Search Results (51)

Landslides represent a recurrent hazard in tropical mountain environments, where rapid urbanization and extreme rainfall amplify disaster risk. The Sentani region of Papua, Indonesia, is highly vulnerable, as demonstrated by the catastrophic debris flows of March 2019 that caused fatalities and widespread losses. This study developed high-resolution landslide susceptibility maps for Sentani using an ensemble machine learning framework. Three base learners—Random Forest, eXtreme Gradient Boosting (XGBoost), and CatBoost—were combined through a logistic regression meta-learner. Predictor redundancy was controlled using Pearson correlation and Variance Inflation Factor/Tolerance (VIF/TOL). The landslide inventory was constructed from multitemporal satellite imagery, integrating geological, topographic, hydrological, environmental, and seismic factors. Results showed that lithology, Slope Length and Steepness Factor (LS Factor), and earthquake density consistently dominated model predictions. The ensemble achieved the most balanced predictive performance, Area Under the Curve (AUC) > 0.96, and generated susceptibility maps that aligned closely with observed landslide occurrences. SHapley Additive Explanations (SHAP) analyses provided transparent, case-specific insights into the directional influence of key factors. Collectively, the findings highlight both the robustness and interpretability of ensemble learning for landslide susceptibility mapping, offering actionable evidence to support disaster preparedness, land-use planning, and sustainable development in Papua. Full article

A landslide disaster is one of the many natural disasters that often occur in Indonesia. This disaster is one of the difficult to avoid disasters, so it often causes fatalities and large material losses. Currently, mitigation systems for landslide disasters are still less effective in their use. Early warning systems that can give information about the landslide through smartphones could be the best solution for this digital era, because society generally has smartphones and is connected through the internet. The early warning system also demanded the ability to decide the landslide status. Fuzzy logic is one of many types of artificial intelligence used as a decision support system, which is similar to human logic. Therefore, it is necessary to build an early warning system against landslides based on the Internet of Things (IoT) that can determine the status of landslides that occur based on the soil slope using the MPU6050 accelerometer sensor and moisture data using the soil moisture sensor. This system can later monitor the slope and moisture data of the soil and can transmit landslide status on smartphone applications connected to the internet. The result of this research is an IoT-based landslide early warning system that can transmit landslide and soil moisture data and transmit landslide status in the form of push notifications on smartphones using the Blynk application. Full article

Hurricane Helene made landfall near Perry (Latitude 30.1 N) in the Big Bend area of Florida with a central pressure of 939 hPa. It moved northwards creating devastating damage and loss of life; however, the greatest damage and number of fatalities occurred well to the north around the City of Asheville (Latitude 35.6 N) where extreme rainfall fell and some of the strongest wind gusts were reported. This paper describes the change in the hurricane’s structure as it tracked northwards, how it gathered tropical moisture from the Atlantic and a turning wind profile between the 850 hPa and 500 hPa elevations, which led to such extreme rainfall. This turning wind profile is shown to be associated with extreme rainfall and loss of life from drowning and landslides around the globe. The area around Asheville suffered 157 fatalities, which is a considerable proportion of the 250 fatalities so far recorded in the whole United States from Helene. This is of extreme concern and should be investigated in detail as the public expects the greatest impact from hurricanes to be confined to coastal areas near the landfall site. It is another example of increased death tolls from tropical cyclones moving inland and generating heavy rainfall. As the global population increases and inland centres become more urbanised, runoff from such rainfall events increases, which causes greater devastation. Full article

Landslides in Ecuador are one of the most common deadly events in natural hazards, such as the one on 26 March 2023. A large-scale landslide occurred in Alausí, Chimborazo province, causing 65 fatalities and 10 people to disappear, significant infrastructural damage, and the destruction of six neighborhoods. This study presents a detailed case analysis of the anthropogenic factors that could have contributed to the instability of the affected area. Field investigations and a review of historical, geological, and social information are the basis for analyzing the complex interactions between natural and human-induced conditions. Key anthropogenic contributors identified include unplanned urban expansion, ineffective drainage systems, deforestation, road construction without adequate geotechnical support, and changes in land use, particularly agricultural irrigation and wastewater disposal. These factors increased the area’s susceptibility to slope failure, which, combined with intense rainfall and past seismic activity, could have caused the rupture process’s acceleration. The study also emphasizes integrating geological, hydrological, and urban planning assessments to mitigate landslide risks in geologically sensitive regions such as Alausí canton. The findings conclude that human activity could be an acceleration factor in natural processes, and the pressure of urbanization amplifies the consequences. This research underscores the importance of sustainable land management, improved drainage infrastructure, and land-use planning in hazard-prone areas. The lessons learned from Alausí can inform risk reduction strategies across other mountainous and densely populated regions worldwide, like the Andean countries, which have similar social and environmental conditions to Ecuador. Full article

This study presents numerical simulations of the Aysén tsunami, which occurred on 21 April 2007. The tsunami was triggered by hundreds of landslides caused by a magnitude 6.2 earthquake. With an estimated wave height of 50 m at the northern tip of the Mentirosa Island, the event resulted in 10 fatalities and the destruction of multiple salmon farms along the fjord. We employed the NHWAVE and FUNWAVE-TVD numerical software to conduct a series of simulations using various landslide configurations and two approaches to model landslide motion: a viscous flow and a solid slide governed by Coulomb friction. The numerical results indicate that the solid landslide model without basal friction provides the most accurate representation of the measured in situ run-up heights and generates the largest inundation areas. Furthermore, the simulation results show that the arrival time of the tsunami waves was approximately 600 s. Our findings indicate that the volume of the landslide is the most critical factor in determining tsunami wave heights. Additionally, the Coulomb friction angle is another significant parameter to consider in the modeling process. Full article

In subtropical regions, typhoons and tropical storms can generate massive rainstorms resulting in thousands of landslides, often termed as Multiple-Occurrence of Regional Landslide Events (MORLE). Understanding the hazards, their location, and their triggering mechanism can help to mitigate exposure and potential impacts. Extreme rainfall events and earthquakes frequently trigger destructive landslides that cause extensive economic loss, numerous fatalities, and significant damage to natural resources. However, inventories of rainfall-induced landslides suggest that they occur frequently under climate change. This study proposed a semi-automated time series algorithm that integrates Sentinel-2 and Integrated Multi-satellite Retrievals for Global Precipitation Measurements (GPM-IMERG) data to detect rainfall-induced landslides. Pixel-wise NDVI time series data are analyzed to detect change points, which are typically associated with vegetation loss due to landslides. These NDVI abrupt changes are further correlated with the extreme rainfall events in the GPM-IMERG dataset, within a defined time window, to detect RIL. The algorithm is tested and evaluated eight previously published landslide inventories, including both those manually mapped and those derived from high-resolution satellite data. The landslide detection yielded an overall F1-score of 0.82 and a mean producer accuracy of 87%, demonstrating a substantial improvement when utilizing moderate-resolution satellite data. This study highlights the combination of using optical images and rainfall time series data to detect landslides in remote areas that are often inaccessible to field monitoring. Full article

Landslide risks in open-pit mine areas are heightened by artificial slope modifications necessary for mining operations, endangering human life and property. On 22 February 2023, a catastrophic landslide occurred at the Xinjing Open-Pit Coal Mine in Inner Mongolia, China, resulting in 53 fatalities and economic losses totaling 28.7 million USD. Investigating the pre-, co-, and post-failure deformation processes and exploring the potential driving mechanisms are crucial to preventing similar tragedies. In this study, we used multi-source optical and radar images alongside satellite geodetic methods to analyze the event. The results revealed pre-failure acceleration at the slope toe, large-scale southward displacement during collapse, and ongoing deformation across the mine area due to mining operations and waste accumulation. The collapse was primarily triggered by an excessively steep, non-compliant artificial slope design and continuous excavation at the slope’s base. Furthermore, our experiments indicated that the commonly used Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) significantly underestimated landslide deformation due to the maximum detectable deformation gradient (MDDG) limitation. In contrast, the high-spatial-resolution Fucheng-1 provided more accurate monitoring results with a higher MDDG. This underscores the importance of carefully assessing the MDDG when employing InSAR techniques to monitor rapid deformation in mining areas. Full article

Snow avalanche is one of the major natural hazards in the mountain region, yet it has received less attention compared to other mountain hazards, such as landslides, floods, and droughts. After a comprehensive overview of snow avalanche hazards in Tibet area, the spatial distribution and main driving factors of snow avalanche hazards in the high mountain region in Tibet were presented in the study first. Snow avalanche-prone areas in Tibet were then mapped based on the snow cover distribution and DEM data and were validated against in situ observations. Results show that there are the highest frequencies of avalanche occurrences in the southeastern Nyainqentanglha Mountains and the southern slope of the Himalayas. In the interior of plateau, avalanche development is constrained due to less precipitation and much flatter terrain. The perennially snow avalanche-prone areas in Tibet account for 1.6% of the total area of the plateau, while it reaches 2.9% and 4.9% of the total area of Tibet in winter and spring, respectively. Snow avalanche hazards and fatalities appear to be increasing trends under global climate warming due to more human activities at higher altitudes. In addition to the continuous implementation of engineering prevention and control measures in pivotal regions in southeastern Tibet, such as in the Sichuan–Tibet highway and railway sections, enhancing monitoring, early warning, and forecasting services are crucial to prevent and mitigate avalanche hazards in the Tibetan high mountain regions, which has significant implications for other global high mountain areas. Full article

The Himalayan country of Nepal is vulnerable to landslides, earthquakes, and fires. Its inhabitants need to be empowered on how to react in emergencies to prevent fatalities and respond to crises efficiently while promoting longer-term sustainability and resilience. This research project, a collaborative effort involving teachers, students, and researchers, highlights the design and implementation of games for disaster risk reduction tested in remote schools. Three interactive games were developed using an iterative game design process and testing in workshops aiming to ensure the inclusivity and diversity of the project. The games targeted preparedness and response to landslides, earthquakes, and house fires. The outcome has proven that the game-based approach to teaching and learning is crucial in empowering underserved school children often left out in formal and informal disaster management processes. This study has shown that game-based learning of disaster preparedness and response effectively empowers resource-deficient communities and regions of the Global South. Full article

Landslides pose a significant threat worldwide, leading to numerous fatalities and severe economic losses. The city of Manizales, located in the Colombian Andes, is particularly vulnerable due to its steep topography and permeable volcanic ash-derived soils. This study aims to assess landslide hazards in Manizales by integrating shallow planar and deep-seated circular failure mechanisms using physics-based models (TRIGRS and Scoops3D). By combining hazard zonation maps with rainfall thresholds calibrated through historical data, we provide a refined approach for early warning systems (EWS) in the region. Our results underscore the significance of the landslide hazard maps, which combine shallow planar and deep-seated circular failure scenarios. By categorizing urban areas into high, medium, and low-risk zones, we offer a practical framework for urban planning. Moreover, we developed physics-based rainfall thresholds for early landslide warning, simplifying their application while aiming to enhance regional predictive accuracy. This comprehensive approach equips local authorities with essential tools to mitigate landslide risks, refine hazard zoning, and strengthen early warning systems, promoting safer urban development in the Andean region and beyond, as the physics-based methods used are well-established and implemented globally. Full article

Human impact by floods and landslides (FLs) is a significant concern, necessitating a deeper understanding to implement effective reduction measures, in line with the Sendai Framework for Disaster Risk Reduction’s goal to reduce disaster mortality between 2020 and 2030. This study examines the evolution of human interaction with FLs over the past 70 years in Calabria, Italy. By systematically analyzing regional newspapers and historical archives from 1951–1960 and 2011–2020, a database was created documenting fatalities, injuries, and the involvement of people in FL incidents. For each victim, the database includes demographic details, accident time and place, circumstances of death or injury, and whether the victim’s behavior was hazardous or protective. Results indicate a drastic reduction in both the total number of fatalities (196 versus 20) and high mortality events from 1951–1960 to 2011–2020 (6 versus 1). However, the number of people involved in incidents has increased (202 versus 1102), although this may be partly due to improved dissemination of information. Changes in population habits and the construction of more robust houses have significantly reduced high-fatality events, enhancing security. The study highlights the importance of data collection for developing locally tailored risk reduction strategies, increasing community resilience by addressing specific vulnerabilities and strengths. Full article

Drawing upon a comprehensive global database of landslides and utilizing high-resolution IMERG satellite precipitation data, this study investigates the spatial and temporal variations of landslide occurrences across the member states of the Association of Southeast Asian Nations (ASEAN). This study constructs a region-specific, graded warning system by formulating an average effective intensity–duration (I–D) rainfall threshold curve for each ASEAN member. Examination of 1747 landslide events spanning from 2006 to 2018 illustrates a significant association between the frequency of landslides in ASEAN regions and the latitudinal movement of local precipitation bands. Incidences of landslides hit their lowest in March and April, while a surge is observed from October to January, correlating with the highest mortality rates. Geographical hotspots for landslide activity, characterized by substantial annual rainfall and constrained landmasses, include the Philippine archipelago, Indonesia’s Java Island, and the Malay Peninsula, each experiencing an average of over 2.5 landslides annually. Fatalities accompany approximately 41.4% of ASEAN landslide events, with the Philippines and Indonesia registering the most substantial numbers. Myanmar stands out for the proportion of large-scale landslide incidents, with an average casualty rate of 10.89 deaths per landslide, significantly surpassing other countries in the region. The I–D rainfall threshold curves indicate that the Philippines experienced the highest precipitation levels before landslide initiation, whereas Myanmar has the threshold set at a considerably lower level. Full article

Landslides are natural disasters with a high socio-economic impact on human societies due to the considerable number of fatalities and the destruction of infrastructure that they cause. A comprehensive landslides inventory is vital for reducing this impact as it can be used in landslides susceptibility studies for the identification of the subregions of an area that are most prone to landslides for the evaluation of the landslide precipitation activation thresholds, and subsequently for the determination of the most suitable precautionary measures. Nowadays, remote sensing techniques are widely used by scientists for creating landslide inventories as they can be rapidly applied to identify landslides along with their spatial characteristics. Nevertheless, besides these characteristics, a comprehensive inventory must also include the time of their activation and the factors that led to their activation. These elements can be quite difficult to specify, especially in areas where official landslide data do not exist, such as in countries that do not have a published national landslides inventory. The objective of this research study is to provide a framework for the creation of a comprehensive landslides inventory by combining open access or publicly available data with remote sensing data and techniques. The Chania regional unit in the western part of Crete Island, Greece, was selected as the study area. Our study presents how a complete landslides inventory, consisting of 236 landslides, was established based on differential interferometric synthetic aperture radar (DInSAR) techniques and open access or publicly available data. This framework can significantly contribute to scientific research on landslide susceptibility in countries that lack a comprehensive landslides inventory. Moreover, it highlights the potential of remote sensing techniques and open access data in improving our understanding of landslide activation mechanisms. Full article

Two of the eight main soil degradation processes with which soils worldwide are confronted are soil erosion and landslides. Specifically, landslides are a major threat in particular areas across Europe, often leading to serious impacts on population, property, and infrastructure. Regarding the abovementioned processes, the case study of the fatal Mandra flash flood (November 2017) in the Attica Region (Greece), which caused 24 deaths, and much infrastructure and building damage, is presented with the intention of assessing the relationship between soil erosion and landslide incidents. Investigations were executed from 2018 to 2022, and their outcomes were taken into consideration by the Technical Authority of the Attica Region. Soil erosion lines were delineated in a GIS and were validated using a previously generated regional Web-GIS landslide susceptibility map. The study presents soil erosion types from the Mandra fatal flash flood event and correlates them with already existing landslide susceptibility analyses for the Attica Region. The produced susceptibility map is a cartographic product on a regional scale (1:100,000) generated via a semiquantitative heuristic methodology named the Rock Engineering System (RES). The way in which both soil erodibility and landslide susceptibility maps were generated and validated could be the basis for proposing modeling approaches that can respond to new developments in European landslide policies. Full article