Landslides are one of the most hazardous geological processes due to their difficult-to-predict nature and destructive effects, often leading to significant loss of life, infrastructure damage, and environmental disruption. In the Southern Andes of Chile, landslides are particularly frequent and destructive due to a combination of factors, including high seismic activity, steep topography, and the presence of weak, unconsolidated pyroclastic soils. Unfortunately, the geomechanical control of landslide initiation in the Southern Andes is still poorly understood, creating a significant source of uncertainty in developing accurate landslide susceptibility or risk models. This study evaluates the geological and geotechnical factors that control the generation of landslides in pyroclastic soils using in situ data, laboratory analysis and remote sensing approaches. The study area covers the surroundings of the Mocho-Choshuenco Volcanic Complex (MCVC), one of the most explosive volcanoes in the Southern Andes. The results show that the landslides are placed on slopes covered by multiple explosive eruptions that include a period of more than 12 ka. Landslide activity is related to pyroclastic soils with significant weathering and halloysite content. In addition, the geotechnical characteristics show very light soils, with highwater retention capacity, which is vital to induce mechanical instability. The detected deformation may be associated with seasonal precipitation that would increase the pore water pressure and reduce the shear strength of the soil, promoting slow-moving landslides. The geological and geotechnical characteristics of the soils suggests that slow-moving landslides would be extended to a large part of the Southern Andes. Finally, this study contributes to improving hazard assessment to mitigate the impact of landslides on the population, infrastructures and natural resources in the Southern Andes.

The 2018 Sulawesi Earthquake and Tsunami serves as a backdrop for this work, which employs simple and straightforward remote sensing techniques to determine the extent of the destruction and indirectly evaluate the region's vulnerability to such catastrophic events. Documenting damage from tsunamis is only meaningful shortly after the disaster has occurred because governmental agencies clean up debris and start the recovery process within a few hours after the destruction has occurred, deeming impact estimates unreliable. Sentinel-2 and Maxar WorldView-3 satellite images were used to calculate well-known environmental indices to delineate the tsunami-affected areas in Palu, Indonesia. The use of NDVI, NDSI, and NDWI indices has allowed for a quantifiable measure of the changes in vegetation, soil moisture, and water bodies, providing a clear demarcation of the tsunami's impact on land cover. The final tsunami inundation map indicates that the areas most affected by the tsunami are found in the urban center, low-lying regions, and along the coast. This work charts the aftermath of one of Indonesia's recent tsunamis but may also lay the groundwork for an easy, handy, and low-cost approach to quickly identify tsunami-affected zones. While previous studies have used high-resolution remote sensing methods such as LiDAR or SAR, our study emphasizes accessibility and simplicity, making it more feasible for resource-constrained regions or rapid disaster response. The scientific novelty lies in the integration of widely used environmental indices (dNDVI, dNDWI, and dNDSI) with threshold-based Decision Tree classification to delineate tsunami-affected areas. Unlike many studies that rely on advanced or proprietary tools, we demonstrate that comparable results can be achieved with cost-effective open-source data and straightforward methodologies. Additionally, we address the challenge of differentiating tsunami impacts from other phenomena (et, liquefaction) through index-based thresholds and propose a framework that is adaptable to other vulnerable coastal regions.

Increasingly, Climate Change (CC) is yielding more adverse climatic conditions that lead to the occurrence of natural hazards. Within these CC-related phenomena, it is possible to list global warming, flooding events, and urban heat islands. These scenarios generate damage to road infrastructure to a greater or lesser extent. Consequently, the CC-related phenomena affect the interconnection of production centers with cities and other communities. In this way, as CC causes potential damage to the pavement structures, socio-economic growth rates are correspondingly decreased. The preceding reveals the importance of designing CC-resilient asphalt pavements, which represent the vast percentage of transport infrastructure built worldwide. In this regard, this literature review aims to summarize the leading technologies and strategies developed in the state-of-the-art to mitigate the impacts of CC, as well as promote disaster risk reduction. Thus, this manuscript explains the following resilient design alternatives: anti-rutting asphalt mixtures, multilayer cool coatings, less temperature- sensitive asphalt mixtures, high-inertia pavements, flame retardancy of asphalt binders, anti-fatigue asphalt mixtures, self-healing asphalt mixtures, self-deicing asphalt mixtures, road-heating systems, fast-draining asphalt pavements, hydrophobic asphalt pavement, anti-ageing additives, solar pavements, and cool pavements. Furthermore, several constitutive models capable of simulating soil behaviour under CC-related events are introduced throughout this paper. This review highlights critical advancements in pavement engineering and encourages the adoption of sustainable, resilient design practices to safeguard infrastructure and ensure longterm socio-economic stability. The findings from this investigation provide a valuable resource for pavement designers, civil engineers, and policymakers, offering practical guidance for adapting road infrastructure to future climatic conditions.

Slope failures are an ongoing global threat leading to significant numbers of fatalities and infrastructure damage. Landslide impact on communities can be reduced using efficient early warning systems to plan mitigation measures and protect elements at risk. This manuscript presents an innovative geophysical approach to monitoring landslide dynamics, which combines electrical resistivity tomography (ERT) and low-frequency distributed acoustic sensing (DAS), and was deployed on a slope representative of many landslides in clay rich lowland slopes. ERT is used to create detailed, dynamic moisture maps that highlight zones of moisture accumulation leading to slope instability. The link between ERT derived soil moisture and the subsequent initiation of slope deformation is confirmed by low-frequency DAS measurements, which were collocated with the ERT measurements and provide changes in strain at unprecedented spatiotemporal resolution. Auxiliary hydrological and slope displacement data support the geophysical interpretation. By revealing critical zones prone to failure, this combined ERT and DAS monitoring approach sheds new light on landslide mechanisms. This study demonstrates the advantage of including subsurface geophysical monitoring techniques to improve landslide early warning approaches, and highlights the importance of relying on observations from different sources to build effective landslide risk management strategies.

Due to favorable natural conditions and human impact, the territory of North Macedonia is very susceptible to natural hazards. Steep hillslopes combined with soft rocks (schists on the mountains; sands and sandstones in depressions), erodible soils, semiarid continental climate, and sparse vegetation cover give a high potential for soil erosion and landslides. For this reason, this study presents a multi-hazard approach to geohazard modeling on the national extent in the example of North Macedonia. Utilizing Geographic Information Systems, relevant data about the entire research area were employed to analyze and assess soil erosion and susceptibility to landslides and identify areas prone to both hazards. Using the Gavrilovi & cacute; Erosion Potential Method (EPM), an average value of 0.36 was obtained for the erosion coefficient Z, indicating low to moderate susceptibility to erosion. However, a significant area of the country (9.6%) is susceptible to high and excess erosion rates. For the landslide susceptibility assessment (LSA), the Analytical hierarchy process approach is combined with the statistical method (frequency ratio), showing that 29.3% of the territory belongs to the zone of high and very high landslide susceptibility. Then, the accuracy assessment is performed for both procedures (EPM and LSA), showing acceptable reliability. By overlapping both models, a multi-hazard map is prepared, indicating that 22.3% of North Macedonia territory is highly susceptible to erosion and landslides. The primary objective of multi-hazard modeling is to identify and delineate hazardous areas, thereby aiding in activities to reduce the hazards and mitigate future damage. This becomes particularly significant when considering the impact of climate change, which is associated with increased landslide and erosion susceptibility. The approach based on a national level presented in this work can provide valuable information for regional planning and decision-making processes.

This research comprehensively assesses the aftermath of Cyclonic Storm Mocha, focusing on the coastal zones of Rakhine State and the Chittagong Division, spanning Myanmar and Bangladesh. The investigation emphasizes the impacts on coastal ecology, shoreline dynamics, flooding patterns, and meteorological variations. Employed were multiple vegetation indices-Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Modified Vegetation Condition Index (mVCI), Disaster Vegetation Damage Index (DVDI), and Fractional Vegetation Cover (FVC)-to evaluate ecological consequences. The Digital Shoreline Assessment System (DSAS) aided in determining shoreline alterations pre- and post-cyclone. Soil exposure and flood extents were scrutinized using the Bare Soil Index (BSI) and Modified Normalized Difference Water Index (MNDWI), respectively. Additionally, the study encompassed an analysis of microclimatic variables, comparing meteorological data across pre- and post-cyclone periods. Findings indicate significant ecological impacts: an estimated 8985.46 km2 of dense vegetation (NDVI >0.6) was adversely affected. Post-cyclone, there was a discernible reduction in EVI values. The mean mVCI shifted negatively from -0.18 to -0.33, and the mean FVC decreased from 0.39 to 0.33. The DVDI underscored considerable vegetation damage in various areas, underscoring the cyclone's extensive impact. Meteorological analysis revealed a 245 % increase in rainfall (20.22 mm on May 14, 2023 compared to the May average of 5.86 mm), and significant increases in relative humidity (14 %) and wind speed (205 %). Erosion was observed along 74.60 % of the studied shoreline. These insights are pivotal for developing comprehensive strategies aimed at the rehabilitation and conservation of critical coastal ecosystems. They provide vital data for emergency response initiatives and offer resources for entities engaged in enhancing coastal resilience and protecting local community livelihoods.

Reliable estimates of future climate change in the Alps are relevant for large parts of the European society. At the same time, the complex Alpine region poses considerable challenges to climate models, which translate to uncertainties in the climate projections. Against this background, the present study reviews the state-of-knowledge about 21st century climate change in the Alps based on existing literature and additional analyses. In particular, it explicitly considers the reliability and uncertainty of climate projections. Results show that besides Alpine temperatures, also precipitation, global radiation, relative humidity, and closely related impacts like floods, droughts, snow cover, and natural hazards will be affected by global warming. Under the A1B emission scenario, about 0.25 degrees C warming per decade until the mid of the 21st century and accelerated 0.36 degrees C warming per decade in the second half of the century is expected. Warming will probably be associated with changes in the seasonality of precipitation, global radiation, and relative humidity, and more intense precipitation extremes and flooding potential in the colder part of the year. The conditions of currently record breaking warm or hot winter or summer seasons, respectively, may become normal at the end of the 21st century, and there is indication for droughts to become more severe in the future. Snow cover is expected to drastically decrease below 1500-2000 m and natural hazards related to glacier and permafrost retreat are expected to become more frequent. Such changes in climatic parameters and related quantities will have considerable impact on ecosystems and society and will challenge their adaptive capabilities. (c) 2013 The Authors. Published by Elsevier B.V. All rights reserved.