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Slope failures occur in open-pit mining areas worldwide, producing considerable damage in addition to economic loss. Identifying the triggering factors and detecting unstable slopes and precursory displacements —which can be achieved by exploiting remote sensing data— are critical for reducing their impact. Here we present a methodology that combines digital photogrammetry, satellite radar interferometry, and geo-mechanical modeling, to perform remote analyses of slope instabilities in open-pit mining areas. We illustrate this approach through the back analysis of a massive landslide that occurred in an active open-pit mine in southwest Spain in January 2019. Based on pre- and post-event high-resolution digital elevation models derived from digital photogrammetry, we estimate an entire sliding mass volume of around 14 million m3. Radar interferometry reveals that during the year preceding the landslide, the line of sight accumulated displacement in the slope reached − 5.7 and 4.6 cm in ascending and descending geometry, respectively, showing two acceleration events clearly correlated with rainfall in descending geometry. By means of 3D and 2D stability analyses we located the slope instability, and remote sensing monitoring led us to identify the likely triggers of failure. Las Cruces event can be attributed to delayed and progressive failure mechanisms triggered by two factors: (i) the loss of historical suction due to a pore-water pressure increase driven by rainfall and (ii) the strain-softening behavior of the sliding material. Finally, we discuss the potential of this methodological approach either to remotely perform post-event analyses of mining-related landslides and evaluate potential triggering factors or to remotely identify critical slopes in mining areas and provide pre-alert warning.

In the present work, the case of the Cármenes del Mar resort (Granada, Spain) is shown. It can be considered one of the most extreme examples on the Mediterranean coast of severe pathologies associated with urban development on coastal landslides. The resort, with 416 dwellings, was partially built on a deep-seated landslide which affects a soft formation composed of dark graphite schists. In November 2015, the City Council officially declared a state of emergency in the resort and 24 dwellings have already been evacuated. We have used two remote sensing techniques to monitor the landslide with the aim of identifying and measuring a wide range of displacements rates (from mm/year to m/year): (1) PSInSAR, exploiting 25 ENVISAT SAR images acquired from May 2003 to December 2009, and (2) photogrammetry, considering the output from two Unmanned Aerial Vehicle (UAV) flights made in June 2015 and January 2016 and the outdated photos from a conventional flight in 2008. The relationship between the geology of the site, data from PS deformation measurements, building displacements, rainfall and damage observed and their temporal occurrence allows a better understanding of the landslide kinematics and both the spatial and temporal evolution of the instability. Results indicate building displacements of up to 1.92 m in 8 years, a clear lithological control in the spatial distribution of damage and a close relationship between the most damaging events and water recharge episodes (rainy events and leaks from swimming pools and the water supply network). This work emphasises the need to incorporate geohazards into urban planning, including policies to predict, prepare for and prevent this type of phenomenon.

Some landslides around the world that have low-angle failure planes show exceptionally poor mechanical properties. In some cases, an extraordinarily pure clay layer has been detected on the rupture surface. In this work, a complex landslide, the so-called Diezma landslide, is investigated in a low- to moderate-relief region of Southeast Spain. In this landslide, movement was concentrated on several surfaces that developed on a centimeter-thick layer of smectite (montmorillonite-beidellite) clay-rich level. Since these clayey levels have a very low permeability, high plasticity, and low friction angle, they control the stability of the entire slide mass. Specifically, the triggering factor of this landslide seems to be linked to the infiltration of water from a karstic aquifer located in the head area. The circulation of water through old failure planes could have promoted the active hydrolysis of marly soils to produce new smectite clay minerals. Here, by using geophysical, mineralogical, and geochemical modelling methods, we reveal that the formation and dissolution of carbonates, sulfates, and clay minerals in the Diezma landslide could explain the elevated concentrations of highly plastic secondary clays in its slip surface. This study may help in the understanding of landslides that show secondary clay layers coinciding to their low-angle failure planes.

The significance of intra-mountain valleys to infrastructure and human settlements and the need to mitigate the geo-hazard affecting these assets are fundamental to the economy of Italian alpine regions. Therefore, there is a real need to recognize and assess possible geo-hazards affecting them. This study proposes the use of GIS-based analyses to construct a sinkhole susceptibility model based on conditioning factors such as land use, geomorphology, thickness of shallow deposits, distance to drainage network and distance to faults. Thirty-two models, applied to a test site (Enemonzo municipality, NE Italy), were produced using a method based on the Likelihood Ratio (λ) function, nine with only one variable and 23 applying different combinations. The sinkhole susceptibility model with the best forecast performance, with an Area Under the Prediction Rate Curve (AUPRC) of 0.88, was that combining the following parameters: Nearest Sinkhole Distance (NSD), land use and thickness of the surficial deposits. The introduction of NSD as a continuous variable in the computation represents an important upgrade in the prediction capability of the model. Additionally, the model was refined using a kernel density estimation that produced a significant improvement in the forecast performance.

Quantitative landslide hazard models provide estimations of the number of landslides per area and time that might be expected in the near future. These models are essential to calculate landslide risk in monetary terms. Although they are very useful tools for managing the activity of unstable slopes, their production calls for a vast amount of spatial and temporal data. Here, we present a case where this was possible producing the quantitative landslide hazard map for the municipality of Loja, Ecuador. It is based on a model that integrates six causal factors (distance to faults, lithology, slope, geomorphology, topographic position index, land use) and a comprehensive multi-temporal inventory of landslides. First, a susceptibility map was generated with a good prediction capability (Area under prediction rate curve, AUPRC: 0.8) combining two widely used and tested probabilistic methods: “Matrix” and “Likelihood ratio”. Subsequently, this map was transformed into a hazard map by including the temporal frequency of landslides. The map assesses the annual probability of each pixel to be set in motion within one of these landslides. The preliminary temporal validation of the hazard map indicates that the pixels mobilized during two years after the map production fit reasonably well with our spatio-temporal forecast. The findings emphasize that classical spatial prediction methods, when augmented by robust and extensive data on landslide distribution and activity, can yield hazard models with reliable predictive capabilities. This suggests that in practical applications, models based on relatively simple calculations can provide effective and reliable starting points for managing landslide risks.

In the last several decades, population growth in the cities of the Andes has caused urban areas to expand into landslide-prone areas. Fatal landslides affecting urban settlements are especially frequent in cities located in the Neogene intramontane basins of the Andes. These basins have similar situations and include geographical and geological features that frequently generate ground instabilities. We studied the characteristics of the mass movements observed in these basins by carrying out a detailed analysis of four landslides that have occurred in the Loja Basin (Ecuador). This multi-method study integrated geophysical, geotechnical methods, mineralogical studies and analyses of precipitation time series. Our study characterizes the slope movements as active, slow-moving, complex earthslide earthflows. According to Differential GPS measurements, these landslides move at velocities of up to several metres per year. Electrical resistivity tomography profiles show that most of the landslides are mainly surficial. Time-series analyses of precipitation reveal that rainfall events that are not exceptionally intensive can reactivate these landslides. This characteristic and the development of these landslides on low-gradient slopes are explained using the results obtained from the geotechnical and mineralogical analyses. We find that the smectite clay minerals detected in the mobilized geological formations, combined with the tropical climate of the northern Andean region, induce the observed weak slope stability conditions. The conceptual model for the studied landslides may aid in assessing landslide-prone areas in Loja and other Neogene intramontane basins of the Andes and can help to mitigate the associated risks.

Rainfall-induced landslides constitute a major cause of damage and fatalities throughout the intramontane basins of the Andes. The geological and climatic setting plays a key role in the generation of a high number of landslides in this area. For this reason, a greater understanding of the relationship between landslide frequency and climate conditions is necessary to mitigate human and economic losses. Accordingly, this paper presents an analysis of rainfall variables associated with a series of dated landslides (153 in total) in the southern Ecuador basin of Loja. This analysis was performed by applying an affordable empirical method that enables the calculation of critical rainfall threshold (CRT) curves. This calculation is based on an in-depth examination of rainfall parameters, such as cumulative precipitation and mean intensity, linked to a wide range of rainfall duration (from 1 to 90 days). The inspection of these parameters was addressed considering their frequency, which was calculated by using partial duration series (PDS), taking into account the entire rainfall record. This work has revealed that only 24% of landslides were triggered by rainfall conditions with maximum return periods greater than 1 year, whereas the rest did not exceed that return period. After finding the best correlation between the maximum return periods and the maximum mean intensity, a minimum power law function was adjusted to the CRT curve that correlates duration and cumulative rainfall. The values for this CRT function resulted in 5.14 and 0.83 for its scaling constant (α) and shape parameter (β), respectively. In addition, a spectral analysis was conducted to detect climatic cycles on the entire rainfall record. In general, a clear correlation could not be established between climatic frequencies and significant rainfall events inducing landslides, although similarly return periods were found for a critical rainfall event of March 2015 (10.4 years) and the SUNSPOT cycles (10.5-12 years). The results derived from this research are significantly valuable for the prevention of future mass-movements, although additional data will be crucial to update and calibrate CRT curves to study the influence of climate on landslide event frequency and magnitude in Loja.

The availability of displacement maps based on Multi-Temporal Satellite SAR Interferometry (MT-InSAR) has greatly increased, particularly since the launch of the Copernicus Sentinel-1 satellites in 2014. These satellites provide open and free data, leading to services like the European Ground Motion Service (EGMS) which offers highly detailed displacement maps across Europe. Despite their potential for territorial management and risk assessment, the use of these maps is limited due to the complexity of the data and the lack of experience in interpreting MT-InSAR results. Projects such as RASTOOL and SARAI aim to address this by developing automated tools that simplify and expedite the analysis of EGMS data. The ADATools suite, including ADAFinder, ADAClassifier, and ADAImpact, automates the identification, classification, and impact assessment of active deformation areas (ADAs). These tools facilitate the use of displacement data for non-experts, supporting better management of territorial and infrastructural risks. Examples of ADATools applications to EGMS data highlight their strengths and future development potential, as part of the SARAI project.

It has long been recognized that earthquakes change the stress in the upper crust around the fault rupture and can influence the behaviour of neighbouring faults and volcanoes. Rapid estimates of these stress changes can provide the authorities managing the post-disaster situation with valuable data to identify and monitor potential threads and to update the estimates of seismic and volcanic hazard in a region. Here we propose a methodology to evaluate the potential influence of an earthquake on nearby faults and volcanoes and create easy-to-understand maps for decision-making support after large earthquakes. We apply this methodology to the Mw 7.8, 2016 Ecuador earthquake. Using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and continuous GPS data, we measure the coseismic ground deformation and estimate the distribution of slip over the fault rupture. We also build an alternative source model using the Global Centroid Moment Tensor (CMT) solution. Then we use these models to evaluate changes of static stress on the surrounding faults and volcanoes and produce maps of potentially activated faults and volcanoes. We found, in general, good agreement between our maps and the seismic and volcanic events that occurred after the Pedernales earthquake. We discuss the potential and limitations of the methodology.

Here, we report evidence for the production of ozone in human disease. Signature products unique to cholesterol ozonolysis are present within atherosclerotic tissue at the time of carotid endarterectomy, suggesting that ozone production occurred during lesion development. Furthermore, advanced atherosclerotic plaques generate ozone when the leukocytes within the diseased arteries are activated in vitro. The steroids produced by cholesterol ozonolysis cause effects that are thought to be critical to the pathogenesis of atherosclerosis, including cytotoxicity, lipid-loading in macrophages, and deformation of the apolipoprotein B-100 secondary structure. We propose the trivial designation \"atheronals\" for this previously unrecognized class of steroids.