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Land-use microsimulation model for livelihood diversification after the 2010 Merapi Volcano eruptions
(2022-09-28)
After the 2010 Merapi volcano eruptions, many villages were relocated to semi-urban settlements separated from their earlier livelihoods and with few options for diversification. Post-disaster resettlement is dependent on people's access to livelihoods as a means for short-and longterm recovery. This study evaluates post-disaster mobility, aiming to clarify whether a land-use network with distributed livelihood options can complement rural labor in a recovery scenario. In 2019, a field survey was conducted in the largest resettlement site of the Sleman Regency in Yogyakarta, Indonesia, to evaluate the state of recovery; socio-demographic and land use data was subsequently processed to forecast urban development up to the year 2030. Travel routines were simulated for 2019 and 2030 comparatively to quantify travel efficiency and ease of access to employment options with the Operational Land Use and Transport Microsimulation (OLUTM) model. 1,944 new tradable and nontradable jobs were added to the area. Consequently, residential demand was met with a 44% deficit caused by spillover effects. The study also saw that 63% of the 84% livelihood diversifications were made by farmers and that farming was kept as the primary job while homebusinesses became a secondary employment. Travel utilities were reduced by 30% while travel in the settlement saw 49% fewer kilometers driven. As a result, CO 2 emissions decreased by 28% and a balance in mobility modes was achieved for the whole settlement. The OLUTM model demonstrates that people utilized 21%-26% of their monthly income before the intervention and 11%-18.4% after with a modest bus service. This study concludes that recovery planning with economies of scale generates livelihood opportunities for farmers in rural areas.
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Optimization of tsunami evacuation with reinforcement learning
(RELX Group (Netherlands), 2022-01-01)
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Sparse representation-based inundation depth estimation using SAR data and digital elevation model
(Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
Floods increase every year worldwide, and prompt information about the affected areas is essential for early disaster response. There has been extensive development in applying remote sensing data to identify floods. In fact, remote sensing data are the only tool to identify the extent of large-scale floods within hours after their occurrence. However, few studies have addressed methods to estimate inundation depth. Inundation depth can be advantageous for identifying areas where people may need assistance during evacuation and estimating damage loss. We present a practical application of sparse representation that integrates a synthetic aperture radar-based flood binary map with a digital elevation model to estimate inundation depths. We assume that the floodwaters can be modeled as a combination of water bodies at a state of rest. A dictionary of water bodies computed under potential inundation levels is constructed from the digital elevation model. Then, the actual flood extent is represented as a sparse linear combination of the water body dictionary. The inundation depth can be estimated because each water body from the linear combination is associated with an inundation level. To assess our proposed procedure, we computed the inundation depth of the flood in the town of Mabi, Okayama Prefecture, produced during the 2018 heavy rainfall. An average absolute value difference of about 60 cm between our results and a field survey performed by a third party was observed. Two other floods produced by the 2019 Hagibis typhoon were analyzed to illustrate the relevant information that can provide inundation depths.
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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.
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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.
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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.
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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.
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Seismic Risk Regularization for Urban Changes Due to Earthquakes: A Case of Study of the 2023 Turkey Earthquake Sequence
(MDPI, 2023-06-01)
Damage identification soon after a large-magnitude earthquake is a major problem for early disaster response activities. The faster the damaged areas are identified, the higher the survival chances of inhabitants. Current methods for damage identification are based on the application of artificial intelligence techniques using remote sensing data. Such methods require a large amount of high-quality labeled data for calibration and/or fine-tuning processes, which are expensive in the aftermath of large-scale disasters. In this paper, we propose a novel semi-supervised classification approach for identifying urban changes induced by an earthquake between images recorded at different times. We integrate information from a small set of labeled data with information from ground motion and fragility functions computed on large unlabeled data. A relevant consideration is that ground motion and fragility functions can be computed in real time. The urban changes induced by the 2023 Turkey earthquake sequence are reported as an evaluation of the proposed method. The method was applied to the interferometric coherence computed from C-band synthetic aperture radar images from Sentinel-1. We use only 39 samples labeled as changed and 9000 unlabeled samples. The results show that our method is able to identify changes between images associated with the effects of an earthquake with an accuracy of about 81%. We conclude that the proposed method can rapidly identify affected areas in the aftermath of a large-magnitude earthquake.
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Preliminary System for the Estimation of Peak Ground Acceleration Distribution in Metropolitan Lima and Callao: Application in Recent Seismic Events
(Fuji Technology Press, 2023-06-01)
The conjunction of seismic records and site effect parameters can lead to the adequate estimation of seismic indexes in urban areas. In this regard, this study uses the map of soil amplification factors obtained in previous studies and the availability of time history waveforms at different locations throughout Metropolitan Lima and Callao to estimate the geospa-tial distribution of maximum values of horizontal acceleration after the occurrence of earthquakes. Results for three earthquakes of intermediate magnitude and distinct epicenter locations are publicly available in an online system created within the frame-work of this study (Amaru Peru) and showed that am-plified motions could be mainly observed in the low-lands of populated slopes as well as in the eolian sandy deposits.
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Evaluating the Seismic Damage Dynamics of Buildings' Vertical Growth in Lima, Peru
(SAGE Publishing, 2026-02-01)
In Lima, as in many cities, most residential buildings grow vertically over their lifespan due to incremental construction. Multiple stories are added to buildings, often without structural retrofits or even without design. As a result, the seismic vulnerability of these buildings increases, requiring the government to create resilience policies that can keep up and bend the seismic risk growth. Unfortunately, little is known about the rate of vertical expansions and risk growth to develop regional risk policies for risk reduction. To address this gap, we surveyed 1311 buildings across four districts of Lima, comparing Google Street View imagery from 2013 to 2014 with field surveys from 2023. Using these data, we calibrated transition probability matrices within a Markov chain model to represent vertical growth dynamics. Results show that vertical expansion is faster in areas adjacent to primary roads compared to secondary ones. Applying the model to three recently established settlements, we projected future vertical growth and assessed its seismic implications. Under a simulated Mw 8.8 earthquake scenario, the probability of building collapse increases from less than 10% to over 30% within three decades. These findings show that vertical growth amplifies seismic risk in informal urban areas. Thus, our study highlights the importance of integrating vertical expansion into seismic risk assessments and policy discussions.
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