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Complex or compound landslides, which combine different movement types with sliding planes at various depths and with varying movement acceleration frequencies, are highly demanding for landform mapping, movement monitoring and reliable hazard assessment. In this work, several techniques including dendrogeomorphological investigation were combined to describe surface morphology, underground structures and movement dynamics of the compound and deep-seated landslide aiming to provide reliable information for its hazard assessment. Interpretation of high-quality digital elevation model and detailed field morphological mapping along with geological information provided context for the interpretation of electric resistivity tomography profiles and enabled the description of properties of two distinct landforms, which are typically identified on a compound or complex deep-seated landslides in the studied region—shallow slides and landslide blocks. Dendrogeomorphological investigation proved for the first time the movement accelerations of the landslide blocks, which reactivate approximately half as often as shallow slides. It also showed different trees' responses to the movements of these two landforms. Trees on the shallow landslide responded mainly with abrupt growth suppression (54.4%) to movements of its highly disturbed material. In contrast, trees on landslide blocks exhibited a dominant response (84.7%) with reaction wood to tilting of the landslide blocks composed of more coherent rock material. The research demonstrated that the dendrogeomorphological investigations provide reliable identification of years with accelerated movements, which corresponds well to instrumental, near-surface monitoring of the landslide. And at the same time, the method provided densely spatially distributed information about partial landslide reactivations during several decades in conditions (e.g. dense forests), where remote sensing methods are difficult to apply. Therefore, we argue that the dendrogeomorphological research is well applicable for hazard assessment of partial failures (cf., shallow slides and landslide blocks) of compound or complex landslides providing information also about the type of landslide movements (sliding vs. surface tilting) and character of the deformed material (highly disturbed vs. more coherent). [ABSTRACT FROM AUTHOR]

The key to seismic landslide risk identification resides in the accurate evaluation of seismic landslide hazards. The traditional evaluation models for seismic landslide hazard seldom consider the landslide dynamic runout process, leading to an underestimation of seismic landslide hazard. Therefore, a joint Newmark–Runout model based on landslide dynamic runout is proposed. According to the evaluation results of static seismic landslide hazard, the landslide source points can be extracted, and the landslide dynamic runout process is simulated to obtain the dynamic seismic landslide hazard. Finally, the static and dynamic seismic landslide hazards are fused to obtain an optimized seismic landslide hazard. In September 2022, a strong Ms6.8 earthquake occurred in the eastern Tibetan Plateau, triggering thousands of landslides. Taking the 2022 Luding earthquake-induced landslide as a sample, the function relationship between seismic slope displacement and landslide occurrence probability is statistically modeled, which partly improves the traditional Newmark model. The optimized seismic landslide hazard evaluation of the Luding earthquake area is conducted, and then, the seismic landslide risk identification is completed by taking roads and buildings as hazard-affected bodies. The results show that the length of the roads facing very high and high seismic landslide risks are 3.36 km and 15.66 km, respectively, and the buildings on the Moxi platform near the epicenter are less vulnerable to seismic landslides. The research findings can furnish critical scientific and technological support for swift earthquake relief operations. [ABSTRACT FROM AUTHOR]

Landslides are one of the most frequent natural disasters that cause significant damage to property in Vietnam, which is characterized by mountainous terrain covering three-quarters of the territory. In 17 northern mountainous provinces of the country, over 500 communes are at a high to very high landslide hazard. The main goal of this study was to establish landslide hazard maps and conduct a comparative evaluation of the efficiency of the methods employed in Tinh Tuc town, Cao Bang province. The landslide hazard assessment was carried out in this study using the combined Fractal-frequency ratio (FFR) and the Frequency ratio (FR) methods. The FR method is based on the actualist principle, which assumes that future landslides may be caused by the same factors that contributed to slope failure in the past and present. The FFR method is based on the determination of the fractal dimension, which serves as a measure of the landslide filling density in the study area. Eight landslide-related factors were considered and presented in cartographic format: elevation, distance to roads, slope, geology, distance to faults, land use, slope aspect, and distance to drainage. Determining the area under the receiver operating characteristic curve (ROC-AUC) and verification index (LRclass) was performed to assess the performance of prediction models and the accuracy of the obtained maps. As a result, five zones were identified for the study area, characterized by very low, low, moderate, high, and very high landslide hazards. The analysis of the reliability of the obtained landslide hazard maps using the AUC and LRclass indices revealed that the FFR model has a higher degree of reliability (AUC = 86 %, LRclass = 86 %) compared to the FR model (AUC = 72 %, LRclass = 73 %); therefore, its use is more effective.

Quantitative calculation of single landslide risk has great significance for the prevention and treatment of landslides, through analysing the slope stability under different rainfall recurrence periods. In this study, the rainfall of the past 40 years in Xun'wu County of China is counted and the rainfall during the return periods of 10, 20 and 50 years are calculated to form three different rainfall conditions. Then, the stability of Cheng'nan landslide in Xun'wu County is calculated by the Geo‐Studio 2007 software, and the probability of landslide occurrence is obtained by Monte Carlo theory under these three conditions. Next, the field investigation is employed to obtain the statistical results of the buildings and personnel in the affected area of Cheng'nan landslide. Finally, the risk of economic loss and casualty under the three conditions are calculated. It was demonstrated that: (1) Under the three conditions, the safety factor decreased gradually, the rate of decrease was slower in the first 3 days and faster in the middle period and there was still a downward trend after the end of the rain. (2) The probability of landslide occurrence during the rainfall return periods of 10, 20 and 50 years were 1.77%, 2.97% and 1.61%, respectively. Besides, the risk index of landslide was the highest under the condition of 20‐years rainfall return period. (3) The economic loss risk and casualty risk in the rainfall return periods of 10, 20 and 50 years were 122,700‐yuan and 4.11 people, 205,900‐yuan and 6.89 people, as well as 11,600‐yuan and 3.74 people, respectively. [ABSTRACT FROM AUTHOR]

Monitoring surface displacements of landslides is essential for evaluating their evolution and the effectiveness of mitigation works. Traditional methods like robotic total stations (RTSs) and GNSS provide high-accuracy measurements but are limited to discrete points, potentially missing the broader landslide's behavior. On the contrary, laser scanner surveys offer accurate 3D representations of slopes and the possibility of inferring their movements, but they are often limited to infrequent, high-cost surveys. Monitoring techniques based on ground-based digital photogrammetry may represent a new, robust, and cost-effective alternative. This study demonstrates the use of multi-temporal images from fixed and calibrated cameras to achieve the 3D reconstruction of landslide displacements. The method presented offers the important benefit of obtaining spatially dense displacement data across the entire camera view and quasi-continuous temporal measurement. This paper outlines the framework for this prototyping technique, along with a description of the necessary hardware and procedural steps. Furthermore, strengths and weaknesses are discussed based on the activities carried out in a landslide case study in northeastern Italy. The results from the photo-monitoring are reported, discussed, and compared with traditional topographical data, validating the reliability of this new approach in monitoring the time evolution of surface displacements across the entire landslide area. [ABSTRACT FROM AUTHOR]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Landslide is a typical geological disaster distributed in most countries worldwide. Due to long-term natural weathering and human engineering disturbances, the instability of landslides is prone to occur. Once monitoring and disposal methods are implemented inappropriately, they can lead to landslide hazards, seriously threatening the safety of people's lives and property. For a long time, extensive research on landslide monitoring has been conducted from various countries, providing crucial technical support for reducing the incidence and severity of landslide hazards. However, considering the complex geological conditions of actual landslides and the direct impact of internal and external factors such as rainfall, storms, and earthquakes, the early warning accuracy of landslide hazards is still relatively low. Therefore, based on advanced research achievements, it is significant to carry out research on the current status and development trends of landslide monitoring technology. Based on the Web of Science core database, this study quantitatively analyzes the advanced research achievements in global landslide monitoring in the past decade using bibliometric analysis. A systematic analysis of landslide monitoring technology development is conducted according to each study's publication time, keywords, and countries. On this basis, a multi-dimensional monitoring system for landslides was proposed, which utilizes the complementary advantages of multi-dimensional monitoring technology to achieve all-round, high-precision, and real-time monitoring of landslides. Finally, taking the Xinpu landslide in the Three Gorges Region of China as an example, a multi-source and multi-field-monitoring experiment was conducted. The application of landslide multi-field-monitoring technology provides an essential reference for monitoring, early warning, as well as the scientific prevention and control of landslide hazard. [ABSTRACT FROM AUTHOR]

This study develops a model to assess building vulnerability across Xinxing County by integrating quantitative derivation with machine learning techniques. Building vulnerability is characterized as a function of landslide hazard risk and building resistance, wherein landslide hazard risk is derived using CNN (1D) for nine hazard-causing factors (elevation, slope, slope shape, geotechnical body type, geological structure, vegetation cover, watershed, and land-use type) and landslide sites; building resistance is determined through quantitative derivation. After evaluating the building susceptibility of all the structures, the susceptibility of each village is then calculated through subvillage statistics, which are aimed at identifying the specific needs of each area. Simultaneously, different landslide hazard classes are categorized, and an analysis of the correlation between building resistance and susceptibility reveals that building susceptibility exhibits a positive correlation with landslide hazard and a negative correlation with building resistance. Following a comprehensive assessment of building susceptibility in Xinxing County, a sample encompassing different landslide intensity areas and susceptibility classes of buildings was chosen for on-site validation, thus yielding an accuracy rate of the results as high as 94.5%. [ABSTRACT FROM AUTHOR]

Climate change is increasing the frequency and intensity of extreme rainfall events, which aggravate the threat to the safety of natural and man-made slopes. There is growing interest in the role of rainfall characteristics in these slope failures. Most of previous studies treated the rainfall individually or as cumulative value and used hypothetical rainfall temporal patterns with no association with actual physical failures. In this study, the two deadly landslides in Sau Mau Ping, Hong Kong, in June 1972 and August 1976, which caused 165 casualties, are revisited. An intriguing question that has long been overlooked is posed: why the slopes that withstood the 1972 rainfall failed in the 1976 rainfall, given that the rainfall intensity of the latter event was only half of the former? Based on an extensive review of the forensic reports and relevant studies on the failure events, numerical modeling is carried out by a combination of seepage analysis with stability analysis and unsaturated shear strength theory. Focus is placed on the geological and hydrological settings and the rainfall characteristics, particularly the temporal pattern of the antecedent and main rainfall, to look into the causes and mechanisms for these failures. Implications of the new findings for future research and practice are also highlighted. [ABSTRACT FROM AUTHOR]

The instability evolution of loess slopes under the coupling of water and earthquake is very complex. Quantitative assessment of seismic landslide hazard has become a common challenge for engineering geologists and seismic geologists. This article takes the Yongguangcun (YGC) landslide induced by the 2013 Mw6.6 Minxian-Zhangxian earthquake to systematically study the hazard of loess slopes under the coupling effect of water and earthquake, namely their runout problem. The seismic accelerations in three directions recorded by MXT were decomposed along the sliding direction and the inclination of the slope to obtain the seismic load along the tangential direction of the sliding surface. Then, a combination of a finite element method and the Newmark method is used to study the co-seismic sliding of the YGC landslides during the earthquake, fully considering the effects of various factors such as pore water pressure, groundwater, and matric suction during rainfall on the permanent displacement of the slope. The present study yields the following research findings: 1) The pre-earthquake safety factor of the YW# landslide, which has a sliding surface in close proximity to the groundwater level, is reduced to 1.247 under the combined influence of rainfall and groundwater. Additionally, the critical earthquake acceleration is determined to be 0.0763 g. 2) It is observed that when the peak acceleration along the tangential direction of the sliding surface near the groundwater surface reaches or surpasses 0.175 g, the cumulative displacement of the YW# landslide may exceed the critical failure value of 5–10 cm. It provides a reference for the quantitative assessment of regional seismic landslide hazard, which has important theoretical and practical value. [ABSTRACT FROM AUTHOR]

ABSTRACTThe north-eastern border of CA represents the accretionary system developed during its continuous collision with Apulian block. The tardive oblique tectonic component is highlighted by pervasive NW-SE crustal transpressive left-lateral strike slip faults developed from the Upper Miocene to Quaternary tectonic stages. The seismotectonic and landslides Main Map represents the update of the main faults, the style of their arrangement and kinematics, the seismotectonic features and landslide area distribution with risk implications. Seismotectonics allows us to recognise a vertical crustal zonation with the distribution of earthquakes and their focal mechanism solution. The prevalent modality of ruptures depicts a mainly transcurrent and compressive solution in mid-lower crust portions respectively. This data, together with the historical seismicity analysis of the area, lead to consider the NW-SE strike-slip faults improved on the Main Map, as recent and tectonically active. The areal distribution of landslide and susceptibility of the area is due to the interaction between seismotectonic peculiarity, lithological typologies and fault zone architectures. Landslides and flood phenomena of this sector involve many municipalities, major and minor infrastructures and economic and social activities. The landslides and the faults have been identified, mapped and classified, originally at detail scale and, then, represented at 1:50,000 scale in the Main Map, included as supplementary material. The geo-structural and geomorphological data were analysed in a geographic information system allowing data management and implementation. The work presents an updated knowledge framework of risk conditions of the study zone, available to plan and reduce the fundamental elements that determine the landslide and seismic risks in this region.

AbstractTo achieve the net-zero carbon dioxide emission goals, the number of solar photovoltaic (PV) power stations (PPSs) installed worldwide has increased. An increasing number of PPSs are exposed to natural hazards, such as landslides. However, the socioeconomic impact of landslide risk on PPSs has rarely been assessed nationally. In this study, we assessed the landslide risk for PPSs by combining statistical susceptibility and physical-based hazard analyses under three representative concentration pathways (RCPs). We found that the cumulative landslide-susceptible area (LSA) during the current, 2040s, and 2090s periods could vary depending on RCP scenarios: 2895 (RCP2.6), 3417 (RCP6.0) and 5492 km2 (RCP8.5). Especially, under RCP6.0, due to the spatial match with the distribution of LSA and the PPSs, the landslide risk on PPSs could become about 60 million dollars per year. This loss would be 24 million dollars more than the risk of RCP2.6. This study provides insights into the economic loss of PPSs from landslides in the Republic of Korea and suggests that severe climate change would bring a significant increase in this economic loss, which may occur in other countries with large mountainous areas.

Abstract Landslide hazards significantly threaten rural communities, impacting various aspects of livelihoods, including food security. The Gamo Highlands in southern Ethiopia is vulnerable to landslide hazards. Therefore, this research aims to investigate the effect of landslide hazards on rural households’ food security status in the Gacho Baba district, Gamo Highlands, southern Ethiopia. The study employed a mixed approach, to collect and analyze data collected from 289 households, community leaders, and early warning and food security experts. Purposive and multistage sampling techniques were deployed. Both descriptive and inferential statistics were used to analyze the data. Household Food Insecurity Access Scale (HFIAS), Food Consumption Score (FCS), and Reducing Coping Strategies Index (RCSI) were food in/security indicators used. The HFIAS reveals significant worries regarding stable access and availability of food, with 62% of sample households categorized as mildly, moderately, and severely food-insecure. FCS indicates prevalent challenges in achieving adequate food consumption levels among the surveyed households, with a significant portion falling into the poor consumption category (51.3%). while the investigation of coping strategies using RCSI categorized (53.3%) of study samples into high coping strategies. The study also reveals varying levels of awareness and preparedness among households, with a significant proportion expressing uncertainty about landslide occurrence and prevention mechanisms. The findings underscore the need for targeted educational and awareness initiatives, as well as comprehensive risk reduction strategies, to enhance household resilience and safeguard food security in landslide-prone areas.

Alluvial river channels respond to changes in sediment supply by adjusting their geometry. Landslide sediment delivery and geomorphic response of river channels during floods are poorly understood and rarely examined in tropical settings. We investigate the impact of landslides on channel geomorphic changes during an extreme typhoon‐induced flood event in the Philippines, specifically the complex geomorphic response of the Antamok River to Typhoon Mangkhut in September 2018, which triggered >500 landslides in the Ambalanga catchment. The catchment has a legacy of anthropogenic modifications, such as extensive small‐scale (artisanal) mining and tailings storage facilities (TSFs) from large‐scale mining activities. We use a novel mix of mapping and computational modelling approaches to test the hypothesis that landslide sediment delivery is a major control on channel geomorphic change. Pre‐ and post‐event imagery show that the overall active channel area increased by 35.9% and the mean active channel width increased by 9.1 m. Spatially, we find no clear relationship between landslide sediment input or unit stream power and channel width geomorphic change, with longitudinal changes in active channel width complicated by TSFs. Multi‐phase modelling using r.avaflow revealed how landslide sediment delivery and TSFs interacted with the flow to generate the observed patterns of channel change. The model simulated channel incision in the upper parts of the catchment (up to 0.78 m) and deposition in the TSFs (up to 1.73 m). Our findings demonstrate that well‐established methods (e.g., stream power threshold) fail to fully explain channel width geomorphic changes, particularly for anthropogenically altered catchments. Integrating techniques, such as landslide mapping and multi‐phase computational modelling improves understanding of sediment supply's role in channel width change during extreme events. Numerical simulations also demonstrate that conventional assumptions of increased erosion and deposition with rising flow discharge are inaccurate with large sediment input, highlighting instead the effectiveness of multi‐phase models. [ABSTRACT FROM AUTHOR]

Landslide hazards significantly threaten rural communities, impacting various aspects of livelihoods, including food security. The Gamo Highlands in southern Ethiopia is vulnerable to landslide hazards. Therefore, this research aims to investigate the effect of landslide hazards on rural households' food security status in the Gacho Baba district, Gamo Highlands, southern Ethiopia. The study employed a mixed approach, to collect and analyze data collected from 289 households, community leaders, and early warning and food security experts. Purposive and multistage sampling techniques were deployed. Both descriptive and inferential statistics were used to analyze the data. Household Food Insecurity Access Scale (HFIAS), Food Consumption Score (FCS), and Reducing Coping Strategies Index (RCSI) were food in/security indicators used. The HFIAS reveals significant worries regarding stable access and availability of food, with 62% of sample households categorized as mildly, moderately, and severely food-insecure. FCS indicates prevalent challenges in achieving adequate food consumption levels among the surveyed households, with a significant portion falling into the poor consumption category (51.3%). while the investigation of coping strategies using RCSI categorized (53.3%) of study samples into high coping strategies. The study also reveals varying levels of awareness and preparedness among households, with a significant proportion expressing uncertainty about landslide occurrence and prevention mechanisms. The findings underscore the need for targeted educational and awareness initiatives, as well as comprehensive risk reduction strategies, to enhance household resilience and safeguard food security in landslide-prone areas. [ABSTRACT FROM AUTHOR]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the Shahroud Watershed, there has been an increasing occurrence of landslides that have caused a lot of human and financial losses. Therefore, landslide susceptibility zonation is crucial for reducing landslide risk. The aim of this study was to compare the Landslide Susceptibility Maps (LSMs) of different methods. Therefore, thematic layers of the ten causal factors were prepared. Then, a landslide inventory map consisting of 104 landslides covering 1401 hectares was compiled and partitioned into two subsets including 70% for training and 30% for testing purposes. Three landslide susceptibility maps were prepared using the Frequency ratio (Fr), Statistical index (Si), and Analytic Hierarchy Process (AHP) methods. The validation process showed that the Si [Area Under the Curve (AUC)= 0.732] and Fr (AUC= 0.707) models presented a more valid LSM than AHP (AUC= 0.651) method. The Qs (Quality sum) index values also confirmed the results of the ROC (Receiver Operating Characteristic) curve such that the Qs index values of 1.71, 1.43, and 0.62 for, respectively, Fr, Si, and AHP models implied a more accurate LSMs of the Fr and Si models than the one from the AHP. The results of this study can be used as a basic step for landslide risk management in the study area. [ABSTRACT FROM AUTHOR]

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides. [ABSTRACT FROM AUTHOR]

The key to seismic landslide risk identification resides in the accurate evaluation of seismic landslide hazards. The traditional evaluation models for seismic landslide hazard seldom consider the landslide dynamic runout process, leading to an underestimation of seismic landslide hazard. Therefore, a joint Newmark–Runout model based on landslide dynamic runout is proposed. According to the evaluation results of static seismic landslide hazard, the landslide source points can be extracted, and the landslide dynamic runout process is simulated to obtain the dynamic seismic landslide hazard. Finally, the static and dynamic seismic landslide hazards are fused to obtain an optimized seismic landslide hazard. In September 2022, a strong Ms6.8 earthquake occurred in the eastern Tibetan Plateau, triggering thousands of landslides. Taking the 2022 Luding earthquake-induced landslide as a sample, the function relationship between seismic slope displacement and landslide occurrence probability is statistically modeled, which partly improves the traditional Newmark model. The optimized seismic landslide hazard evaluation of the Luding earthquake area is conducted, and then, the seismic landslide risk identification is completed by taking roads and buildings as hazard-affected bodies. The results show that the length of the roads facing very high and high seismic landslide risks are 3.36 km and 15.66 km, respectively, and the buildings on the Moxi platform near the epicenter are less vulnerable to seismic landslides. The research findings can furnish critical scientific and technological support for swift earthquake relief operations.

Landslides are the major problems of mountainous areas of Nepal basically due to its fragile geomorphology, intense rainfall, improper land management practices and rapid construction of hilly roads without applying necessary stabilization measures. There are huge loss of life and property, decline in ecosystem productivity and functionality and sedimentation on downstream areas due to frequent landslides. Multiple spatial factors like land use land cover, topography, road, drainage, geological setting and climatic factors like rainfall are found more associated with landslide occurrence and determine landslide susceptibility of the area. Understanding of landslide phenomenon and associated factors are crucial for adopting appropriate prevention, control and rehabilitation measures. This study was carried out in Singati sub-watershed of Sunkoshi River Basin with objectives to understand landslide hazards, associated factors and activities performed to minimize possible hazards with best strategy of minimizing hazards. Landslide assessments were made through identification and digitization of landslides using temporal Google image and field investigation. Where landslide hazard assessment and preparation of factor map was done by using GIS software and field observed data were analyzed and dimension of landslides were calculated. Along with, People perceptions on major effects of landslides on livelihood assets, were explore from associated household's questionnaire survey (n=60) using purposive sampling. And most causative factor of landslide on the perception of local people was calculated using nonparametric test (Friedman). From the field survey, a total of 46 landslides were surveys in different location of the study area. The total area of the landslide was found to be 4.77 km2. From the comparison matrix analysis using Friedman test, the study identified the main responsible factor for the occurrence of landslide are rural road, construction, slope factor rainfall and land use. The road factor up to 200 m area and 200–500 m distance from road covered the highest percentage of landslide hazard. Southeastern aspect with the slope class 30°–45° had the highest susceptibility to landslide. Dense forest was found to be more effected by landslide in comparison to other land use due to the construction of road in sloppy area inside the forest. Comparison the effects of landslide before and after the road construction about 80 percent of the respondent had the positive response on it. [ABSTRACT FROM AUTHOR]

The north-eastern border of CA represents the accretionary system developed during its continuous collision with Apulian block. The tardive oblique tectonic component is highlighted by pervasive NW-SE crustal transpressive left-lateral strike slip faults developed from the Upper Miocene to Quaternary tectonic stages. The seismotectonic and landslides Main Map represents the update of the main faults, the style of their arrangement and kinematics, the seismotectonic features and landslide area distribution with risk implications. Seismotectonics allows us to recognise a vertical crustal zonation with the distribution of earthquakes and their focal mechanism solution. The prevalent modality of ruptures depicts a mainly transcurrent and compressive solution in mid-lower crust portions respectively. This data, together with the historical seismicity analysis of the area, lead to consider the NW-SE strike-slip faults improved on the Main Map, as recent and tectonically active. The areal distribution of landslide and susceptibility of the area is due to the interaction between seismotectonic peculiarity, lithological typologies and fault zone architectures. Landslides and flood phenomena of this sector involve many municipalities, major and minor infrastructures and economic and social activities. The landslides and the faults have been identified, mapped and classified, originally at detail scale and, then, represented at 1:50,000 scale in the Main Map, included as supplementary material. The geo-structural and geomorphological data were analysed in a geographic information system allowing data management and implementation. The work presents an updated knowledge framework of risk conditions of the study zone, available to plan and reduce the fundamental elements that determine the landslide and seismic risks in this region. [ABSTRACT FROM AUTHOR]

Landslides, following floods and earthquakes, are one of the most significant natural hazards in the world, causing considerable human and financial losses annually. The Savadkooh region, located in the northern foothills of the Alborz Mountains, is susceptible to landslides due to climatic, geomorphological, geological, hydrological, and human-biological factors. The aim of this research is to conduct a risk analysis of landslides to identify development constraints in the physical structure of rural settlements in the Mazandaran Savadkooh region. To achieve this goal, 319 landslides were identified and analyzed based on records, field observations, satellite images, and other relevant data. Precipitation was found to be a key and central factor in the occurrence of more than 180 landslides in the region. In this study, the MARCOS model was used as one of the new multi-criteria decision-making methods for landslide hazard zoning in the area. Using GIS software and combining layers of slope, aspect, geology, land use, distance from roads, rivers, faults, precipitation, and earthquakes, a landslide hazard zoning map of the region was prepared in five classes: very low, low, moderate, high, and very high. The model output shows that over 63% of the area and 146 villages are located in zones with moderate to very high landslide hazard, mainly at elevations below 2000 meters, with slopes of 20 to 30 degrees, rich in clay minerals (Shemshak Formation, Sari Continental Formation, Quaternary alluvial deposits), and within 100 meters of roads and rivers. Validation of the MARCOS model using the density ratio method showed an accuracy rate of 89.1%, indicating a very good fit between the model results and field observations, as well as geotechnical and geophysical studies conducted in the area. The occurrence of 283 landslides in zones with moderate to very high hazard, 38 landslides in the built-up areas of villages, and 137 landslides within 300 meters of village settlements in these zones confirms the validity of the study's results. The findings can be used to develop comprehensive regional development plans, progress and settlement plans for rural areas, and rural settlement plans to identify areas at risk of landslides and to identify opportunities and constraints for the physical development of rural settlements.

Monitoring surface displacements of landslides is essential for evaluating their evolution and the effectiveness of mitigation works. Traditional methods like robotic total stations (RTSs) and GNSS provide high-accuracy measurements but are limited to discrete points, potentially missing the broader landslide’s behavior. On the contrary, laser scanner surveys offer accurate 3D representations of slopes and the possibility of inferring their movements, but they are often limited to infrequent, high-cost surveys. Monitoring techniques based on ground-based digital photogrammetry may represent a new, robust, and cost-effective alternative. This study demonstrates the use of multi-temporal images from fixed and calibrated cameras to achieve the 3D reconstruction of landslide displacements. The method presented offers the important benefit of obtaining spatially dense displacement data across the entire camera view and quasi-continuous temporal measurement. This paper outlines the framework for this prototyping technique, along with a description of the necessary hardware and procedural steps. Furthermore, strengths and weaknesses are discussed based on the activities carried out in a landslide case study in northeastern Italy. The results from the photo-monitoring are reported, discussed, and compared with traditional topographical data, validating the reliability of this new approach in monitoring the time evolution of surface displacements across the entire landslide area.

This study develops a model to assess building vulnerability across Xinxing County by integrating quantitative derivation with machine learning techniques. Building vulnerability is characterized as a function of landslide hazard risk and building resistance, wherein landslide hazard risk is derived using CNN (1D) for nine hazard-causing factors (elevation, slope, slope shape, geotechnical body type, geological structure, vegetation cover, watershed, and land-use type) and landslide sites; building resistance is determined through quantitative derivation. After evaluating the building susceptibility of all the structures, the susceptibility of each village is then calculated through subvillage statistics, which are aimed at identifying the specific needs of each area. Simultaneously, different landslide hazard classes are categorized, and an analysis of the correlation between building resistance and susceptibility reveals that building susceptibility exhibits a positive correlation with landslide hazard and a negative correlation with building resistance. Following a comprehensive assessment of building susceptibility in Xinxing County, a sample encompassing different landslide intensity areas and susceptibility classes of buildings was chosen for on-site validation, thus yielding an accuracy rate of the results as high as 94.5%.

Context: The landslides in Tijuana, Mexico, destroy a large number of structures and infrastructures each year, producing large losses in various sectors of the economy. Method: In this study, we carry out a quantitative assessment of the landslides hazard in a neighborhood of the city that was affected by a landslide in 2010 and shows signs of terrain instability that warn about the possibility of new landslides. The hazard was calculated using the spatial probability, based on the susceptibility of the terrain to landslides, and the temporal probability using a database of events that occurred at sites near the study area. We apply deterministic methods based on the analysis of slope stability to calculate susceptibility, and we estimate the temporal probability using probability models that consider the occurrence of independent random events. Results: it was obtained that more than 50% of the study area presents a high landslides hazard of for return periods of 5, 10, 15 and 20 years, and it is demonstrated that the seismicity, topography and geotechnical properties of the soils, they are the factors with the greatest influence on terrain instability. In addition, it was determined that the areas of potential landslides are in soils whose resistance has been reduced due to the presence of underground flows produced by the infiltration of water through existing cracks and fractures in the terrain. Conclusions: the application of the described procedure made it possible to quantify the landslides hazard in the Laderas de Monterrey neighborhood for four return periods and to identify the factors with the greatest influence on the occurrence of these phenomena. The results obtained are an important step to analyze and evaluate the risk that landslides represent for structures, infrastructures, and people exposed to the impact of these phenomena; and they are a valuable tool for decision-making related to risk management and the establishment of regulations on land use in the area.

Maps that attempt to predict landslide occurrences have essentially stayed the same since 1972. In fact, most of the geo-scientific efforts have been dedicated to improve the landslide prediction ability with models that have largely increased their complexity but still have addressed the same binary classification task. In other words, even though the tools have certainly changed and improved in 50 years, the geomorphological community addressed and still mostly addresses landslide prediction via data-driven solutions by estimating whether a given slope is potentially stable or unstable. This concept corresponds to the landslide susceptibility, a paradigm that neglects how many landslides may trigger within a given slope, how large these landslides may be and what proportion of the given slope they may disrupt. The landslide intensity concept summarized how threatening a landslide or a population of landslide in a study area may be. Recently, landslide intensity has been spatially modeled as a function of how many landslides may occur per mapping unit, something, which has later been shown to closely correlate to the planimetric extent of landslides per mapping unit. In this work, we take this observation a step further, as we use the relation between landslide count and planimetric extent to generate maps that predict the aggregated size of landslides per slope, and the proportion of the slope they may affect. Our findings suggest that it may be time for the geoscientific community as a whole, to expand the research efforts beyond the use of susceptibility assessment, in favor of more informative analytical schemes. In fact, our results show that landslide susceptibility can be also reliably estimated (AUC of 0.92 and 0.91 for the goodness-of-fit and prediction skill, respectively) as part of a Log-Gaussian Cox Process model, from which the intensity expressed as count per unit (Pearson correlation coefficient of 0.91 and 0.90 for the goodness-of-fit and prediction skill, respectively) can also be derived and then converted into how large a landslide or several coalescing ones may become, once they trigger and propagate downhill. This chain of landslide intensity, hazard and density may lead to substantially improve decision-making processes related to landslide risk. [ABSTRACT FROM AUTHOR]

The purpose of this study is to map and geographically locate areas with a high probability of natural events occurring such as "rockfall". In this context, a multi-method approach is proposed to characterize and evaluate the potential vulnerability of an unstable ground as well as rockfall risk, through morpho-tectonic, geological, and morphometric analysis integrated into a geographic information system (GIS). Several parameters such as slope, lithology, lineaments, morphology, land use, and rainfall have been integrated and indexed in a geographic information system to be able to develop the rockfall risk map that allowed us to detect and geographically delimit the unstable areas in the Korbous cliff. The studied area presents a contrasted territory, from both morphological and geological points of view. The steep slopes' rockfalls are quite frequent and constitute a potential risk to infrastructure and habitats at the bottom of slopes such as Korbous village, Ain Oktor, and MC 128 road. The proposed rockfall risk map, in this study, would serve as a guide and decision-support tool for the choice of preventive measures for reducing disaster risk (RDR). [ABSTRACT FROM AUTHOR]

Landslide hazard assessment is crucial for landslide monitoring and early warning. A novel method based on deep learning model for national-scale landslide hazard assessment was proposed in this study, which contains three stages: (1) landslide susceptibility analysis using three hybrid neural networks of convolutional neural network-simple recurrent unit (CNN-SRU), convolutional neural network-long short-term memory (CNN-LSTM), and convolutional neural network-gated recurrent unit (CNN-GRU); (2) landslide temporal probability prediction using the proposed spatiotemporal transformer (ST-transformer) to address the time uncertainty of rainfall threshold calculation in landslide temporal probability prediction and the matter without considering the geographical regional differences of landslide spatiotemporal probability weights; and (3) quantitative landslide hazard calculation with the preceding results using the improved landslide hazard formula. The validation of this method was conducted in conterminous United States, where the results of steps (1) and (2) demonstrated excellent performance compared with existing works. Consequently, the calculation derived from the previous two steps was effectively used for landslide hazard assessment using the improved landslide hazard formula, and its reliability was confirmed through the validation of actual landslide events. The proposed method is of practical significance for national-scale landslide hazard assessment. [ABSTRACT FROM AUTHOR]

Landslides are one of the most common geological hazards, with rainfall being the main trigger for their occurrence. In order to find the impact of rainfall conditions on slope stability and determine the rainfall threshold curve, the saturated-unsaturated seepage and stability analysis of three small slopes in Anhui province was carried out using FLAC2D 7.0 numerical simulation software, and the changing trend of safety factor of slopes with rainfall intensity and duration was obtained. The results show that the influence of rainfall on slopes is limited; the rainfall intensity corresponding to the minimum safety factor of slopes during the rainfall infiltration process is the ultimate rainfall intensity, and the longer the rainfall duration, the smaller the ultimate rainfall intensity becomes and tends to stabilize; the changes in pore pressure and saturation at the monitoring location on the slope further verify that the slope tends to become saturated under ultimate rainfall intensity, resulting in the minimum safety factor. Subsequent rainfall has little effect on the safety factor of slope. To be on the safe side, a critical safety factor of 1.15 was assumed, and the corresponding rainfall intensity was defined as the critical rainfall intensity. Similar to the trend of ultimate rainfall intensity, the longer the rainfall duration, the smaller the critical rainfall intensity becomes and tends to stabilize. The critical rainfall intensities for the three small slopes tend to stabilize at 13, 12, and 16 mm?d-1, respectively, with corresponding rainfall durations of 5, 9, and 12 d. It is indicated that under the influence of long-term early-stage rainfall, a small amount of rainfall can cause slope instability and failure. Additionally, the critical rainfall intensity data of these three small slopes(simulated data points for geological disaster rainfall)were used to fit the rainfall threshold curve, and the accuracy of the rainfall threshold curve was validated with 435 sets of historical rainfall data for geological disasters in Anhui province from 2008 to 2022. The verification results show that over 95% of actual disaster rainfall data can be predicted by the rainfall threshold curve. [ABSTRACT FROM AUTHOR]