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Item type:Publication, Reinforcement learning-based tsunami evacuation guidance system(Elsevier Ltd, 2024-12-01)Congestion and crowding are critical issues during indoor and outdoor emergency evacuations. In the 2011 Great East Japan Earthquake and Tsunami, vehicle traffic was one of the causes of the event's casualties. After this, vehicle evacuation in tsunami events is not advised in Japan. Then, pedestrian evacuation is expected to be the primary mode of mobility in emergencies. However, crowding and congestion may affect the evacuation time of individuals and the overall outcome of the process. In addition, narrow streets and a high preference for the shortest routes may worsen the situation. This study aims to find the best evacuation route for a target population, considering less congestion in the road network and increasing the chances of reaching safe areas on time. We propose using reinforcement learning to train an intelligent network of agents, placed at the intersections, in charge of the evacuation process to fully complying evacuee agents. The model rewards decisions that lead to successful evacuation, considering the dynamics of departure times and street congestion throughout the simulation. We demonstrate the applicability of reinforcement learning to guide tsunami evacuation in a simulation and test this against a non-guided case where evacuees move following the shortest paths. Results show that the reinforcement learning model yields better outcomes than evacuations following the shortest paths. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Vulnerabilities and exposure of recent informal urban areas in Lima, Peru(Elsevier Ltd, 2024-10-01)Urban areas are experiencing rapid growth, accompanied by significant disorder in Lima Metropolitan area and many other cities in South America. Due to decades of uncontrolled construction practices, it is imperative to identify and better understand the types of informalities prevalent in these recent urban areas. Addressing this lack of information is crucial for implementing appropriate countermeasures and developing new policies that benefit the communities residing in such areas. It is worth noting that understanding disaster risk aligns with the first priority of the Sendai Framework for Disaster Risk Reduction. In this study, we propose the use of radar satellite imagery recorded by the Sentinel-1 constellation since 2017 to identify clusters of urban growth in Lima Metropolitan area. Then, the informal urban clusters can be depicted by visual inspection of the last recorded high-resolution optical image. With good spatial and temporal resolution, we identified 25 clusters informal areas. Among our findings, we observed that several of these clusters are situated in landfills comprised of construction and other waste, increasing their vulnerability to debris flow, landslides, and earthquakes. Additionally, we noted that some new urban areas mainly consist of temporarily empty houses, highlighting the feasibility of implementing countermeasures, such as relocations, in the early stages of informal occupation. These results underscore the significant contribution of satellite radar imagery in identifying recent informal urban areas. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Applying the multi-dimensional damage assessment (MDDA) methodology to the Cumbre Vieja volcanic eruption in La Palma (Spain)(Springer Science and Business Media B.V., 2024-12-01)Volcanic events with an important affectation of urban areas and other land areas with important human activity have been rare in Europe in the past century. This has led to a lack of comprehensive analysis of the social, economic and environmental damages that these types of events can cause on specific human communities. In the present study, we apply an industrial ecology approach to calculate the damage linked to the Cumbre Vieja volcanic eruption in the Canary Islands in September 2021. Therefore, the main objective was to apply the multi-dimensional damage assessment (MDDA) methodology to quantify the degree of damage that has been exerted by the eruption in the island of La Palma (Spain) through the inclusion of environmental damage endpoints with other sustainable development variables (i.e., social and economic dimensions). Data were obtained from different sources, including the cadastre of La Palma, local data on derived health, as well as data obtained from the global ecosystem dynamics investigation of NASA, among other sources. Thereafter, damage endpoints were all converted to disability-adjusted life years (DALYs). Results show that direct gaseous emissions from the volcano were responsible for a significant amount of total DALYs, above 90% in all scenarios, followed by damage linked to economic losses, as well as social losses related to morbidity. Other environmental damages played a minor part in the total damage exerted by the volcano. The results demonstrate the importance of air quality indicators in the aftermath of an eruption in densely populated areas; in contrast, the impact associated with infrastructure loss played a minor role in total damage. Although challenges remain when providing a holistic quantification of total damage linked to volcanic disasters, the MDDA method constitutes a promising systematic standardized and transparent damage quantification tool that allows computing a deterministic damage evaluation that can aid in natural hazard risk assessment. In fact, it is considered that the method has the potential to be used as a holistic decision tool to aid in mitigating disaster risk. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analyzing the behavior of beachgoers in the city of Lima and their relationship with potential plastic emissions(Elsevier Ltd, 2024-12-01)Beach littering is a source of marine plastic waste accumulation. This is particularly so in overcrowded beaches in the Global South in which cleaning measures are scarce or sporadic and lack of waste management systems can increase plastic release. In the current study we focus on the importance of the behavior shown by beachgoers and how their conduct relates to the amount of plastic that potentially ends up entering littoral ecosystems. Transportation services to beaches, sports, food, and beverage containers are analyzed through a 24-question survey performed to 500 beachgoers in 4 beaches (i.e., Venecia, Punta Negra, Punta Hermosa and San Bartolo) located in the megacity of Lima, Peru, in February 2022. The data obtained were then processed to understand the differences in behavior across different beaches. Moreover, a K-means algorithm was used to identify representative beachgoer profiles. The results showed a dichotomous behavior between two groups of beaches, in which the size group of beachgoers, transportation mode, accommodation, food consumption patterns or the use of reusable containers are some of the main differences between the two groups. No major differences were identified in terms of age distribution across the different beaches, but group sizes were higher in Punta Negra and Villa El Salvador. The K-means algorithm suggests that the surveyed population can be grouped into three main categories, of which two correspond mainly to higher socioeconomic beachgoers in the beaches of Punta Hermosa and San Bartolo. Overall, single use plastic for food and beverages appears as one of the main sources of plastic pollution across beaches and groups, although other sources of plastic emission should not be underestimated. Finally, the three beachgoer profiles identified are useful to implement targeted policies to minimize the environmental impacts of these profiles. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Open dataset of road obstructions due to collapsed buildings from the 2023 Turkey earthquakes(International Association for Earthquake Engineering, 2024-01-01)After large-magnitude earthquakes, collapsed buildings can disrupt transportation networks due to debris obstructing streets, sidewalks, and highways. These disruptions can critically compromise rescue activities, the mobilization of seriously injured patients, and aid distribution to the affected population. Accordingly, it is recommended the removal of obstructions during the first 48 hours after a disaster to meet emergency response needs as quickly as possible. However, the literature on seismic vulnerability has yet to deeply address the topic of road obstructions due to the limited availability of data. In this paper, we exploit several open datasets to collect about 1,400 collapsed buildings causing varying levels of road obstructions after the 2023 Turkey, earthquake sequence. The buildings are located in Hatay, Islahiye, Adiyaman, and Kahramanmaras. From visual inspection of high-resolution satellite and aerial images, the buildings were geolocated and classified according to the level of obstruction produced in the road by its debris. In the study, we considered three levels of obstruction: no obstruction, partial obstruction, and complete obstruction of a road. The number of floors was recorded from Google Street View data. Analysis of the data shows that taller buildings that experienced full collapse produced more obstructions. Thus, researchers can utilize the dataset to develop probabilistic models that predict the obstruction level according to the type of construction, the number of floors in a building, and the damage level. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Vertical growth of masonry buildings in Peru and its role in the increase of seismic vulnerability(International Association for Earthquake Engineering, 2024-01-01)In Lima, the capital of Peru, and many cities in South America, houses tend to grow vertically. Due to financial limitations and increment of family members, houses increase a floor at different periods. As a result, their dynamic properties and performance during earthquakes change over time. Thus, it is necessary to estimate the change in the seismic vulnerability considering the height change in time. Unfortunately, today, there is no information regarding the vertical growth rate of buildings in Lima. To this aim, we have estimated the vertical growth rate of informal masonry buildings by inspecting 457 samples. The selection of the buildings was based on their availability in the Google Street View dataset, which was used to identify the number of floors in 2013. Then, the number of floors in 2023 was determined by a series of field surveys. With the number of floors at the two dates, we compute the transition matrix T. The relevance of the transition matrix lies in that it can be used to predict the number of floors in different years and assess the change in the seismic vulnerability of masonry buildings. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Informal urban growth monitoring in earthquake-prone areas using SAR satellite images(International Association for Earthquake Engineering, 2024-01-01)In recent decades, Peru’s primary mode of urban growth has been the informal occupation of bare lands. These urban areas are characterized by their lack of essential services, such as electricity and water. With the lack of suitable land for urban development, informal urban has grown into unsafe areas against earthquakes. Due to the lack of resources in developing countries, detecting recent informal occupations in unsafe areas cannot be performed, which is an important task for relocation purposes. This article reports the performance of machine learning applied in synthetic aperture radar (SAR) satellite images for the early detection of informal settlements in hazardous areas. The methodology uses a set of temporally SAR images of a specific area, binary pixel classification, and post-processing techniques to improve the prediction performance. Two informal occupations that occurred in the districts of Chorrillos and Villa el Salvador, Lima, Peru, in April 2021 were used as experimental evaluation. A set of SAR images of the constellation Sentinel-1 was used with a resolution of 10m. The results show that time series analysis of SAR images can identify recent informal occupations. However, the geometrical distortions in SAR images reduce the accuracy of the spatial extent of the occupations. We conclude that SAR images are a valuable source for a sustainable informal urban growth monitoring system. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Placing engineering in the earthquake response and the survival chain(Nature Research, 2024-12-01)Earthquakes injure millions and simultaneously disrupt the infrastructure to protect them. This perspective argues that the current post-disaster investigation paradigm is insufficient to protect communities’ health effectively. We propose the Earthquake Survival Chain as a framework to change the current engineering focus on infrastructure to health. This framework highlights four converging research opportunities to advance understanding of earthquake injuries, search and rescue, patient mobilizations, and medical treatment. We offer an interdisciplinary research agenda in engineering and health sciences, including artificial intelligence and virtual reality, to protect health and life from earthquakes.