Landslide Disaster Research Articles

Earthquake And Landslide Disaster Risk Assessment At The University Of Defense: A Preliminary Study

Earthquake And Landslide Disaster Risk Assessment At The University Of Defense: A Preliminary Study

Challenges for Sustainable Urban Planning: A Spatiotemporal Analysis of Complex Landslide Risk in a Latin American Megacity

This paper analyzes the spatiotemporal evolution of a complex landslide risk scenario in a Latin American megacity, underscoring the key challenges it poses for sustainable urban planning in such cities. This research draws upon multiple studies commissioned by the mayor’s office of the megacity of Bogota, Colombia, and utilizes aerial photographs and satellite imagery from diverse sensor types. The methodology used considered six spatiotemporal analysis scenarios: rural/natural, mining, urban, landslide risk, stabilization and environmental park, and informal reoccupation. The findings reveal a complex interplay between the megacity’s peripheral areas, which face constraints for human settlement, and their potential for construction material exploitation. This complex relationship was further compounded by weaknesses in planning and controlling peripheral occupations, coupled with a burgeoning demand for developable land in a landslide risk context (landslide area: 73 ha). The analysis scenarios highlighted the predominant use of a reactive urban planning approach that addressed events, changes, or problems after they had occurred, rather than proactively anticipating and preventing potential risks at the study site. The detected land-use transformations unveiled different historical moments, culminating in a landslide disaster (804 houses destroyed, 3000 families at risk). This catastrophe necessitated a radical and significant intervention, incurring substantial costs for the megacity administration (USD 26.05 million). This landslide was the largest recorded in the megacity and one of the most extensive in urban areas across Latin America.

Effectiveness of mangrove sword bean food bar addressed to older people of landslide disaster victims.

Older people require extra attention due to their reduced ability to prepare for disasters, as they adequately possess distinct needs. These groups necessitate uncomplicated, readily consumable, and palatable food options that fulfill their micronutrient needs. The objective of this research was to assess the effects of a snack bar enriched with api-api mangrove (Avicennia marina) and sword bean (Canavalia ensiformis) on the body weight and Body Mass Index (BMI) of older people individuals afflicted by a landslide event. A non-randomized pre-post-intervention study was undertaken, involving 31 senior participants. The intervention group consisted of 15 seniors who were provided with a mangrove sword bean snack bar, while the control group comprised 16 seniors who received a sword bean food bar during 15 days. All study participants received education on maintaining a balanced diet for older people individuals. The data analysis involved using univariate and bivariate analyses, explicitly applying the independent t-test and dependent t-test. In the hedonic evaluation, the mangrove sword bean food bar had superior average attributes in terms of scent, flavor, texture, and color compared to the sword bean food bar. The consumption of snack bars made from mangrove sword beans resulted in a significant rise in weight (0.2 kg), energy intake (240.8 kcal), protein content (5.8 g), carbohydrate content (40.06 g), and fat content (4.4 g). Carbohydrate can significantly increase weight in the treatment subjects. Furthermore, the provision of comprehensive nutrition education has the potential to enhance the post-study knowledge score, as seen by the observed increase of 40.6. A significant disparity was observed between the mean carbohydrate consumption and understanding of balanced nutrition among the intervention and control groups. Api-api mangrove sword bean snack bars have been identified as a viable and efficient substitute for emergency food provisions, particularly in disaster-stricken communities. These food bars have demonstrated a significant capacity to contribute to the weight gain of individuals within such groups, thus addressing the nutritional needs of impacted populations in the aftermath of natural calamities. Subsequent investigations may include employing pregnant women as participants to explore the issue above. Clinicaltrials.gov, identifier: NCT05897892.

A Finite Element Analysis-Unascertained Measure Theory-Based Hybrid Approach to Safety Assessment for Pipelines Subject to Landslide Disasters

Abstract Pipeline safety faces a prevalent threat in mountainous areas due to landslides. The advent of landslides introduces the risk of pipeline leaks or ruptures, posing a significant threat to the environment, with the potential for casualties. Throughout the occurrence of landslides, uncertainties abound, yet few studies have addressed the incorporation of uncertainties in assessing pipeline safety. This work proposes a novel hybrid approach to the safety assessment for pipelines under landslides. The use of finite element analysis (FEA) models the pipeline under the action of landslides. The numerical outcomes, combined with unascertained measure theory (UMT), develop a multi-indicator unascertained measure (UM) matrix. Random forest (RF) algorithm is employed to determine the weight of indicators in the matrix. The hybrid application of set pair theory and the UM evaluation vector finally determine the pipeline safety degree and level. The proposed methodology has been well-validated through a case study on an in-service pipeline. The results indicate that the case pipeline safety degree is 2.777, 2.132, 3.132, 3.904, and 2.240, respectively. The corresponding safety level is III, II, III, IV, and II, respectively, which is consistent with the pipeline's actual condition. Different from the conventional safety assessment approach, the proposed methodology demonstrates the enhanced effectiveness, facilitating a more precise evaluation of the pipeline's safety condition.

2D and 3D Modelling Electrical Resistivity Tomography (ERT) of Landslide Sliding and Weak Bedding Plane Along Mountain Road North Bengkulu-Lebong, Indonesia

The North Bengkulu-Lebong Mountain Road is prone to landslide disasters due to its geological susceptibility to land movement. This study aims to measure and assess the sliding plane on the mountain road, particularly in the layer with a soft rock structure, such as clay rock. The study utilizes 2D and 3D Electrical Resistivity Tomography (ERT) methods with the Wenner-Schlumberger configuration to measure the resistivity of the rock layers.The research includes one 2D measurement point and one 3D ERT measurement point, estimating actual resistivity values in each rock layer. Our results identify triggering and controlling factors for landslide disasters in the research area. The geological conditions consist of layers of clay (200-500 Ωm), wet clay (500-900 Ωm), dry clay (1000-3000 Ωm), weathering clay (500-1000 Ωm), aquifer (10-65 Ωm), perched aquifer (100-200 Ωm), weathering igneous rock (>10000 Ωm), and massive intrusive rock (>20000 Ωm). These geological conditions significantly influence the strength of landslide materials, with the sliding of the soft rock layer causing landslides and resulting in a large volume of landslide material. Other contributing factors to landslides in this location include slope, topography, and hydrology, with extreme slopes ranging from 33° to 55°, making it a very steep area with high potential for landslides.

Spatial distribution of near-fault landslides along Litang fault zones, eastern Tibetan Plateau

Active fault zones are areas impacted by intense tectonic activity, where geohazards such as landslides occur and their distribution characteristics vary across segments. Using the Litang fault zone in the eastern Tibetan Plateau as an example, this study cataloged landslides within a 10 km range on both sides of the fault zone. The Litang fault zone was divided into four sections based on landform characteristics and the spatial distribution of active faults. A comprehensive analysis was conducted on the relationship between landslide distribution and topography, lithology, and active faults in different sections. Additionally, the study employed a random forest model to compare landslide susceptibility between the whole-region and its sub-regions. The results show that lithology and topography significantly influence the distribution of landslide types. The Upper Triassic sandstone, Slate exhibit more debris flows in areas with slopes ranging from 5° to 35°, while slopes >35° in the Upper Triassic sandstone, Slate are prone to unstable slopes. Rock avalanche occur in Upper Triassic sandstone, Slate, and Quaternary sand and gravel. Active faults play a key role in control ling landslides distribution through distance, hanging wall, locked segment, and direction effects. The number of landslides is positively correlated with the activity of faults. Additionally, the dip angle and motion characteristics of faults have significant influence on the distribution of landslides. The results of landslide susceptibility evaluation show that sub-region models have higher accuracy than the whole-region model. This study provides a new method for exploring the spatial distribution of landslides and can provide scientific reference for reducing landslide disasters in active fault zones.

POTENCY OF CARBON STORAGE AND CO2 ABSORPTION AT PT TIRTA INVESTAMA, SUBANG DISTRICT

The Biodiversity Park covering an area of ±5,800 Ha provides conservation functions in the work area of PT Tirta Investama Plant Subang and for the surrounding community which has a sloping to very steep topography. A landslide disaster occurred in the company's work area in Block II at the beginning of 2024 due to increased rainfall of 17.6 mm/hour caused by global warming. Biodiversity Park also provides the function of reducing greenhouse gas emissions by storing and absorbing CO2 by plants in the area to reduce global warming through photosynthetic activity assisted by energy from sunlight. The research method is to carry out a census inventory of mahogany plants in Block II. This research aims to determine carbon storage and CO2 uptake in mahogany plants. The research show that 412 mahogany plants can store 26,364 tonnes/ha of carbon in their stems or equivalent to an equivalent CO2 uptake of 96,755 tonnes/ha.

Analysis of Existence and Faults Impact on Geological Disasters Using GGMPlus Data

The existence of faults can trigger various geological natural disasters because faults will react when an earthquake occurs and volcanic activity occurs, causing effects in the form of landslides, subsidence, ground movements, and other geological disasters. This research aims to analyze the existence and impact of local faults on geological disasters around the research location using GGMPlus data. A derivative filter is used to get FHD and SVD maps based on the gravity anomaly map. Fault analysis was carried out using a graph from the FHD and SVD map incisions, which were then correlated with each other. The incision graph of the meeting point between the maximum FHD value and the zero SVD value will be interpreted as a fault structure. The results show that there were several fault indication points; these points were then drawn straight lines to get the lineaments of the faults. The fault lineaments with the location of the landslide and subsidence events are correlated so that it becomes evident that the subsidence and landslide disaster in the Brau Hamlet, Batu City, area can be associated with local faults. Based on several previous research on determining faults in coastal areas, it is known that the areas crossed by the Palu-Koro fault have experienced many disasters, such as landslides, land movement and liquefaction. The existence of local faults in an area can increase the impact of damage when natural disasters such as earthquakes and landslides occur.

Landslide hazard assessment and agricultural vulnerability using a geospatial approach

The village of Cukilan, Semarang Regency, Indonesia, is predominantly utilized for agricultural purposes, facilitated by its high rainfall suitable for various crops. Despite the benefits it provides to farmers, the elevated rainfall also poses natural disaster risks, particularly landslides, which can adversely affect surrounding communities. This study aims to map landslide potentials and evaluate their impacts on the agricultural sector in the Cukilan Village, Semarang Regency. The research methodology encompasses a literature review focusing on landslide potential estimation and field survey. The literature review aims to obtain landslide potential distribution maps compiled by DVMBG, considering rainfall, slope, geology, land use, and soil types. Field surveys validate conditions based on landslide potential estimations, involving random soil sampling and analyzing parameters like permeability, texture, bulk density, depth, and surface density. The research findings reveal the impact of landslide potential on the agricultural sector and the mapping of landslide potential areas in Cukilan Village, depicting various risk levels: very high (0.71% of total area, covering 5 ha), high (13.24%, 93 ha), moderate (56.55%, 397 ha), and low (29.48%, 207 ha). Based on these findings, it is evident that managing landslide disaster risks in agricultural development in the area is crucial, including the implementation of safer land use planning and appropriate mitigation strategies.

Landslide Susceptibility Zoning: Integrating Multiple Intelligent Models with SHAP Analysis

In this study, we aim to delineate landslide susceptibility zones within Dien Bien province, Vietnam, leveraging the capabilities of various machine learning models including Light Gradient Boosting Machine (LGBM), K-Nearest Neighbors (KNN), and Gradient Boosting (GB). Harnessing a dataset comprising 665 data points and encompassing 14 influential factors such as slope, aspect, curvature, elevation, geological composition, Normalized Difference Vegetation Index (NDVI), and proximity to geological features like faults, rivers, and roads, a comprehensive database for landslide modeling was constructed. The analysis entailed rigorous evaluation and comparison of model accuracy employing established statistical metrics, notably Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC). The findings underscore the efficacy of the Light Gradient Boosting Machine model, exhibiting superior performance with an AUC score of 0.85, surpassing both the Gradient Boosting model (AUC = 0.81) and the K-Nearest Neighbors model (AUC = 0.79). Notably, the Light Gradient Boosting Machine model emerges as a promising tool for precise landslide prediction within the study area, offering significant potential for the creation of a robust landslide susceptibility map. The resulting spatial forecast map for Dien Bien province holds considerable utility for informing land use planning initiatives aimed at mitigating the impact of landslide disasters in the region. Moreover, the application of SHAP (Shapley Additive explanation) values to quantify the contribution of each factor to landslide susceptibility prediction, offering novel insights into model interpretation and feature importance. The resulting spatial forecast map holds significant implications for land use planning and disaster mitigation efforts in Dien Bien province, showcasing the potential of advanced machine learning techniques in enhancing landslide risk management strategies.

Influence of Calculation Parameters on the Slope Stability of the Historical Rasos Cemetery in Vilnius (Lithuania)

Many objects of cultural and religious importance are located on naturally or artificially shaped hills. In such cases, the stability of the slopes determines both the safety of users and the facilities themselves and thus the preservation of cultural heritage. The analysis of the slope stability requires the assessment of the soil shear strength, defined as the ratio of resistance forces to driving forces. An important issue in the slope stability analysis is the proper determination of soil mechanical parameters, including their changes due to soil moisture. This paper presents an assessment of the slope stability of the Rasos Cemetery in Vilnius (Lithuania), where, due to a partial slope sliding, some of the tombstones were destroyed by being covered with soil. An analysis of the slope stability (factor of safety) was performed for two cross-sections using six calculation schemes. In each of them, calculations were carried out for three groups of soil parameters and for four design approaches (characteristic values, DA2, DA3a, and DA3b in accordance with the geotechnical standard applicable in the European Union—Eurocode 7: Geotechnical design). For the calculation approach (DA3a) for different groups of soil parameters, the values of the slope stability factors of safety were practically below 1.0. If the value of the factor of safety is less than 1.0, the slope is unstable. In the range of values 1.0–1.3, there is a serious risk of slope instability, and only when the factor of safety value reaches above 1.3 is the slope classified as stable. The comparison of the slope stability factors obtained with different design approaches (in relation to the DA3a) shows that the most unfavorable stability factor is approximately 43% lower than the result obtained from the characteristic values, approximately 21% lower than the result obtained using the DA2 design approach, and approximately 24% lower than the result obtained using the DA3b design approach. The analytical and numerical method (GEO5) analysis showed that, regardless of the adopted calculation approach, the required slope stability factor was not obtained. The article shows that selecting the correct geological cross-section to determine the critical slope slip surface and adopting the relevant design approach is crucial for slope sustainability. Based on the analysis, a proprietary solution for the construction work was proposed, which will ensure both the full stability of the slope and the safety of all graves and consequently landslide disaster prevention.

Active thickness estimation and failure simulation of translational landslide using multi-orbit InSAR observations: A case study of the Xiongba landslide

The active thickness of the translational landslides plays a pivotal role in evaluating its hazards and simulating its instability. Existing techniques have difficulties in estimating the accurate active thickness due to the limitations of observation conditions and imaging geometry, leading to deviations in failure simulations. To overcome these challenges, this study proposes an enhanced method that utilizes multi-orbit Interferometric Synthetic Aperture Radar (InSAR) observations to estimate the active thickness of the translational landslides and subsequently conduct more accurate instability simulations. The method involves integrating multi-orbit InSAR imaging parameters with the spatial geometry of the landslide to establish a slope coordinate system. This system enables the projection of one-dimensional InSAR Line Of Sight (LOS) displacements onto the three-dimensional displacements of the landslide. Subsequently, the active thickness is estimated by combining InSAR three-dimensional displacements with the mass conservation method. Finally, the estimated thickness is incorporated into the geological model construction to simulate the dynamic movement of the landslide. The method was applied to the Xiongba translational landslide in Gongga County, Tibet Autonomous Region, China. The results show that the deformation is mainly concentrated at its forefront, with maximum three-dimensional deformation rates of 4.7 m/a, 2.3 m/a, and 1.24 m/a. The landslide encompasses an estimated area of around 5.33 square kilometers, and its active thickness varies from 0 to 106.59 m. The maximum displacement distance reaches 1469.76 m, with a peak velocity of 60.37 m/s. The proposed method provides scientific support for assessing, analyzing, and preventing landslide disasters.

ANALYSIS OF LANDSLIDE SUSCEPTIBILITY IN KLATEN REGENCY

Landslide disasters are frequently occurring events in Indonesia. The northern part of Klaten Regency, situated on the slopes of Mount Merapi, and the southern part, which directly borders limestone hills, are vulnerable to landslides due to their elevated terrain. This research aims to investigate the role of Geographic Information Systems (GIS) in analyzing, mapping, and identifying areas prone to landslide disasters. Mapping landslide susceptibility as a GIS application aims to be a disaster mitigation effort, thereby minimizing the resulting impacts and losses. The mapping is conducted based on the Puslattinak method, using several parameters such as rainfall, slope, rock types, land use, and soil types. This mapping employs a weighted multi-level analysis method, where each parameter has a different weight depending on its influence on landslide disasters. The results of this research include the Landslide Susceptibility Map of Klaten Regency in 2022. According to the research findings, Klaten Regency is divided into three susceptibility classes: low (17,868.23 hectares), medium (41,494.22 hectares), and high (10,533.96 hectares), with rainfall intensity being the most influential parameter

Dams overtopping scenarios from catastrophic landslides in mountains’ headwaters Case study in Kobe City, Japan

As a Mw 8.0 Nankai Trough Earthquake is predicted with an 80% probability of occurrence within the next 30 years, the efficiency of check dams in the mountains above Kobe City is a crucial question when considering co-seismic landslide disaster risk management. In the present contribution the author aimed to define which subsection of the Sumiyoshigawa watershed may be more prone to generate impacts in downstream Kobe City from catastrophic landslides in the headwaters. For this purpose, the present state of the check dams network was analysed from the 2018 LiDAR (Light Detection and Ranging) data, considering the progressive infilling of the structures. As a result, the capacity of the dams in 2018 dropped by about 1/10 of the original designed capacity, arguably because of the heavy rainfall events in 2014 and 2018. Despite this evolution, however, landslides > 20,000 m3 starting from only one tributary can fill all the dams and flow downstream. From this data, it is possible to prioritize dam curation programs, especially because population ageing and shrinking is reducing the manpower and the funds available to maintain the check dams.

Efforts to Increase the Capacity of Sukorejo Village, Semarang City Community in Facing Landslide Disasters Through the Preparation of Evacuation Standard Operating Procedures (SOPs)

This study identified the problem of landslide disasters that often occur in Sukorejo Village, Gunungpati District, Semarang City. Sukorejo village belongs to the high ground movement zone which has a high degree of vulnerability to soil movement. The purpose of the study was to determine efforts to increase the capacity of the community in facing landslide disasters through the preparation of evacuation standard operating procedures (SOPs). The data collection of this study used interview, observation, documentation, and geographic information systems (GIS) methods. Data analysis is carried out with the approach of spatial analysis and qualitative descriptive analysis. The results showed that the preparation of evacuation SOPs is very important to increase the capacity of the community during landslide emergency response. The recommendations given are the need to add an Early Warning System (EWS) tool, install evacuation route signs, and gathering points in landslide-prone areas. In addition, the community also needs to increase awareness and preparedness in the face of possible landslides. This research contributes to improving understanding of landslide disaster mitigation efforts and can be followed up by assessing community capacity and evaluating future evacuation SOPs.

Deep Learning-Based Landslide Recognition Incorporating Deformation Characteristics

Landslide disasters pose a significant threat, with their highly destructive nature underscoring the critical importance of timely and accurate recognition for effective early warning systems and emergency response efforts. In recent years, substantial advancements have been made in the realm of landslide recognition (LR) based on remote sensing data, leveraging deep learning techniques. However, the intricate and varied environments in which landslides occur often present challenges in detecting subtle changes, especially when relying solely on optical remote sensing images. InSAR (Interferometric Synthetic Aperture Radar) technology emerges as a valuable tool for LR, providing more detailed ground deformation data and enhancing the theoretical foundation. To harness the slow deformation characteristics of landslides, we developed the FCADenseNet model. This model is designed to learn features and patterns within ground deformation data, with a specific focus on improving LR. A noteworthy aspect of our model is the integration of an attention mechanism, which considers various monitoring factors. This holistic approach enables the comprehensive detection of landslide disasters across entire watersheds, providing valuable information on landslide hazards. Our experimental results demonstrate the effectiveness of the FCADenseNet model, with an F1-score of 0.7611, which is 9.53% higher than that of FC_DenseNet. This study substantiates the feasibility and efficacy of combining InSAR with deep learning methods for LR. The insights gained from this research contribute to the advancement of regional landslide geological hazard monitoring, identification, and prevention strategies.

Research on Deformation Characteristics of Pipelines Under Landslide Action

Landslide disasters often occur along oil and gas pipelines, seriously affecting the safety of oil and gas transportation. Therefore, it is urgent to study the deformation and damage characteristics of pipelines under landslide disaster conditions. This article takes oil and gas pipelines under landslide disaster conditions as the research object, and based on numerical simulation methods, focuses on the influence of different landslide parameters on pipeline deformation and damage. The research results indicate that the length, width, height, and slope of landslides, as well as the relative position of pipeline landslides, have a significant impact on pipeline deformation and damage; When the oil and gas pipeline is laid in the middle of the landslide, the response of pipeline deformation and failure to slope sliding is most significant; The prediction results of the pipeline landslide geological hazard warning model are highly consistent with the original data and have wide applicability. The research results are of great significance for monitoring and evaluating geological hazards of pipeline landslides, and reducing the risk of geological hazards of pipeline landslides in the monitoring area.

Inventory of Landslides in the Northern Half of the Taihang Mountain Range, China

The Taihang Mountains are a critical mountain range and geographical boundary in eastern China. Landslide disasters are particularly common in this region and usually cause serious casualties and property damage. However, previous landslide inventories in the region are limited and lack comprehensive landslide cataloguing. To address this gap, the northern half of the Taihang Mountain Range was selected for this study. A landslide database for the area was constructed using multi-temporal high-resolution optical imagery from the Google Earth and human–computer interactive visual interpretation technology. The results indicate that at least 8349 landslides have occurred in the Taihang Mountain Range, with a total landslide area of about 151.61 km2. The size of the landslides varies, averaging about 18,159.23 m2, with the largest landslide covering 2.83 km2 and the smallest landslide only 5.95 m2. The significance of this study lies in its ability to enhance our understanding of the distribution of landslides in the northern half of the Taihang Mountains. Furthermore, it offers valuable data references and supports for landslide assessment, early warning systems, disaster management, and ecological protection efforts.

Assessment of factors causing landslides using the Analytical Hierarchy Process (AHP) method

Landslides are Indonesia's second most common disaster in the last ten years. Landslides cause losses, reaching hundreds of billions and threatening human safety. For this reason, it is necessary to take action to reduce the negative impact of landslides. Physical and non-physical mitigation can occur before, during, and after a disaster. The most essential thing in disaster mitigation is knowing the major factors that cause landslides. This research aims to analyze the major and minor factors that cause landslides using the Analytical Hierarchy Process (AHP) and the Likert scale. Respondents in this research are experts in disasters, especially landslides—respondents from universities in Indonesia, practitioners, and people involved in disaster mitigation. Validity and reliability tests were carried out on each question used in the questionnaire. The research results show that the landslide disaster was caused by a disruption in balance that occurred due to internal and external disturbance factors. The major external factors that cause slope failures are the cutting of hills and changes in land use to built-up areas. In contrast, the major internal factors that trigger landslides are heavy rainfall and steep topographic conditions. The results of this research in the form of weight and scoring values for each factor causing landslides can be used as a reference for mapping landslide areas to identify areas with the potential for landslides.

Socialization and Making of Landslide Disaster Warning Equipment in Gentan Village, Sukoharjo

Abstract: This research aims to enhance the awareness and consciousness of the community regarding the potential disasters that may occur in Gentan Village. Various types of natural disasters frequently occur in Gentan Village, one of which is landslides. In this study, a device was created and installed in landslide-prone areas of Gentan Village. The purpose of this device is to provide notifications in the form of a siren when a landslide disaster occurs, with the hope that it will be beneficial to the surrounding community. In the implementation of this activity, Badan Penanggulangan Bencana Daerah (BPBD) participated in providing information about natural disasters and how to mitigate them. BPBD and the local community also supported and actively participated in the installation of landslide warning devices in landslide-prone areas. The impact of this activity has been able to increase the knowledge and awareness of the Gentan Village community regarding landslide disasters. The landslide warning devices are expected to be replicated and further developed to become more effective. Keywords: disaster, warning signal, technology