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Density currents, fluid flows driven by differences in density, play a crucial role in disaster prevention for water pollution and tsunami mitigation, particularly due to thermal releases from power plants. Understanding their dynamics is pivotal for effective mitigation strategies. While the influence of seabed and lake bottom topography on density currents is well-studied, research on how embankment shapes affect these currents has been limited. This study aimed to fill this gap by experimentally and numerically analyzing the flow dynamics of density currents using various embankment shapes in a controlled water tank environment. The findings revealed distinct variations in density perturbation across different embankment shapes. Specifically, density currents exhibited reduced head velocities in embankments shaped as right-angled triangles, rectangles, and L-shapes, in that sequential order. This research underscores the significance of embankment design in modifying density currents, offering valuable insights for optimizing disaster management strategies related to water pollution and tsunami hazards induced by thermal effluents from industrial sources. [ABSTRACT FROM AUTHOR]

Fire detection is a critical task in environmental monitoring and disaster prevention, with traditional methods often limited in their ability to detect fire and smoke in real time over large areas. The rapid identification of fire and smoke in both indoor and outdoor environments is essential for minimizing damage and ensuring timely intervention. In this paper, we propose a novel approach to fire and smoke detection by integrating a vision transformer (ViT) with the YOLOv5s object detection model. Our modified model leverages the attention-based feature extraction capabilities of ViTs to improve detection accuracy, particularly in complex environments where fires may be occluded or distributed across large regions. By replacing the CSPDarknet53 backbone of YOLOv5s with ViT, the model is able to capture both local and global dependencies in images, resulting in more accurate detection of fire and smoke under challenging conditions. We evaluate the performance of the proposed model using a comprehensive Fire and Smoke Detection Dataset, which includes diverse real-world scenarios. The results demonstrate that our model outperforms baseline YOLOv5 variants in terms of precision, recall, and mean average precision (mAP), achieving a mAP@0.5 of 0.664 and a recall of 0.657. The modified YOLOv5s with ViT shows significant improvements in detecting fire and smoke, particularly in scenes with complex backgrounds and varying object scales. Our findings suggest that the integration of ViT as the backbone of YOLOv5s offers a promising approach for real-time fire detection in both urban and natural environments. [ABSTRACT FROM AUTHOR]

There are differences between Western mainstream culture and traditional Indigenous culture in the way they address sustainable development. The spirit of sustainability has been emphasized and practiced by Indigenous cultures for hundreds or even thousands of years, but it is increasingly disappearing over time due to the threat of natural disasters. It is necessary to recover this practice of sustainable development from its roots in traditional Indigenous knowledge. This study considers the possibility and utility of incorporating science, technology, engineering, and mathematics (STEM) into Indigenous education for sustainability, a topic that has not been addressed by other studies. Based on a literature review, the proposed framework and content for this study focus on Indigenous disaster prevention. The specific topic was chosen to be most relevant to young Indigenous children. STEM indicators from the US next-generation science standards (NGSS) were referenced to create the proposed STEM teaching objectives, which were designed to be specifically appropriate for Indigenous curricula and teaching activities. Additionally, the cultural curriculum model was adopted to reform the Indigenous curriculum and teaching model by utilizing the transformation and social action approaches. Finally, the five-stage learning cycle was used as the framework to implement the curriculum, intertwined with the principles of the spiral curriculum, to co-construct an instructional example of Indigenous education for sustainability for future reference. [ABSTRACT FROM AUTHOR]

Facing persistent natural catastrophes, the necessity for disaster prevention products in afflicted cities becomes paramount. Modular design has proven to be a viable method for streamlining transportation and manufacturing processes for disaster prevention products. However, existing post-disaster prevention products often fail to incorporate the green modular concept, with limited research on spatial allocation strategies. In response to the current challenges, a new breed of green post-disaster prevention products is urgently warranted to mitigate the impact of major natural disasters and safeguard lives and property. To achieve the goal, this study employs a combined analytic hierarchy process (AHP) and geographic information systems (GIS) analysis to propose an inflatable cabin for emergency disaster prevention, specifically designed for flood scenarios. Using the inflatable cabin as an empirical case, this study introduces a layered design approach progressing from macro to meso and then to micro levels to construct an objective decision-making model to prioritize key design elements, develop spatial post-disaster prevention strategies, and analyze the mechanical performance. Results indicate that at a distance of 30 m from the base of the slope (SPIC), the impact force is most significant, reaching up to 1.8 × 10⁷ kN. As the distance increases from 30 m to 150 m, the maximum impact force decreases by an order of magnitude, and the average impact force decreases by approximately two orders of magnitude. Furthermore, this comprehensive approach, which starts from a holistic design perspective and culminates in optimizing individual disaster structures, offers practical significance for engineering design research. [ABSTRACT FROM AUTHOR]

A systematic understanding of the spatial distribution of meteorological disasters that affect cotton growth, such as rainstorms, gales, and hail, is important for reducing plant losses and promoting sustainable development. Our study aimed to evaluate the risk of meteorological disasters during cotton growth and analyze their spatial distribution and driving factors. A risk assessment model for major meteorological disasters during cotton cultivation in Xinjiang was established by integrating entropy weight methods and an analytic hierarchy process. A cotton meteorological disaster risk assessment index system, including the vulnerability of disaster-bearing bodies, hazards of disaster-causing factors, and exposure of disaster-bearing bodies, was constructed using Google Earth Engine. We determined the comprehensive risk levels of major meteorological disasters for cotton in various regions of Xinjiang. Research shows that the selection of indicators is very important, and crop risk assessment with a clear disaster-bearing body can make the results more accurate. It is necessary to consider the risk assessment of multiple disaster species for meteorological disaster risk assessment. The results revealed spatial differences in the meteorological disaster risk for cotton in 2020. The very high and high risks for cotton accounted for 42% of the cotton planting area, mainly distributed in Karamay, Tacheng, Kashgar, Changjizhou, Kezhou, and Ilizhou. Consequently, this study provides a scientific basis for cotton cultivation in Xinjiang, China. [ABSTRACT FROM AUTHOR]

In response to the adverse effects of climate change-induced frequent extreme disasters on agricultural production and supply stability, this study develops a comprehensive agricultural disaster prevention system based on current adaptation strategies for mitigating agricultural meteorological disasters. The primary goal is to enhance disaster preparedness and recovery through three core platforms: a fine-scale weather forecast service system, a crop disaster early warning system, and an agricultural information service platform for disasters. The results show that every major agricultural production township in Taiwan now has dedicated agricultural weather stations and access to refined weather forecasts. Additionally, a disaster prevention calendar for 76 important crops is established, integrating cultivation management practices and critical disaster thresholds for different growth periods. Utilizing this calendar, the crop disaster early warning system can provide timely disaster-related information and pre-disaster prevention assistance to farmers through various information dissemination tools. As a disaster approaches, the agricultural information service platform for disasters provides updates on current crop growth conditions. This service not only pinpoints areas at higher risk of disasters and vulnerable crop types but also offers mitigation suggestions to prevent potential damage. Administrative efficiency is then improved with a response mechanism incorporating drones and image analysis for early disaster detection and rapid response. In summary, the collaborative efforts outlined in this study demonstrate a proactive approach to agricultural disaster prevention. By leveraging technological advancements and interdisciplinary cooperation, the aim is to safeguard agricultural livelihoods and ensure food security in the face of climate-induced challenges. [ABSTRACT FROM AUTHOR]

Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage grade prediction by fire based on simplified building information. This paper's primary objective is to propose and verify a framework for predicting the scale of property damage caused by fire using machine learning (ML). Korean public datasets are collected and preprocessed, and ML algorithms are trained with only 15 input data using building register and fire scenario information. Four models (artificial neural network (ANN), decision tree (DT), k-nearest neighbor (KNN), and random forest (RF)) are used for ML. The RF model is the most suitable for this study, with recall and precision of 74.2% and 73.8%, respectively. Structure, floor, causes, and total floor area are the critical factors that govern the fire size. This study proposes a novel approach by utilizing ML models to accurately and rapidly predict the size of fire damage based on basic building information. By analyzing domestic fire incident data and creating fire scenarios, a similar ML model can be developed. [ABSTRACT FROM AUTHOR]

The Taipei Dome Complex is located in Taipei, Taiwan. It is a composite park with a multi-functional dome and incorporates a shopping mall, restaurants, cinemas, and an office building. In 2017, Taipei, Taiwan hosted the Universiade, and thousands of people protested. Smoke bombs were thrown, and the police were attacked. Due to its location in the "Circum-Pacific seismic belt" and the fact it is affected by the subtropical monsoon climate, Taiwan suffers frequent natural disasters. We aim to define the security risk factors for the Taipei Dome Complex by assessing flood simulation from the National Science and Technology Center for Disaster Reduction, earthquake simulation of the Taiwan Earthquake Loss Estimation System (TELES), and a case study of a terrorist attack. We propose 24 risk factors from five major perspectives: equipment safety, traffic accidents, human resources, security management, and disaster events. [ABSTRACT FROM AUTHOR]

Emphasizing the need to provide a coordinated flood management strategy in the country and avoid acting in an isolated way when it occurs, improving the attitude of flood control during floods, and controlling floods with comprehensive analysis are among the main purposes of the current study. In this study, the environment's physical, technological, social, economic, and political characteristics are considered to assess the urban flood risk. This study entails a discussion of flood hazard control in Benin City, the capital city of Edo State of Nigeria. The research methodology involves employing both interviews and questionnaire distribution. First, three key persons involved in flood control are interviewed at the State Emergency Management Agency (SEMA), which coordinates disaster risk reduction in the state, and then, the responses are classified into themes that are used to prepare the questionnaire to be distributed in four main regions. The questionnaires are distributed to the employees in institutions concerned with flood control and to the general population living in the region. Based on the obtained results from the interviews, some methods that could be applicable in controlling flooding in the region are listed. The results showed that the most important ones are flood warning systems, flood prevention through using the building resilient infrastructure and community programs, protection and mitigation through using natural processes, and strategic implementation of a flood emergency plan through sustainability. [ABSTRACT FROM AUTHOR]

This study examines the effectiveness of parapets in preventing overtopping failures of small-scale homogeneous reservoir dams under seismic loads. In this study, a parapet covered the entire width of the dam crest and was designed to ensure its weight is transmitted to the dam crest. The test included four modes: initial mode, first seepage, seismic, and second seepage. The results show that without parapets the crack length and width expand significantly in the dam crest during the seismic mode, and the effect was large in the second seepage mode. The crack depth increased by 11.3–24 times during the seismic mode and expanded up to 73.3% of the dam height in the longitudinal direction along the axis of the crack formed in the dam crest during the second seepage mode. These findings suggest that the earthquake weakened the dam body, making it vulnerable to penetration. In contrast, the parapet structure effectively suppressed most of the tensile cracks by increasing the constraint force. Additionally, no crack expansion or tearing occurred during the second seepage mode post-earthquake, indicating improved seismic performance and suppression of seepage deformation. [ABSTRACT FROM AUTHOR]

In recent years, a combination of forestry decline and global climate change has led to heavy rains and landslides in Japan that have caused extensive forest damage through woody debris outflow. The current configuration of impermeable sabo dams has insufficient capacity to capture woody debris under these conditions; therefore, improvements to permeable sabo dams, which have a high woody debris capture capacity, are underway; these sometimes involve the addition of steel fittings. In this study, we examined the effectiveness of such measures in consideration of the factors affecting woody debris flow. After reviewing a woody debris outflow that occurred during a heavy rain disaster in northern Kyushu, Japan, we propose woody debris countermeasures that consider basin and runoff characteristics. Our results indicate that woody debris flow occurs later than sediment flow. Therefore, we performed experiments to test the effectiveness of various methods to slow water flow using the terrain conditions at the nearest valley outflow point. Finally, we propose woody debris countermeasure policies considering basin characteristics, to promote the future preservation of river basins. [ABSTRACT FROM AUTHOR]

Gravel and sediment frequently build up in holes during the anchor cable installation process, which makes it harder to install the anchor cable and causes reinforcement to fail, which can lead to accidents. In this paper, a bit anchor setup approach is proposed to set up a drill bit at the front of the anchor cable to aid the anchor cable drilling. The feasibility of this approach is established with the aid of DEM-MBD joint simulation and proves the correctness of the simulation model. The major elements affecting drilling effectivity have been studied by the use of 'check + simulation'. The effects exhibit that the axial velocity and working aperture are negatively correlated with the drilling resistance of the anchor cable; the feed price is positively related to the anchor cable drilling resistance; with the increase in anchor cable pitch, the drilling resistance of the anchor cable changes into a hump shape. When the bit is 0.2 m from the backside of the hole, the particle pace vector at the decrease stop of the bit gives a conical distribution. This paper is of fantastic magnitude in relation to the environment-friendly setup of anchor cables and protection against disasters. [ABSTRACT FROM AUTHOR]

Coal resources have always been the focus of attention in the field of sustainable development. Based on the problem of surrounding rock control in close-distance coal seams, first, a mechanical model of floor failure was established based on the 29204 working face in Dongqu Mine; the failure mechanism of the floor was revealed by the zero displacement line, and a method to judge the occurrence state of the roof in the lower coal seam was put forward. Furthermore, by FLAC3D numerical simulation software, the mechanical model is verified, and the optimal support parameters are optimized, and the optimal water–cement ratio and grouting pressure are determined to be 0.6 and 3 MPa respectively. The application shows that the roof displacement is reduced by about 73.48% compared with the control group. Compared with the control group, the cable stress decreased by about 50.68%, and the application effect is remarkable. The research results provide an effective solution to ensure the sustainable development of coal resources and disaster prevention. [ABSTRACT FROM AUTHOR]

Recently, concerns about ecosystem loss and the threat of disasters have emerged. Understanding people's perception of the ecosystem's value will lead to disaster adaptation through ecosystem conservation. We incorporated use and disaster attributes into a contingent valuation study to investigate Japanese peoples' perceptions of the value of various ecosystems. We construct a concept representing ecosystems' perceived disaster prevention and mitigation functions by investigating the effects of use status and disaster concerns on people's preferences. Results revealed that almost all of the ecosystem's disaster prevention and mitigation functions are not perceived by people. In some cases, people mistakenly avoid ecosystems that protect people from disasters. In conclusion, this concept and its findings facilitate an understanding of people's perceptions of disaster prevention mitigation functions of ecosystems and promote the concrete practice of conserving ecosystems. [ABSTRACT FROM AUTHOR]

Quantitative probability has been computed for the tsunami hazard posed by earthquakes from the Manila Trench, which has been regarded as a huge threat in the South China Sea. This study provides a spatial distribution of the tsunami hazard covering the affected area with a spatial resolution of 0.1° for disaster prevention of islands and continental coasts. The quantitative probability of the tsunami hazard is computed by an efficient model, which can realize a large amount of potential tsunami scenarios analysis in order to consider the randomness and uncertainty in earthquake magnitude, source location and focal depth. In the model, for each potential tsunami scenario, the occurrence probability of the corresponding earthquake and the intensity of tsunami waves at each target location are computed. The occurrence probability of each scenario is estimated based on the historical earthquake records. Then, the subsequent tsunami caused by each scenario is computed using a new, efficient approach, instead of direct simulation using an ocean dynamics model. A total of 1,380,000 scenarios are computed in order to obtain a stable statistical result. Based on the results, the spatial distribution of the tsunami hazard is discussed and high-hazard regions along the coast have been identified. [ABSTRACT FROM AUTHOR]

Earthquakes threaten humanity globally in complex ways that mainly include various socioeconomic consequences of life and property losses. Resilience against seismic risks is of high importance in the modern world and needs to be sustainable. Sustainable earthquake resilience (SER) from the perspective of structural engineering means equipping the built environment with appropriate aseismic systems. Shape memory alloys (SMAs) are a class of advanced materials well suited for fulfilling the SER demand of the built environment. This article explores how this capability can be realized by the innovative SMA-based superelasticity-assisted slider (SSS), recently proposed for next-generation seismic protection of structures. The versatility of SSS is first discussed as a critical advantage for an effective SER. Alternative configurations and implementation styles of the system are presented, and other advantageous features of this high-tech isolation system (IS) are studied. Results of shaking table experiments, focused on investigating the expected usefulness of SSS for seismic protection in hospitals and conducted at the structural earthquake engineering laboratory of the University of Bonab, are then reported. SSS is compared with currently used ISs, and it is shown that SSS provides the required SER for the built environments and outperforms other ISs by benefitting from the pioneered utilization of SMAs in a novel approach. [ABSTRACT FROM AUTHOR]

The safety inspection capability of construction sites before typhoons could be improved using a UAV, which has a rapid identification capability. However, the main safety inspection items need construction experience and technical safety specifications. This study aimed to obtain the influencing factors of typhoon and their weight proportion through the knowledge of disaster theory and the analytic hierarchy process (AHP). The effectiveness of this method was verified by collecting and analyzing the field data at the construction site. A set of construction site early warning flows and disaster prevention and mitigation measures for typhoons are proposed. The results show that UAVs can be used as a tool in this scenario, helping to improve disaster prevention and enhancing the capability of construction site management to evaluate typhoon risk. The research provides a much-needed common ground for collecting and analyzing advances in UAVs and immersive technologies, as well as their influence on building projects. Furthermore, this article provides a new horizon for beginner researchers working on digitalized construction research. [ABSTRACT FROM AUTHOR]

The development of disaster prevention literacy is not listed as a compulsory course in the K-12 education system in Taiwan, and there are very few academic departments that focus mainly on disaster prevention education in the domestic higher education system. For Taiwan, where disasters are relatively frequent, it is indispensable for every citizen to have the proper disaster prevention knowledge and response skills. In recent years, education courses related to disaster prevention have been gradually set up in general education courses in universities and colleges in response to the trend. This study took students of the elective courses on disaster prevention education in the general education courses of universities as the experimental subjects. Supplemented by the social participation course operation model, the cooperation of team members during the course can bring students a different experiential value to further achieve the teaching goal of improving learning achievement and feedback. It was found from the research results that: (1) the appropriate disaster prevention course arrangement can bring positive and significant effects on the dimensions of perceived experience and team interaction; (2) the learning mode of the university disaster prevention education course, combined with the social participation course operation model, was helpful to the improvement of experiential value and learning achievement; (3) the mediation regression analysis showed the cooperation mode of group team members' interaction did have a partial mediation effect in terms of experiential value, as well as learning achievement and feedback compared with the traditional pure classroom teaching model. The research results indicated that the teaching effectiveness of the disaster prevention education course for college students with the social participation course operation model was good. [ABSTRACT FROM AUTHOR]

Few studies currently examine the effect of different disaster informational programmes because conducting such intervention studies is challenging. By providing two types of online disaster learning programmes, this intervention study measured changes made to three different perspectives: (1) disaster preventive awareness scores, (2) willingness to pay for disaster information (WTP), and (3) settlement preferences (preferences for post-disaster recovery goals). The participants engaged with one of two different types of 45-min learning programmes—one created as a narrative-based disaster learning programme (N = 218) and the other presented as a collective information disaster learning programme (N = 201). Consequently, both disaster preparedness scores and WTP increased statistically after both styles of disaster preparedness programmes. Furthermore, the increase generated by the narrative programme was greater (2.2 times higher for WTP value and 1.72 times higher in WTP value-increased probability). In their preprogramme answer, people who selected safety and nature conservation for post-disaster recovery goals improved their awareness scores. Despite both programmes having the same theme and length, only the narrative learning programme had a beneficial—improvement odds ratio for all three perspectives. Thus, the narrative-based disaster learning (vicarious) experience simultaneously improved people's disaster awareness scores, willingness to pay for disaster information, and settlement preferences for disaster prevention. [ABSTRACT FROM AUTHOR]

Recently, global climate change has led to a high incidence of extreme weather and natural disasters. How to reduce its impact has become an important topic. However, the studies that both consider the disaster's real-time geographic information and environmental factors in severe rainstorms are still not enough. Volunteered geographic information (VGI) data that was generated during disasters offered possibilities for improving the emergency management abilities of decision-makers and the disaster self-rescue abilities of citizens. Through the case study of the extreme rainstorm disaster in Zhengzhou, China, in July 2021, this paper used machine learning to study VGI issued by residents. The vulnerable people and their demands were identified based on the SOS messages. The importance of various indicators was analyzed by combining open data from socio-economic and built-up environment elements. Potential safe areas with shelter resources in five administrative districts in the disaster-prone central area of Zhengzhou were identified based on these data. This study found that VGI can be a reliable data source for future disaster research. The characteristics of rainstorm hazards were concluded from the perspective of affected people and environmental indicators. The policy recommendations for disaster prevention in the context of public participation were also proposed.

Rural areas are vulnerable to natural disasters and tend to suffer severe losses. An EF4 tornado occurred in Funing on 23 June 2016, killing 99 people, injuring at least 846 people, and destroying more than 2000 houses. Using a multinomial logistic regression model, this study explored the influencing factors between housing damage and variables of building conditions, tornado intensity, and village environmental factors. The results show that 2-story houses and masonry houses were more likely to be slightly damaged or be in a dangerous state. Furthermore, the building area was positively related to houses in two categories: slight damage (SD) and dangerous and requiring immediate repair (DR), indicating that the larger or taller the house, the more severe the damage. In terms of tornado intensity, houses classified as SD were more likely to be hit by EF4 tornados than by EF3 tornados, and houses were damaged more by EF1 or EF2 tornados. This finding demonstrates that the level of housing damage was not strongly correlated with the tornado intensity. Slightly damaged houses exhibited the highest correlation with environmental factors. The proportion of slightly damaged houses was positively correlated with the water area in the village, unlike the proportion of houses in the DR and unable to be repaired (UR) categories. Moreover, the larger the water area of a village, the less housing damage it suffered. These findings provide new insights into minimizing housing damage in wind disasters to improve disaster prevention planning in rural areas.

Public participation in community-organized disaster mitigation activities is important for improving disaster mitigation capacity. With data from 260 questionnaires, this study compared the current status of public participation in model disaster mitigation communities and nonmodel communities in a geological-disaster-prone area. Three community-organized disaster mitigation education activities were compared cross-sectionally. A binary logistic regression was used to analyze the effects of attitude, perceived behavioral control, disaster experience, and other key factors on the public's choice to participate in community disaster mitigation activities. The analysis results indicated that model communities had higher public participation in two efforts, evacuation drills and self-help skills training, and lower participation in activities that invited them to express their feedback than nonmodel communities. The influence of attitudinal factors on the decision to participate in disaster mitigation activities had a high similarity across community types. The public participation in model disaster mitigation communities is influenced by factors such as subjective norms and participation cognition; the behavior of people in nonmodel communities is influenced by factors such as previous experience with disasters, perceived behavioral control, risk perception, and participation cognition and has a greater potential for disaster mitigation community construction. This study provides practical evidence and theoretical support for strengthening the sustainable development of disaster mitigation community building.

Many countries lack clear legal requirements on the distance between buildings and petrol station facilities. The regulations in force directly determine the petrol station facilities' required distance to buildings, and such distances are considered relevant for newly designed and reconstructed buildings. Public buildings must be located no closer than 60 m to the above-ground liquefied gas tanks and liquid gas dispensers. Still, based on engineering calculations and the applied technical measures, it is possible to determine a safe distance for buildings that are constructed, extended and reconstructed, to which superstructures are added or whose utilisation method changes. The paper presents the results of calculations devoted to determining a safe distance between public buildings and LPG filling station facilities, using selected analytical models. The analyses were carried out for the LPG gas system commonly used in petrol stations, consisting of two gas storage tanks of 4.85 m 3 capacity each, and a dispenser. It is legitimate to eliminate the obligation to observe the 60 m distance between LPG filling stations and public buildings and the mandatory distance of 60 m between liquefied gas dispensers and public buildings is not justified in light of the implemented requirements to use various protections at self-service liquefied gas filling stands.

In the context of global changes, nature-based solutions (NBSs) increasingly draw attention as a possible way to reduce disaster risk associated with extreme hydro-meteorological events while providing human well-being and biodiversity benefits at the same time. The PHUSICOS platform is dedicated to gather and analyse relevant NBSs used to reduce disaster risk associated with extreme hydro-meteorological events in mountainous and hilly lands. To design the platform, an in-depth review of 11 existing platforms has been performed. The PHUSICOS platform currently references 152 literature NBS cases and is continuously enriched through the contribution of NBS community. The platform also proposes a qualitative assessment of the NBSs collected according to 15 criteria related with five ambits: "disaster risk reduction", "technical and economical feasibility", "environment", "society", and "local economy". This paper presents the structure of the platform and a first analysis of its content. [ABSTRACT FROM AUTHOR]

In this work, we explored a novel approach to integrate both geo-environmental and soil geomechanical parameters in a landslide susceptibility model. A total of 179 shallow to deep landslides were identified using Google Earth images and field observations. Moreover, soil geomechanical properties of 11 representative soil samples were analyzed. The relationship between soil properties was evaluated using the Pearson correlation coefficient and geotechnical diagrams. Membership values were assigned to each soil property class, using the fuzzy membership method. The information value method allowed computing the weight value of geo-environmental factor classes. From the soil geomechanical membership values and the geo-environmental factor weights, three landslide predisposition models were produced, two separate models and one combined model. The results of the soil testing allowed classifying the soils in the study area as highly plastic clays, with high water content, swelling, and shrinkage potential. Some geo-environmental factor classes revealed their landslide prediction ability by displaying high weight values. While the model with only soil properties tended to underrate unstable and stable areas, the model combining soil properties and geo-environmental factors allowed a more precise identification of stability conditions. The geo-environmental factors model and the model combining geo-environmental factors and soil properties displayed predictive powers of 80 and 93%, respectively. It can be concluded that the spatial analysis of soil geomechanical properties can play a major role in the detection of landslide prone areas, which is of great interest for site selection and planning with respect to sustainable development at Mount Oku.

Subway infrastructure is a representative urban infrastructure for sustainable urban development as part of its policy to harmonize with economic growth. As the transportation infrastructure of large cities develops with high speed and intelligence, more attention will be paid to its safety. The main cause of death in subway fires is asphyxiation, due to the closed specificity of the underground space. Therefore, smoke exhaust facilities should be capable of minimizing the effects of smoke to ensure the safe evacuation of passengers in the event of fire. In this study, three kinds of fire locations are adopted to analyze the distribution of platform temperature, CO, and visibility in connection with the smoke exhaust system operation method. We evaluate the performance of the applicable smoke exhaust system from ASET-based untenable area analysis. Fatality evaluation by escape analysis according to the smoke exhaust system estimates the fatality based on the tenability performance evaluation. Moreover, the FED method was used to evaluate tenability performance. Therefore, the result of this study suggests a solution for sustainable subway Disaster response from the performance evaluation of the subway platform smoke exhaust system for safe evacuation of passengers, which is essential for subway construction or remodeling. [ABSTRACT FROM AUTHOR]

This paper reviews the efforts made and experiences gained in developing the Flood Prevention and Emergency Response System (FPERS) powered by Google Earth Engine, focusing on its applications at the three stages of floods. At the post-flood stage, FPERS integrates various remote sensing imageries, including Formosat-2 optical imagery to detect and monitor barrier lakes, synthetic aperture radar imagery to derive an inundation map, and high-spatial-resolution photographs taken by unmanned aerial vehicles to evaluate damage to river channels and structures. At the pre-flood stage, a huge amount of geospatial data are integrated in FPERS and are categorized as typhoon forecast and archive, disaster prevention and warning, disaster events and analysis, or basic data and layers. At the during-flood stage, three strategies are implemented to facilitate the access of the real-time data: presenting the key information, making a sound recommendation, and supporting the decision-making. The example of Typhoon Soudelor in August of 2015 is used to demonstrate how FPERS was employed to support the work of flood prevention and emergency response from 2013 to 2016. The capability of switching among different topographic models and the flexibility of managing and searching data through a geospatial database are also explained, and suggestions are made for future works. [ABSTRACT FROM AUTHOR]