DEVELOPMENT OF A BUILDING EXPOSURE MODEL BASED ON UAV AND 360 IMAGERY FOR SEISMIC RISK ASSESSMENT IN NEJAPA (EL SALVADOR) We develop an exposure and seismic vulnerability database for seismic risk applications in the city centre of Nejapa (El Salvador). This area, as most of the country, is characterised by a very limited availability of open cadastral data, street-level and aerial imagery and LiDAR point clouds.We carry out an on-site campaign integrating aerial street-level images. Aerial images are captured in a drone flight and are used to identify building footprints and roof properties. Façade photos are obtained with a 360º camera during a walk-down survey, provindng information about the number of storeys and wall materials. These data are combined to generate a 3D model of the city centre. Next, buildings are identified, characterised, and assigned a vulnerability and fragility models.This database is used to estimate seismic risk for a simulated Mw 6.7 earthquake on the Guaycume fault near the city. Results show that 71% of buildings would suffer complete damage and 68% of the population would be homeless, with losses exceeding USD 15 million.A dashboard integrating these data are set up to help disseminating the results of the study into stakeholders and decision makers.

In Latin America, high seismic activity drives countries to develop disaster risk reduction policies based on seismic risk studies. This work demonstrates the feasibility of creating a seismic exposure and vulnerability database using remotely sensed data. In Nejapa, El Salvador, a drone flight and 360° photo capture were conducted to generate a 3D model of the city. Buildings were identified, characterised, and assigned a vulnerability model. This database was used to estimate seismic risk for a simulated Mw 6.7 earthquake on the Guaycume fault near the city. Results show that 71% of buildings would suffer complete damage and 68% of the population would be homeless, with losses exceeding USD 15 million. Findings were shared with relevant institutions in El Salvador through a dashboard. The country is currently collecting the same type of data used in the present study to update its cadastre and census. This is an opportunity to replicate this pilot experience in many other cities across the country and to provide open data access, positioning El Salvador at the forefront of civil protection in the Latin American region.

In this paper, we study the geographic and temporal distribution of earthquakes in Guatemala, and their magnitudes, from 1526 to October 2022. We utilized the earthquake catalog of the national seismic network of Guatemala, complemented by two additional sources. First, we describe the development of the detection network and the seismic catalog. Second, we analyze the errors in the catalog and determine the quality of the focal locations, examining their distribution in time and space while separating events into shallow and deep earthquakes. Finally, we calculate seismic parameters such as annual rates of earthquakes and magnitude of completeness. The results indicate a strong variability in time and space of errors and seismic parameters that are linked to changes in the detection network. In conclusion, by highlighting the evolution of this catalog and its features, this paper underscores the importance of considering these spatial and temporal variations in future analyses of seismicity and seismic hazard in Guatemala. This topic can be of interest to other countries with similar characteristics in tectonics and detection networks.

Disaster risk reduction in heritage and culturally significant assets within the urban and rural parishes of Guaranda is a strategic priority for preserving cultural identity and strengthening community resilience. This study assesses the vulnerability of heritage buildings through a multidisciplinary approach that integrates local knowledge and promotes the active participation of key stakeholders. The applied methodology was structured into four phases: (i) preliminary analysis, (ii) inventory update, (iii) vulnerability assessment, and (iv) evaluation of the process and its social and impact in the community. Main results include the inventory update of 526 heritage buildings, achieving 99% coverage with updated data. Additionally, various traditional construction typologies were identified, and thematic maps were developed to represent vulnerability to seismic, flood, landslide, and volcanic hazards. Lastly, citizen participation was strengthened through the implementation of a satisfaction survey and the creation of the collective “Somos Memoria”.

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We extend the conventional seismic risk assessment approach to open spaces in the 2011 Lorca earthquake scenario. Conventional approaches to seismic risk provide estimates of damaged buildings mainly related to structural failure. The damage related to the production of debris in damaged buildings and its spread in the surrounding space receives a secondary role. However, in many cases, this secondary damage is of prime importance. In this work, we consider the Mw5.2, 2011 Lorca earthquake (Spain), which caused nine fatalities associated with the fall of non-structural building parts. First, we analyze reports of emergency interventions, including those related to debris removal, and we derive their geographical and temporal distributions. Then, we introduce an extension of the conventional risk model to include the debris generated in damaged buildings and its accumulation in open spaces. We apply this risk extension model together with the conventional risk model to estimate the distributions of damaged buildings and of debris volumes related to the 2011 Lorca earthquake scenario. Results indicate differences between predicted and observed damage estimates within a half-damage degree interval and differences in debris volumes within the same order of magnitude. The approach presented is easily exportable to urban risk studies of other areas.

The seismic vulnerability of a city is a degree of its intrinsic susceptibility or predisposition to sustain damage or losses stemming from seismic events. In terms of physical vulnerability, one of the most important factors for assessing seismic risk, especially, for estimating losses, is the exposure of structures, particularly those structures intended for residential use. The present article outlines a methodology for classifying residential buildings based on the structural and non-structural components that ultimately determine the building typology and control the seismic performance. The proposed methodology is divided into three steps: first, spatial data are analysed using an official database that is supplemented by remote field work to verify, validate, and identify construction typologies and urban modifiers after incorporating the new observable data. During the second step, machine learning techniques based on Two-Step cluster analysis and neural networks are used to identify building typologies, using a multilayer perceptron to assess the representativeness of the building typologies identified. Finally, each building typology is defined, a vulnerability assessment is carried out, and vulnerability classes are ranked based on the macroseismic scale. The above-mentioned steps were applied to 7631 residential buildings in the city of Murcia, Spain. The methodology is scalable and may be automated, so it may be replicated in other urban areas with similar characteristics or adapted to different urban settings. This may help save time and reduce the cost of carrying out seismic risk studies, providing valuable information for both civil protection and regional and local governments.

The Eastern Betics Cordillera embraces a zone of low-to-moderate seismic activity located at the SE of the Iberian Peninsula. However, a major active fault system which crosses the area, ca. 500 km long, known as the Eastern Betics Shear Zone (EBSZ), has been responsible for the occurrence of several large historical earthquakes (Mw> 6.0) since the beginning of the historical record. Finding physics-based evidence for relations between significant historical events in such a moderate-slipping fault system would help us narrate them as long-term cascades. Such a perspective provides valuable insights into faults interactions over time and, thus, until the contemporary periods.Some authors have examined static Coulomb failure stress changes (ΔCFS) to explain the triggering influence of moderate instrumental earthquakes in this region. However, the applied approach in this study, which implies the estimation of postseismic ΔCFS, is the first attempt of this kind to identify triggering connections between historical earthquakes in EBSZ.This study addresses a sixteenth-century cascade of three large earthquakes that occurred in less than 13 years within a radius of 100 km in the southern section of the EBSZ. It includes the 1518 Vera (Mw~6.2), the 1522 Alhama de Almería (Mw~6.5 -7.1) and the 1531 Baza (Mw~6.5) earthquakes, each one associated with a different causative fault, namely the N-S strike-slip Palomares fault, the NE-SW strike-slip Carboneras fault and the N-S to NW-SE normal Baza fault, respectively. We aim to explore the Coulomb stress transfer along the occurrence of this cascade and the plausible rupture scenarios that could favour or not a triggering connection between the causative faults.First, a simple smoothed slip model is performed to simulate the earthquake ruptures. The applied slip models respect existing information on the attributes and hypotheses based on seismological and paleoseismic studies. Then, the multilayered viscoelastic relaxation modelling by Wang et al. (2006) is used to calculate the time-dependent deformation fields (since the 1518 Vera earthquake) across the crust and the lithospheric mantle. Finally, the cumulative co+postseismic ΔCFS are solved for the kinematics of the Carboneras and Baza fault planes in 1522 and 1531, respectively.Our results strongly suggest a sequential stress-triggering connection between these three large events. According to our models, the 1531 Baza earthquake occurred along with an increase in the ΔCFS due to the viscoelastic relation over time. We further explore the implication of the characteristic curved-shape of the Baza fault when considering different rupture scenarios of the 1522 event at the Carboneras fault. We found that the northern NS-oriented section of the Baza fault remains more exposed to positive cumulative co+postseismic ΔCFS and, indeed, was more prone to rupture in 1531 rather than the southern NW-SE section. We believe our results would pave the way for understanding the relationship between many other major historical earthquakes in the Betics Cordillera.

Understanding the crustal fault interaction and connection between earthquakes in areas with slow tectonic deformation, such as Betic Cordillera (South Spain), is challenging. When seismic rates are low and large destructive earthquakes happen less frequently, it is necessary to resort to historical or paleoseismic records. This study investigates the postseismic viscoelastic relaxation mechanism as a potential explanation for the occurrence of three historical earthquakes (I EMS VIII‐IX) in the Eastern Betic Shear Zone during the XVI‐century, all of which occurred within a span of 13 years: 1518 Vera Mw6.2, 1522 Alhama de Almeria Mw6.5, and 1531 Baza Mw6.2 associated with the Palomares, Carboneras, and Baza faults, respectively. The results strongly suggest a sequential stress‐triggering connection between the three events. The northern NS‐oriented section of the Baza fault is found to have experienced a larger positive ΔCFS and, indeed, more prone to rupture in 1531. The study also examines whether the cumulative ΔCFS had influenced the occurrence of further significant earthquakes (≥Mw6.0) in the region. A triggering connection between the cascade and the 1658 Almeria Mw6.2 earthquake is suggested, whereas no indications of similar linkage to the 1674 Lorca Mw6.0 or the 1804 Dalias Mw6.4 events are found. The stress triggering impact of the cascade over nearby active faults is noteworthy. It is expected that this analysis could have future applications for studying other important historical events, and improving seismic hazard analysis in complex fault settings of the Betic Cordillera.

EDITORIAL article Front. Earth Sci., 14 March 2023Sec. Solid Earth Geophysics Volume 11 - 2023 | https://doi.org/10.3389/feart.2023.1164767

The present study proposes a statistical methodology to rate the habitability of different types of buildings after an earthquake. The first step was to rank variables that affect the vulnerability of a building and formulate a statistical study with a discrimination index that makes it possible to identify buildings as habitable or non-habitable. This ranking applied the criteria established in various international guidelines that are used to distinguish between habitable (undamaged/no structural damage) and non-habitable buildings (structural damage). The proposed methodology was applied to a database with information about buildings and damage grade experienced following the 2011 earthquake in Lorca. The approach presented could be extended to other regions where neccessary data are available.

The present work is part of the resilience study of urban areas, where the study area is the urban center of Valdivia (Chile). The aim is to catalog and identify buildings and urban blocks for the subsequent evaluation of exposure and vulnerability to seismic risk. This is done through a collaborative mapping with the participation of a local team of volunteers (of the Technological University of Chile INACAP) that was previously trained on vulnerability issues and OpenStreetMap platform. The study area comprises 83 urban blocks. Each urban block is subdivided into parcels, which contain buildings with different type of construction and different uses. In the future, this research will continue with the development of urban resilience indexes at physical and social scales.

The Carboneras Fault, located in the Southeast Iberian Peninsula, is one of those with the highest slip rate (a), among the active faults in Spain, and is also one of the longest (L), which also makes it one of the highest potential seismic, in terms of the scalar seismic moment that could be released (Mo). According to QAFI v3 (IGME, 2015), a = 1.1 mm / year and L = 110.5 km, which would make possible an earthquake of magnitude Mw = 7.4, (using the of W & C'94 empirical relationship) with a recurrence interval of TR = 1150 years . The fault is strike slip and pleosysmic studies in it point to minimum of 6 events since the Mid Pleistocene observed in trenches along La Serrata (Moreno, 2010, Moreno et al., 2008) and an elapsed time for Mw 7.4 of 1178 years. On the other hand, the last major event reported historically in the fault is the one that occurred in 1522, with I (EMS) = IX and M = 6.5, which allows estimating an elapsed time of about 500 years for that magnitude. With the available data, hazard estimates have been developed from different fault modeling: 1) TC characteristic earthquake, 2) Brownian model of temporal dependence, 3) Renewal model and 4) Poisson model. The sensitivity of the results to the different source modeling is analyzed, and these are compared in turn with the PGA values of the latest seismic hazard map of Spain (UPM-IGN, 2013). Finally, we analize the impact of the results in the city of Almeria, which is one of the most vulnerable in southern Spain, which makes the impact spread to the seismic risk scenarios that can be expected due to future earthquakes.

We analyze the 2014 Papanoa seismic series, located in the Guerrero, Mexico, subduction interface. First, Coulomb failure stress changes because of the mainshock, and the two largest aftershocks are calculated along the interface. The location of aftershock epicenters largely coincides with areas showing positive stress changes. In addition, epidemic-type aftershock sequence modeling of the series indicates aftershock productivity was not especially large and suggests an increase of background activity rates after the occurrence of the 2014 Papanoa series. This information is used to infer the magnitude-dependent, smoothed densities of background rates for the study area. Ground-motion exceedance rates because of interface sources are computed considering different seismicity rate densities and applying the declustering approach. Results show a slight increase of expected accelerations for different exceedance probabilities.

We present a procedure for exposure and vulnerability evaluation that integrates LiDAR, orthophotos, and other ancillary datasets. It comprises three phases: (1) city stratification into homogeneous regions; (2) exposure database compilation; and (3) vulnerability allocation using predictive modelling. We have conducted two applications in Lorca (Spain) and Port-au-Price (Haiti) and here we compare them. Each phase of the method is subject to variations due mainly to data availability; however, it does not affect the final accuracy that remains high in both scenarios (over 80%). It is a flexible procedure that is able to adapt to the particular features of two different cities.

The Permian-Triassic rifting represents the first of the two Mesozoic rifting stages recorded in the Iberian Peninsula. Its first phases of development started during the Early Permian, and were linked to the beginning of the break-up of Pangea, the large, unique and rheologically unstable supercontinent that mainly resulted from the collision of Gondwana and Laurussia. This chapter analyzes this first rifting stage in Iberia in two separate phases, an initial or tectonic phase, and a later mature phase. This analysis focuses on the main Permian-Triassic basins of the Iberian Peninsula: the Pyrenean, Iberian, Catalan, Ebro and Betic basins, as well as the basins located in the present-day Balearic Islands. In order to achieve a better understanding of the analyses of these basins, a multidisciplinary approach has been carried out by 48 researchers, including studies of tectonics, sedimentology, magmatism, mineralogy, geochemistry and paleontology.

We present a procedure for assessing the urban exposure and seismic vulnerability that integrates LiDAR data with aerial images from the Spanish National Plan of Aerial Orthophotography (PNOA). It comprises three phases: first, we segment the satellite image to divide the study area into different urban patterns. Second, we extract building footprints and attributes that represent the type of building of each urban pattern. Finally, we assign the seismic vulnerability to each building using different machine-learning techniques: Decision trees, SVM, logistic regression and Bayesian networks. We apply the procedure to 826 buildings in the city of Lorca (SE Spain), where we count on a vulnerability database that we use as ground truth for the validation of results. The outcomes show that the machine learning techniques have similar performance, yielding vulnerability classification results with an accuracy of 77%-80% (F1-Score). The procedure is scalable and can be replicated in different areas. This is particularly relevant in Spain, where more than seven hundred towns have to develop seismic risk studies in the years to come, according to the General Direction of Civil Protection and Emergencies. It is especially interesting as a complement to conventional data gathering approaches for disaster risk applications in cities where field surveys need to be restricted to certain areas, dates or budget.

We present a procedure for assessing the urban exposure and seismic vulnerability that integrates aerial and satellite images with LiDAR data. It comprises three phases: first, we segment the satellite image to divide the study area into different urban patterns. Second, we extract building footprints and attributes that represent the type of building of each urban pattern. Finally, we assign the seismic vulnerability to each building using two machine learning techniques: logistic regression and Bayesian networks. We apply the procedure in the city of Lorca (SE Spain), where we count on a vulnerability database that we use as ground truth for the validation of results. The outcomes show that both machine learning techniques have similar performance, yielding vulnerability classification results with an accuracy of over 75% (F1 Score) in most of the cases, provided that the building footprints are correctly delineated. The procedure is scalable and can be replicated in different areas as a complement to conventional data gathering approaches. It is especially interesting for disaster risk applications in areas where cadastral databases are inaccessible or field surveys are not viable.

In 11 of August 2012, two destructive earthquakes with Mw= 6.4 and 6.2 occurred between cities Ahar and Varzeghan (Northwest Iran). They had a close epicentral distance of 6 Km and also had a short time lag of 11 minutes. Following that, a high-rate of aftershock activity began where during the first month more than 2000 events (M≥0.7) affected several villages in the area. The seismic released energy induced significant damage and losses in an extensive zone. Right after the seismic doublet occurrence, a surface rupture with a primarily east-west orientation was observed. The idea of having an almost vertically dipped fault plane for the first shock is more consistent with the trace of the upper edge on the surface and the focal mechanism solutions which propose a steady dipping EW. Previous studies propose different geometries for the generating faults of the second earthquake. In this study, we associate the surface rupture with the first mainshock and both nodal plane explaining the relationship between the two main seismic events are discussed after Coulomb failure stress calculation due to the first shock. Then the stress transfer because of the doublet is analyzed in order to determine its consistency with the statistical modeling prediction for the aftershock population and spatial distribution. For statistical modeling a temporal version of Epidemic Type Aftershock Sequence (ETAS) is applied on one-year seismicity including events with minimum magnitude of 2.5.http://dx.doi.org/10.4995/CIGeo2017.2017.6662