es Salaam Library Journal 17, no. 2 (January 18, 2023): 72–93. http://dx.doi.org/10.4314/udslj.v17i2.6.
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This paper presents the results of an integration of Geographical Information Systems (GIS) and Remote Sensing (RS) techniques to delineate landslide susceptible areas in Lushoto district, Tanzania. To achieve this, the study has examined the distribution of landslide events and identified susceptible areas in the district. The study collected data through a handheld Global Positioning System (GPS), open-source databases and on-screen digitization. Analytical Hierarchy Process (AHP) technique was used to evaluate factors influencing landslides and Quantum GIS software was used to analyse landslides data through multi criteria technique to generate landslide susceptible areas. The study reveals that past landslides are more concentrated in the southern habitable areas of Lushoto district in which mudflow and rock falls are more dominant. The findings further expose that rainfall (29.97%) and slopes (21.72%), are the factors that have a higher influence on the occurrence of landslides while proximity to rivers (2.48%) and NDVI (1.69%) have very low influences. Further, the findings reveal that about 45% of the total area falls under moderate to very high landslides susceptible areas. This study concludes that a large area of Lushoto district’s southern part is at risk of being battered by landslides resulting from the influence of rainfall and slopes. As such the study recommends that governmental and non-governmental organizations should intervene through the formulation of policies against human activities that induce landslides in susceptible areas and to use these geospatial results to officially demarcate these areas to minimize fatalities and other economic and environmental impacts.
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KONIG, Tehrrie, Hermann KUX, and Alessandra CORSI. "LANDSLIDE RISK MANAGEMENT USING THE MATHEMATICAL MODEL TRIGRS." Geosciences = Geociências 41, no. 1 (May 27, 2022): 243–54. http://dx.doi.org/10.5016/geociencias.v41i1.16290.
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Landslides are recurrent events in Brazil, usually triggered by intense rainfall. When these events occur in urban areas, they end up becoming disasters due to economic damage, social impact, and loss of human life. The identification and monitoring of landslide-prone areas are crucial to avoid fatalities. Therefore, the aims of this work are a temporal analysis of the Factor of Safety variation in Campos do Jordão, using the mathematical model TRIGRS. During the analyzed period, two heavy rainfall events were recorded in the area and triggered landslides. The results show TRIGRS efficiency in correctly identify landslide-prone areas and its applicability to become a useful tool for urban planning and early warning systems.
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Kubwimana, Désiré, Lahsen Ait Brahim, Pascal Nkurunziza, Antoine Dille, Arthur Depicker, Louis Nahimana, Abdellah Abdelouafi, and Olivier Dewitte. "Characteristics and Distribution of Landslides in the Populated Hillslopes of Bujumbura, Burundi." Geosciences 11, no. 6 (June 17, 2021): 259. http://dx.doi.org/10.3390/geosciences11060259.
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Accurate and detailed multitemporal inventories of landslides and their process characterization are crucial for the evaluation of landslide hazards and the implementation of disaster risk reduction strategies in densely-populated mountainous regions. Such investigations are, however, rare in many regions of the tropical African highlands, where landslide research is often in its infancy and not adapted to the local needs. Here, we have produced a comprehensive multitemporal investigation of the landslide processes in the hillslopes of Bujumbura, situated in the landslide-prone East African Rift. We inventoried more than 1200 landslides by combining careful field investigation and visual analysis of satellite images, very-high-resolution topographic data, and historical aerial photographs. More than 20% of the hillslopes of the city are affected by landslides. Recent landslides (post-1950s) are mostly shallow, triggered by rainfall, and located on the steepest slopes. The presence of roads and river quarrying can also control their occurrence. Deep-seated landslides typically concentrate in landscapes that have been rejuvenated through knickpoint retreat. The difference in size distributions between old and recent deep-seated landslides suggests the long-term influence of potentially changing slope-failure drivers. Of the deep-seated landslides, 66% are currently active, those being mostly earthflows connected to the river system. Gully systems causing landslides are commonly associated with the urbanization of the hillslopes. Our results provide a much more accurate record of landslide processes and their impacts in the region than was previously available. These insights will be useful for land management and disaster risk reduction strategies.
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Taskiran, Taha, Serdar Alli, and Yuksel Yilmaz. "Hydro–Mechanical Behaviour of a Rainfall-Induced Landslide by Instrumental Monitoring: Landslide–Rainfall Threshold of the Western Black Sea Bartin Region of Türkiye." Applied Sciences 13, no. 15 (July 27, 2023): 8703. http://dx.doi.org/10.3390/app13158703.
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Bartin City is located in the Western Black Sea Region of Türkiye, where rainfall-induced landslides are more frequently observed. Although it is known that many landslides are induced by rainfall, there is limited knowledge regarding how rainfall triggers these landslides in the city. To clarify the triggering mechanisms of rainfall-induced landslides, a detailed field monitoring program was performed on a chosen area to represent landslides in Bartin. The instrumentation included the measurements of site suction, volumetric water content, groundwater level, and rainfall amount over a period of two years. Various stability analyses were performed regarding pore pressures after both transient flow infiltration analysis and site-measured suction values. The rainfall intensity–duration thresholds were obtained for both dry and wet periods as a result of the numerical analyses performed by means of parameters obtained from field monitoring. The results show that the wet period conditions create more critical conditions before failure compared to the dry period conditions, so landslides occur more easily in wet periods. According to the landslide–rainfall threshold relations, landslide-risk limits are reached if the rainfall intensity is over 10 mm/h for the dry periods and lasts between 0.85 h and 17 h depending on the saturated hydraulic conductivity of the soil. When the rainfall intensities are less than 10 mm/h, longer rainfall durations are needed for a landslide to occur. For the wet periods, landslide-risk situations are encountered if the rainfall intensity over 1 mm/h continues for 0.36 h–3.67 h, depending on the saturated hydraulic conductivities.
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Mazzanti, P., and F. Bozzano. "An equivalent fluid/equivalent medium approach for the numerical simulation of coastal landslides propagation: theory and case studies." Natural Hazards and Earth System Sciences 9, no. 6 (November 25, 2009): 1941–52. http://dx.doi.org/10.5194/nhess-9-1941-2009.
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Abstract. Coastal and subaqueous landslides can be very dangerous phenomena since they are characterised by the additional risk of induced tsunamis, unlike their completely-subaerial counterparts. Numerical modelling of landslides propagation is a key step in forecasting the consequences of landslides. In this paper, a novel approach named Equivalent Fluid/Equivalent Medium (EFEM) has been developed. It adapts common numerical models and software that were originally designed for subaerial landslides in order to simulate the propagation of combined subaerial-subaqueous and completely-subaqueous landslides. Drag and buoyancy forces, the loss of energy at the landslide-water impact and peculiar mechanisms like hydroplaning can be suitably simulated by this approach; furthermore, the change in properties of the landslide's mass, which is encountered at the transition from the subaerial to the submerged environment, can be taken into account. The approach has been tested by modelling two documented coastal landslides (a debris flow and a rock slide at Lake Albano) using the DAN-W code. The results, which were achieved from the back-analyses, demonstrate the efficacy of the approach to simulate the propagation of different types of coastal landslides.
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Yu, Teng-To, Ting-Shiuan Wang, and Youg-Sin Cheng. "Analysis of Factors Triggering Shallow Failure and Deep-Seated Landslides Induced by Single Rainfall Events." Journal of Disaster Research 10, no. 5 (October 1, 2015): 966–72. http://dx.doi.org/10.20965/jdr.2015.p0966.
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Earthquakes, rainfall, or a combination of both can trigger landslides, which can be classified into shallow and deep-seated types according to scale. Landslide risk potential can be charted according to the spatiotemporal characteristics of a combination of triggering factors that can be collated for similar historical events by various methods. The geographic information system (GIS) and the instability index method are two approaches commonly used to perform such a task; however, the nature of the event and the quality of imported data affect the degree of bias of model predictions against real-time values. To identify the differences between shallow and deep-seated landslides, 324 cases of landslides triggered by single rainfall events in Taiwan are analyzed in this study. It is determined that the principal factor governing shallow failure for rainfall-induced landslides is slope and that deep-seated failure is controlled by the amount of accumulated rainfall. By arranging the weighting, these factors could predict 93% and 75% of the occurrences of shallow and deep-seated landslides, respectively, based on a pre-event digital terrain model.
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., Thongley, D. Wangmo, V. Sharma, and K. Choden. "Spatiotemporal variation of landslide using the projected rainfall data from climate change scenario." Disaster Advances 16, no. 1 (December 15, 2022): 36–41. http://dx.doi.org/10.25303/1601da036041.
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The adverse change in weather increases landslide risk every year due to climate change. Consequently, developmental activities were hampered due to the landslide. This study aimed at developing past landslides (1997, 2007, 2017) using national rainfall data and projected landslides for the years 2027, 2037, 2050 and 2100 using the projected rainfall data in three districts of Bhutan namely Zhemgang, Mongar and Bumthang. The study uses elevation, aspect, slope, curvature, TWI, SPI, NDVI, distance from the river, distance from road, lithology and flow accumulation as influencing factors apart from different year rainfall data. The frequency ratio was employed for data analysis. Kappa index and accuracy were used to validate the landslide map for the year 2017. The landslide risk zones are classified into very low, low, moderate, high and very high. It is observed that the total area of the very low zone decreased from 1997 to 2100 while the area of the very high-risk zone increases from 1997 to 2100. Among the districts, the Zhemgang dzongkhag was highly susceptible to landslides. On the other hand, Bumthang district is least impacted by the landslides.
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Bhat, Deepak Raj, Soichiro Osawa, Akihiko Wakai, Katsuo Sasahara, Netra P. Bhandary, Fei Cai, Hirotaka Ochiai, and Norihiro Tanaka. "Rigorous Analysis of Stress-Dependent Landslide Movements with Groundwater Fluctuations Applicable to Disaster Prevention in Monsoon Asia." Journal of Disaster Research 16, no. 4 (June 1, 2021): 658–73. http://dx.doi.org/10.20965/jdr.2021.p0658.
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In this study, novel finite element approaches are proposed for numerical analysis of stress-dependent landslide movement with groundwater fluctuation by rainfall. Two new constitutive parameters that are capable of directly controlling the relationship between the apparent factor of safety and sliding velocity are incorporated into a specific material formulation used in finite element analysis for the first time. For the numerical simulation of the measured time history of the sliding displacement caused by the groundwater fluctuations, such required analytical parameters can also approximately be determined by back analysis. The proposed models are applied to a landslide field experiment on a natural slope caused by rainfall in real time in Futtsu City, Chiba Prefecture of Japan to check its applicability. The predicted and measured time histories along the horizontal direction on the upper, middle, and lower slope are compared. In addition, the deformation pattern, shear strain pattern, and possible failure mechanisms of the natural slope of such a field experiment landslide are discussed in detail based on the analysis results of the finite element method (FEM)-based numerical simulation. Moreover, the creeping landslides and possible landslide sites for further application of the proposed models are briefly discussed in the cases of Nepal and Japan as examples in Asia. It is believed that the proposed newly developed numerical models will help in understanding the secondary creep behavior of landslides triggered by extreme rainfall, and at the same time, long-term management of such landslides will be much easier in monsoon Asia. Finally, it is expected that this study will be extended for simulation of the tertiary creep behavior of landslides induced by rainfall in the near future.
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Bell, R., and T. Glade. "Quantitative risk analysis for landslides ‒ Examples from Bíldudalur, NW-Iceland." Natural Hazards and Earth System Sciences 4, no. 1 (March 9, 2004): 117–31. http://dx.doi.org/10.5194/nhess-4-117-2004.
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Abstract. Although various methods to carry out quantitative landslide risk analyses are available, applications are still rare and mostly dependent on the occurrence of disasters. In Iceland, two catastrophic snow avalanches killed 34 people in 1995. As a consequence the Ministry of the Environment issued a new regulation on hazard zoning due to snow avalanches and landslides in 2000, which aims to prevent people living or working within the areas most at risk until 2010. The regulation requires to carry out landslide and snow avalanche risk analyses, however, a method to calculate landslide risk adopted to Icelandic conditions is still missing. Therefore, the ultimate goal of this study is to develop such a method for landslides, focussing on debris flows and rock falls and to test it in Bíldudalur, NW-Iceland. Risk analysis, beside risk evaluation and risk management, is part of the holistic concept of risk assessment. Within this study, risk analysis is considered only, focussing on the risks to life. To calculate landslide risk, the spatial and temporal probability of occurrence of potential damaging events, as well as the distribution of the elements at risk in space and time, considering also changing vulnerabilities, must be determined. Within this study, a new raster-based approach is developed. Thus, all existent vector data are transferred into raster data using a resolution of 1m x 1m. The specific attribute data are attributed to the grid cells, resulting in specific raster data layers for each input parameter. The calculation of the landslide risk follows a function of the input parameters hazard, damage potential of the elements at risk, vulnerability, probability of the spatial impact, probability of the temporal impact and probability of the seasonal occurrence. Finally, results are upscaled to a resolution of 20m x 20m and are presented as individual risk to life and object risk to life for each process. Within the quantitative landslide risk analysis the associated uncertainties are estimated qualitatively. In the study area the highest risks throughout all of the analyses (individual risk to life and object risk to life) are caused by debris flows, followed by rock falls, showing that risk heavily varies depending on the process considered. The resultant maps show areas, in which the individual risk to life exceeds the acceptable risk (defined in the aforementioned regulation), so that for these locations risk reduction measures should be developed and implemented. It can be concluded that the newly developed method works satisfactory and is applicable to further catchments in Iceland, and potentially to further countries with different environmental settings.
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Katebi, Mohammad, Pooneh Maghoul, and James Blatz. "Numerical analysis of pipeline response to slow landslides: case study." Canadian Geotechnical Journal 56, no. 12 (December 2019): 1779–88. http://dx.doi.org/10.1139/cgj-2018-0457.
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A numerical analysis is carried out to study the behaviour of pipelines subjected to slow landslides at three at-risk landslide zones of Manitoba Pipeline Network. The pipeline’s longitudinal axis is parallel to the slow landslides at all three research sites. The ground displacements monitored for 5 years are imposed on the pipe using a special purpose pipe–soil interaction element (PSI element) using ABAQUS/Standard. The stiffness of PSI elements is defined based on soil–pipe interface properties according to a 2017 technical report from Pipeline Research Council International Inc. The results of the numerical analysis are compared with the instrumentation data to draw recommendations for future monitoring programs in slow landslide zones.
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Qiu, Haijun, Yifei Cui, Dongdong Yang, Yanqian Pei, Sheng Hu, Shuyue Ma, Junqing Hao, and Zijing Liu. "Spatiotemporal Distribution of Nonseismic Landslides during the Last 22 Years in Shaanxi Province, China." ISPRS International Journal of Geo-Information 8, no. 11 (November 9, 2019): 505. http://dx.doi.org/10.3390/ijgi8110505.
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The spatiotemporal distribution of landslides provides valuable insight for the understanding of disastrous processes and landslide risk assessment. In this work, we compiled a catalog of landslides from 1996 to 2017 based on existing records, yearbooks, archives, and fieldwork in Shaanxi Province, China. The statistical analyses demonstrated that the cumulative frequency distribution of the annual landslide number was empirically described by a power-law regression. Most landslides occurred from July to October. The relationship between landslide time interval and their cumulative frequency could be fitted using an exponential regression. The cumulative frequency of the landslide number could be approximated using the power-law function. Moreover, many landslides caused fatalities, and the number of fatalities was related to the number of landslides each month. Moreover, the cumulative frequency was significantly correlated with the number of fatalities and exhibited a power-law relationship. Furthermore, obvious differences were observed in the type and density of landslides between the Loess Plateau and the Qinba Mountains. Most landslides were close to stream channels and faults, and were concentrated in cropland at elevations from 600–900 m and on slope gradients from 30–40°. In addition, the landslide frequency increased as the annual rainfall levels increased over a large spatial scale, and the monthly distribution of landslides presented a significant association with the precipitation level. This study provides a powerful method for understanding the spatiotemporal distribution of landslides via a rare landslide catalog, which is important for engineering design and planning and risk management.
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Arrisaldi, Thema, Puji Pratiknyo, and Wahyu Wilopo. "GIS for Landslide Risk Assessment, Study Case Pengasih and Sentolo District, Kulon Progo, Indonesia." International Journal of Disaster Management 6, no. 1 (April 16, 2023): 19–34. http://dx.doi.org/10.24815/ijdm.v6i1.30595.
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Landslide is a natural phenomenon that often occurs as a disaster in Kulon Progo Region. This research is located in Pengasih and Sentolo District, Kulon Progo. The aim of the study is landslide risk mapping in the research area. The landslide risk map has 3 parameters, such as potential landslide condition, vulnerable situations, and community capacity to cope with the landslide disaster. Potential landslide obtained from Geographic Information System (GIS )overlay analysis using Analytical Hierarchy Process (AHP) consists of 4 sub-parameters: slope gradient (55.49%), geological condition (25.16%), stream density (9.67%), land use (9.67%). The vulnerability was obtained from 3 sub-parameters, such as economic vulnerability (33.33%), infrastructure vulnerability (33.34%), and population density (33.33%). The community capacity in the research area was obtained from The activity of the Region Disaster Management Authority (BPBD) of Kulon Progo to strengthen community awareness to cope with landslide disasters, such as socialization about landslides and simulation during an emergency landslide. The input in overlay analysis used GIS for the parameters are all sub-parameters from each parameter. Landslide risk map obtained from overlay analysis using GIS based on landslide potential map, vulnerability map, and capacity map. The result is that Pengasih and Sentolo Districts have low to moderate landslide risk conditions. Several landslides occur in each landslide risk zone.
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Kasiyanchuk, Dmytro, and Liudmyla Shtohryn. "Assessment of the Ecological Risks of Landslide Damages in the Carpathian Region." Grassroots Journal of Natural Resources 4, no. 3 (September 30, 2021): 52–61. http://dx.doi.org/10.33002/nr2581.6853.040306.
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The dynamism of the landslides within the Carpathian region of Ukraine is because of the difficult engineering and geological conditions. High landslide den sity and significant population density contribute to the fact that environmental parameters worsen and require rational management. Permanent natural factors like clay flysch formation, fault tectonics, high seismic activity, and dense network of rivers mostly facilitate the active development of landslides in the Carpathian region. However, it is triggered by extreme long-term precipitation. The numerical parameters of population density, the landslide damage coefficient, and the predictive range of landslide intensification were selected to assess the ecological risk of damages in the area. The landslide dam age coefficient characterizes the tendency of the area to landslide development, considering all the factors contributing to the landslides. Risk, as a multifunctional calculated complex, includes the calculation of damage, according to which we can assess the possibility of risk for the human being while assuming the equal distribution of the population within the study area. The integral components of the risk are calculated based on the data gathered to assess the growth of risks in the future, considering the area distribution and predictive time series of the landslide intensification. This analysis has identified engineering and geological areas having the greatest risk to human life.
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Petrucci, Olga, Graziella Emanuela Scarcella, and Massimo Conforti. "Multi-Level Data Analyses for Characterizing Rainfall-Induced Landslide Scenarios: The Example of Catanzaro Municipality (South Italy)." Water 15, no. 13 (July 1, 2023): 2437. http://dx.doi.org/10.3390/w15132437.
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This paper presents a GIS-based approach to create a multilevel data system for detailed knowledge of landslide occurrences in small territorial units such as municipalities. The main aim is to collect all the available data (geological, geomorphological, and climatic data, as well as landslide inventory maps and catalogues) in a structured data management system and perform further analyses to identify the typical landslide scenarios of the study area that can be useful in landslide risk management. We demonstrated the use of the methodology analyzing landslide risk in the municipality of Catanzaro (southern Italy), having a surface of 111.7 km2, 20.5% of which was affected by landslides. The spatial and temporal distribution of landslides highlighted that in several cases, they are reactivations of pre-existing phenomena. In fact, in the municipality, approximately 17% of the buildings fall within landslides-affected areas, 7.9% of which are in areas where landslides are classified as active. Furthermore, active landslides involve 8.1% and 9.5% of the roads and railways, respectively. In the 1934–2020 study period, 53% of activations occurred between October and December and were triggered by daily rain which in the highest percentage of cases (49%) showed values between 50 and 100 mm. The proposed GIS platform can be easily updated in order to preserve the landslide history of the area and can be enriched with further thematic layers (i.e., layers concerning flood events, which often occur simultaneously with major landslide events). The case study demonstrates how the platform can support landslide risk management in terms of monitoring, planning remedial works, and the realization/updating of civil protection plans.
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Thoha, A. S., B. Slamet, M. M. Harahap, T. Y. Sari, and D. L. N. Hulu. "The analysis of landslide vulnerability level distribution in the Labuhanbatu Utara Regency, North Sumatera Province, Indonesia." IOP Conference Series: Earth and Environmental Science 912, no. 1 (November 1, 2021): 012063. http://dx.doi.org/10.1088/1755-1315/912/1/012063.
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Abstract Forest degradation can increase the level of disaster risk, particularly landslides. The impact of landslides, especially in Labuhanbatu Utara Regency, North Sumatera Province, socio-economic, physical and environmental losses that are directly perceived by the community in the disaster site. The study objective was to analyze the distribution of landslide vulnerability levels in the Labuhanbatu Utara Regency. The spatial distribution of landslide vulnerability level used spatial modeling with the Storie Index method with four variables, including rainfall, slope, soil type, and land cover type. The spatial distribution of landslide vulnerability level was mostly at a very low – low level with a percentage of 57.6% of the area of Labuhanbatu Utara Regency. Areas that occupied high – very high of landslide vulnerability level with the largest area were in three districts, including Na IX-X, Aek Natas, and Kualuh Selatan. Landslide prone areas are generally located on plantation and agricultural land use and also distribute on steep slopes. Various parties need to reorganize community activities in areas of high – very high landslide vulnerability to reduce disaster risk.
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Nugraha Putra, Aditya, Istika Nita, Muhammad Rifqi Al Jauhary, Shofie Rindi Nurhutami, and Mohd Hasmadi Ismail. "Landslide Risk Analysis on Agriculture Area in Pacitan Regency in East Java Indonesia Using Geospatial Techniques." Environment and Natural Resources Journal 19, no. 2 (January 20, 2021): 141–52. http://dx.doi.org/10.32526/ennrj/19/2020167.
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Pacitan is one of the regencies in East Java Province, dominated by hills and mountain landforms covering 85% of its area. Since 2011, more than 16 landslides have occurred significantly in this area. These disasters have engulfed more than 350 ha of agricultural land in Pacitan. This study analyzed the risk of future landslides due to land use change. The parameters used were rainfall, slope, topography, geology, soil, and land use which were assessed and weighed by the Paimin method. Land-use classification from Landsat 8 OLI in 1998, 2008, and 2018 were analyzed using regression formula to calculate the trend of change in 2030. Land use was also classified from the land capability classification (LCC) and regional spatial planning (RSP) as land use options in 2030. The results showed that land use changed over time due to the changes in landslide hazards, which increased three-foldfrom 1998 to 2018 and will peak tremendously in 2030. There are 29.47 ha of agricultural land in 2018 that have a high potential landslide hazard if no intervention is made. The accuracy for prediction of the 2018 data mapping was 82%. The LCC strategy suggests land use planning to reduce a high level of the landslides.
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Yan, Liangxuan, Quanbing Gong, Fei Wang, Lixia Chen, Deying Li, and Kunlong Yin. "Integrated Methodology for Potential Landslide Identification in Highly Vegetation-Covered Areas." Remote Sensing 15, no. 6 (March 10, 2023): 1518. http://dx.doi.org/10.3390/rs15061518.
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It is normally difficult to identify the ground deformation of potential landslides in highly vegetation-covered areas in terms of field investigation or remote sensing interpretation. In order to explore a methodology to effectively identify potential landslides in highly vegetation-covered areas, this paper established an integrated identification method, including sliding prone area identification based on regional geological environment analysis, target area identification of potential landslides in terms of comprehensive remote sensing methods, and landslide recognition through engineering geological survey. The Miaoyuan catchment in Quzhou City, Zhejiang Province, southeastern China, was taken as an example to validate the identification methods. Particularly, the Shangfang landslide was successfully studied in terms of comprehensive methods, such as geophysical survey, drilling, mineral and chemical composition analysis, and microstructure scanning of the sliding zone. In order to assess the landslide risk, the potential runout of the Shangfang landslide was evaluated in a quantitative simulation. This paper suggests a methodology to identify potential landslides from a large area to a specific slope covered by dense vegetation.
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Wang, Peng Cheng, Zhao Yi Xu, Ming Zhou Bai, Yan Qing Du, Shu Huai Mu, Dong Wang, and Yin Jing Yang. "Landslide Risk Assessment Expert System Along the Oil and Gas Pipeline Routes." Advanced Materials Research 418-420 (December 2011): 1553–59. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.1553.
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The West-East gas pipeline project in Western China was as an example in the research work. Expert system platform was used as a basic tool. The typical model database systems of West-East gas pipeline project was built. On the base of collection, collation, comprehensive analysis of existing data, through a case study of a large number of landslides, the induced landslides and stability control factor were becoming clear. A landslide risk assessment criteria and evaluation index system was established. On this basis, through application of expert system method, a Expert system platform based landslide risk evaluation expert system about long-distance pipeline routes was developed.It also give a application example of this expert system.
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Mohamad, Z., Z. Ramli, M. Z. Abd Rahman, M. R. Mohd Salleh, Z. Ismail, and M. F. Abdul Khanan. "VULNERABILITY MAPPING AND ANALYSIS: AN IMPLEMENTATION IN GEOHAZARD AREAS IN SABAH." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W9 (October 30, 2018): 189–200. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w9-189-2018.
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<p><strong>Abstract.</strong> Vulnerability identifies the element-at-risk as well as the evaluation of their relationships with the hazard. The relationships relate the landslide potential damages over a specific element-at-risk. Vulnerability can be defined as the degree of loss to a given element-at-risk or set of elements at risk resulting from the occurrence of a natural phenomenon of a given magnitude and expressed on a scale from 0 (no damage) to 1 (total damage). In this study, the landslide vulnerability mapping and analysis were made on two element-at-risks namely buildings and roads. Based on field observations, building and road construction materials have been classified into 22 and 5 construction materials respectively. The field visits were made on specific areas based on candidate buildings and roads as chosen during the landslide exposure analysis and mapping. The vulnerability values for these element-at-risks were expressed using expert opinion. Four experts have been interviewed with separate sessions. The experts were also supplied with local information on the landslides occurrences and photos of element-at-risk in Kundasang and Kota Kinabalu. The vulnerability matrices were combined based on the weighted average approach, in which higher weight was assigned to panel with local expert (landslides and damage assessment), wide experience in landslide vulnerability analysis, hazard and risk mapping. Finally, the vulnerability maps were produced for Kundasang and Kota Kinabalu with spatial resolution of 25<span class="thinspace"></span>cm. These maps were used for the next step i.e. landslide risk mapping and analysis.</p>
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Shekhunova, S. B., N. P. Siumar, O. P. Lobasov, and S. M. Stadnichenko. "ANALYSIS OF SPATIAL PATTERNS OF LANDSLIDE FORMATION WITH GIS TOOLS (ZAKARPATSKA OBLAST)." Ukrainian geographical journal 2022, no. 3 (November 2022): 11–20. http://dx.doi.org/10.15407/ugz2022.03.011.
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To identify the primary and derived geological factors determining the spread and activation of landslides within Zakarpatska Oblast, a database of 2.575 landslides were collected and integrated into GIS, with a total area of 385.21 km2 covered. Using the ArcView Spatial Analyst environment, the factors of landslide formation represented by the constructed grids of the relief, its derivatives, and the density of structural-tectonic heterogeneities have been examined. It has been established that landslide development maximum occurs at heights with hypsometric marks of 280–730 m, slopes of 7.5–22.4° steepness, oriented to the west, south-west, south, and south-east and located at a distance of up to 500 m from watercourses. Two-thirds of all analyzed landslides are located within a kilometer zone along structural-tectonic disturbances and at a distance of up to 1250 m to disorders with the 90–180° azimuth. The approach applied made it possible to establish for the first time ever the patterns of landslide occurrence, relying on the results of processing a large array of primary cartographic information, and to obtain probable limit values characterizing landslide formation factors, as well as build an iterative regional predictive model for forecasting landslide hazards occurrence. Mapping of areas with characteristic values of the factors determined will be used for local landslide forecasts. It will be implemented in the development of measures to reduce the risk of hazardous landslide processes in Zakarpatska Oblast.
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Setiawan, Heru, Nanette C. Kingma, and C. J. Van Westen. "Analysis Community’s Coping Strategies and Local Risk Governance Framework in Relation to Landslide." Indonesian Journal of Geography 46, no. 2 (December 31, 2014): 143. http://dx.doi.org/10.22146/ijg.5784.
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Analysis of people perception and analysis of the coping strategy to landslides are the two elements that are es-sential to determine the level of preparedness of communities to landslides. To know the preparedness of government and other stakeholders in facing landslide, the analysis risk governance framework was required. A survey using questionnaires with random sampling was applied to assess the level of people perception and people coping strategy related to landslide. Analysis of risk governance frame work was done at the district and sub-district level. ἀe study found that people perception related with landslide dominated by high and moderate level. Age and education are two factors that inḀuence the people’s perception to landslide. Local people applied four types coping strategy, which are: economic, structural, social and cultural coping strategy. Totally, 51.6% respondents have high level, 33.3% have moderate level and only 15.1% respondents that have low level of coping strategy. ἀe factors that inḀuence the level of coping strategy are education, income and building type. Analysis of risk governance framework is limited to the three components including stakeholder involvement, risk management and risk communication. Based on the data analysis, the level of stakeholder involvement at the district scope was categorized on the moderate till high and the level of stakeholder involvement at sub-district level was categorized on the high level. Generally, the risk management of Karanganyar was categorized on the moderate level and high level and the risk management in Tawangmangu was categorized on the moderate level. ἀere are some elements must be improved on the risk governance framework, those are data management, the pattern of relationships among stakeholders, increased participation of NGOs, constructed and updated landslide risk map, enhancement of microᴀnance role in helping the com-munity when disaster strikes and dissemination of information about the landslide to the local community.
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Sujatmiko, Karina Aprilia, Koji Ichii, Soichiro Murata, and Iyan Eka Mulia. "Application of Stress Parameter from Liquefaction Analysis on the Landslide Induced Tsunami Simulation: A Case Study of the 2018 Palu Tsunami." Journal of Disaster Research 18, no. 3 (April 1, 2023): 199–208. http://dx.doi.org/10.20965/jdr.2023.p0199.
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The accuracy of numerical simulations of a landslide-induced tsunami depends on the landslide characteristics, such as landslide geometry and geotechnical parameters. However, owing to the difficulty in sampling and measuring submarine landslides, rough assumptions of landslide parameters typically lead to significant uncertainties. In the 2018 Palu event, the earthquake was followed by immediate cascading disasters of coastal subsidence, both land and submarine landslides and a tsunami. This scenario provides opportunities to analyze landslide phenomena on land to characterize the submarine landslide causing the tsunami. This study proposes a new approach of using shear-stress parameters obtained from liquefaction analyses as input for landslide-induced tsunami simulation. To obtain the submarine landslide parameter, using the finite element method we modeled the liquefaction happened in Jono-Oge located near Palu Valley area. The shear-stress in this area was quite small with the range 1.5–3.5 kPa. We found that tsunami simulation yielded better accuracy by applying the stress value range obtained from the liquefaction analysis on land (1.5 kPa) rather than the typically adopted stress value for general cases (20 kPa). The result from the tsunami simulation using two-layer method with identical landslide location and geometry showed that shear-stress value of landslide mass gave quite a significant effect to the tsunami height.
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Kohno, Masanori, and Yuki Higuchi. "Landslide Susceptibility Assessment in the Japanese Archipelago Based on a Landslide Distribution Map." ISPRS International Journal of Geo-Information 12, no. 2 (January 22, 2023): 37. http://dx.doi.org/10.3390/ijgi12020037.
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Though danger prediction and countermeasures for landslides are important, it is fundamentally difficult to take preventive measures in all areas susceptible to dangerous landslides. Therefore, it is necessary to perform landslide susceptibility mapping, extract slopes with high landslide hazard/risk, and prioritize locations for conducting investigations and countermeasures. In this study, landslide susceptibility mapping along the whole slope of the Japanese archipelago was performed using the analytical hierarchy process (AHP) method, and geographic information system analysis was conducted to extract the slope that had the same level of hazard/risk as areas where landslides occurred in the past, based on the ancient landslide topography in the Japanese archipelago. The evaluation factors used were elevation, slope angle, slope type, flow accumulation, geology, and vegetation. The landslide susceptibility of the slope was evaluated using the score accumulation from the AHP method for these evaluation factors. Based on the landslide susceptibility level (I to V), a landslide susceptibility map was prepared, and landslide susceptibility assessment in the Japanese archipelago was identified. The obtained landslide susceptibility map showed good correspondence with the landslide distribution, and correlated well with past landslide occurrences. This suggests that our method can be applied to the extraction of unstable slopes, and is effective for prioritizing and implementing preventative measures.
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Mozas-Calvache, A. T., J. L. Pérez-García, T. Fernández-del Castillo, J. M. Gómez-López, and C. Colomo-Jiménez. "ANALYSIS OF LANDSLIDES BASED ON DISPLACEMENTS OF LINES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 549–55. http://dx.doi.org/10.5194/isprs-archives-xli-b7-549-2016.
Full textAbstract:
Nowadays, the development of UAS has allowed the obtaining of high resolution and accurate cartographic products, such as DSMs and orthoimages. These products can be used in studies of the evolution of landslides. The stability of slopes is a main issue because, among others, it can suppose a serious risk to infrastructures. Until this moment, some studies for analysing slope movements have been carried out using the comparison of positions of well-defined points or comparing two surfaces obtained from two DSMs. In this paper we present a methodology for analysing landslides based on some linear elements located on the terrain. More specifically, we analyse some lines of road sections which are located on an unstable slope, checking the movements of the landslide and their effect on the infrastructure. The methodology includes the obtaining of high resolution orthoimages and DSMs which correspond to two or more epochs of the same landslide, the 3D digitizing of common linear elements, and the computing of the displacements of matched lines (from two epochs) using positional control methods based on lines. The proposed methodology has been tested using two DSMs and two orthoimages (corresponding to two epochs) obtained from two photogrammetric projects developed with an UAS. This real case was applied to an unstable slope with landslides which affected several sections of a road. The results have demonstrated the viability of the proposed methodology in analysing the behaviour of the landslide and more specifically, the effects on these infrastructures.
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Mozas-Calvache, A. T., J. L. Pérez-García, T. Fernández-del Castillo, J. M. Gómez-López, and C. Colomo-Jiménez. "ANALYSIS OF LANDSLIDES BASED ON DISPLACEMENTS OF LINES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 549–55. http://dx.doi.org/10.5194/isprsarchives-xli-b7-549-2016.
Full textAbstract:
Nowadays, the development of UAS has allowed the obtaining of high resolution and accurate cartographic products, such as DSMs and orthoimages. These products can be used in studies of the evolution of landslides. The stability of slopes is a main issue because, among others, it can suppose a serious risk to infrastructures. Until this moment, some studies for analysing slope movements have been carried out using the comparison of positions of well-defined points or comparing two surfaces obtained from two DSMs. In this paper we present a methodology for analysing landslides based on some linear elements located on the terrain. More specifically, we analyse some lines of road sections which are located on an unstable slope, checking the movements of the landslide and their effect on the infrastructure. The methodology includes the obtaining of high resolution orthoimages and DSMs which correspond to two or more epochs of the same landslide, the 3D digitizing of common linear elements, and the computing of the displacements of matched lines (from two epochs) using positional control methods based on lines. The proposed methodology has been tested using two DSMs and two orthoimages (corresponding to two epochs) obtained from two photogrammetric projects developed with an UAS. This real case was applied to an unstable slope with landslides which affected several sections of a road. The results have demonstrated the viability of the proposed methodology in analysing the behaviour of the landslide and more specifically, the effects on these infrastructures.
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Arrogante-Funes, Patricia, Adrián G. Bruzón, Fátima Arrogante-Funes, Ana María Cantero, Ariadna Álvarez-Ripado, René Vázquez-Jiménez, and Rocío N. Ramos-Bernal. "Ecosystem Services Assessment for Their Integration in the Analysis of Landslide Risk." Applied Sciences 12, no. 23 (November 28, 2022): 12173. http://dx.doi.org/10.3390/app122312173.
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Landslides are disasters that cause damage to anthropic activities, innumerable loss of human life, and affect the natural ecosystem and its services globally. The landslide risk evaluated by integrating susceptibility and vulnerability maps has recently become a manner of studying sites prone to landslide events and managing these regions well. Developing countries, where the impact of landslides is frequent, need risk assessment tools to address these disasters, starting with their prevention, with free spatial data and appropriate models. However, to correctly understand their interrelationships and social affection, studying the different ecosystem services that relate to them is necessary. This study is the first that has been attempted in which an integrated application methodology of ecosystem services is used to know in a systematic way if the information that ecosystem services provide is useful for landslide risk assessment. For the integration of ecosystem services into the landslide risk evaluation, (1) eight ecosystem services were chosen and mapped to improve understanding of the spatial relationships between these services in the Guerrero State (México), and (2) areas of synergies and trade-offs were identified through a principal component analysis, to understand their influence on risk analysis better. These are extracted from the models of the ARIES platform, artificial intelligence, and big data platform. Finally, (3) the similarity between the risk characteristics (susceptibility and vulnerability, already mapped by the authors) and the ecosystem services assessment was analysed. The results showed that the ecosystem services that most affect the synergy are organic carbon mass and the potential value of outdoor recreation; meanwhile, the possible removed soil mass was the most important trade-off. Furthermore, the lowest similarity value was found between landslide vulnerability and ecosystem services synergy, indicating the importance of including these ecosystem services as a source of valuable information in the risk analysis methodologies, especially with respect to risk vulnerability.