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New Directions in Hazard and Disaster Science: Advances in Applied...
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New Directions in Hazard and Disaster Science: Advances in Applied Sciences

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: closed (20 August 2020) | Viewed by 40118
Related Special Issue: New Directions in Hazard and Disaster Science: Advances in Applied Sciences II

Special Issue Editor

Prof. Dr. Jason Levy

E-Mail Website
Guest Editor
Disaster Preparedness and Emergency Management, University of Hawaii, 2540 Dole Street, Honolulu, HI 96822, USA
Interests: epidemiology and prevention of congenital anomalies; psychosis and affective psychosis; cancer epidemiology and prevention; molecular and human genome epidemiology; evidence synthesis related to public health and health services research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Hazards, risk and disasters—including geologic and hydrological processes, intentional threats, and health-related crises—are a growing menace to sustainability, economic development, and global security. For example, there are a wide variety of natural hazards (volcanic eruptions, earthquakes, landslides, mudflows, sinkholes, snow avalanches, flooding, and tsunamis) that pose a critical threat to pivotal infrastructure systems and life safety. Every year, terrorist attacks, severe natural events, and epidemics damage cause injuries and deaths on a large scale. Advances in hazard and disaster science and management are needed to cope with potentially hazardous human threats as well as geoprocesses.

This Special Issue examines a new set of applied science tools in the Big Data era that that can help to reduce the impact of these natural, technologic, intentional, and health-related threats. There are advances in applied sciences that can directly reduce the likelihood, impact, and vulnerability of communities to disaster: remote sensing; electrical, electronics, and communications engineering; nanotechnology and applied nanosciences; mechanical and civil engineering; applied biosciences and bioengineering; environmental and sustainable science and technology; applied physics; computing and artificial intelligence; earth sciences and geography; and applied industrial technologies. For example, new approaches in data science and machine learning capitalize on the ubiquity of risk and hazard data sets, as well as advances in remote sensing, global position systems, and GIS. These solutions also provide new opportunities for the analysis and management of all types of disaster risks.

Prof. Dr. Jason K. Levy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Applied industrial technologies for managing natural hazards
  • Environmental and sustainable science and technology and disaster prevention
  • Technologic risks and critical infrastructure protection
  • Systems engineering for disaster risk reduction
  • Geohazards analysis with earth sciences and geography

Published Papers (10 papers)

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Research

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15 pages, 606 KiB  
Article
DisKnow: A Social-Driven Disaster Support Knowledge Extraction System
by João Boné, Mariana Dias, João C. Ferreira and Ricardo Ribeiro
Appl. Sci. 2020, 10(17), 6083; https://0-doi-org.brum.beds.ac.uk/10.3390/app10176083 - 02 Sep 2020
Cited by 4 | Viewed by 2502
Abstract
This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, [...] Read more.
This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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23 pages, 13731 KiB  
Article
Trialing Innovative Technologies in Crisis Management—“Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response
by Elisa Schröter, Ralph Kiefl, Eric Neidhardt, Gaby Gurczik, Carsten Dalaff and Konstanze Lechner
Appl. Sci. 2020, 10(11), 3743; https://0-doi-org.brum.beds.ac.uk/10.3390/app10113743 - 28 May 2020
Cited by 8 | Viewed by 2521
Abstract
Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but [...] Read more.
Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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14 pages, 2196 KiB  
Article
Conversation-Based School Building Inspection Support System
by Meng-Han Tsai, Hao-Yung Chan and Liang-Yuan Liu
Appl. Sci. 2020, 10(11), 3739; https://0-doi-org.brum.beds.ac.uk/10.3390/app10113739 - 28 May 2020
Cited by 11 | Viewed by 3265
Abstract
A conversation-based system is proposed for supporting assessors in performing existing school building inspections. School building safety is a pressing issue; however, some difficulties in the overall process require solutions or improvements, including the complexity of building inspection tasks, the restrictions posed by [...] Read more.
A conversation-based system is proposed for supporting assessors in performing existing school building inspections. School building safety is a pressing issue; however, some difficulties in the overall process require solutions or improvements, including the complexity of building inspection tasks, the restrictions posed by the paperwork process, and the ineffectiveness of the management of existing school building inspections. In this study, we developed a conversation-based building inspection support system to reduce such problems, with the proposed system notifying and guiding assessors to complete building inspections, combined with a dashboard for managers to consume reports to determine whether further assessments or retrofits are required. The process of school building inspections was digitalized, with a chatbot implemented that features notifications either according to a routine inspection schedule or postseismic events, a conversation-based interface for guiding nonprofessional assessors, the integration of intuitive activation of inspections after receiving notifications, the use of multimedia to show damage directly without the possibility of mistakes, and data visualization for supporting managerial decision-making to enhance the quality and accuracy of budget allocation. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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19 pages, 10449 KiB  
Article
Novel Ensemble Landslide Predictive Models Based on the Hyperpipes Algorithm: A Case Study in the Nam Dam Commune, Vietnam
by Quoc Cuong Tran, Duc Do Minh, Abolfazl Jaafari, Nadhir Al-Ansari, Duc Dao Minh, Duc Tung Van, Duc Anh Nguyen, Trung Hieu Tran, Lanh Si Ho, Duy Huu Nguyen, Indra Prakash, Hiep Van Le and Binh Thai Pham
Appl. Sci. 2020, 10(11), 3710; https://0-doi-org.brum.beds.ac.uk/10.3390/app10113710 - 27 May 2020
Cited by 37 | Viewed by 3425
Abstract
Development of landslide predictive models with strong prediction power has become a major focus of many researchers. This study describes the first application of the Hyperpipes (HP) algorithm for the development of the five novel ensemble models that combine the HP algorithm and [...] Read more.
Development of landslide predictive models with strong prediction power has become a major focus of many researchers. This study describes the first application of the Hyperpipes (HP) algorithm for the development of the five novel ensemble models that combine the HP algorithm and the AdaBoost (AB), Bagging (B), Dagging, Decorate, and Real AdaBoost (RAB) ensemble techniques for mapping the spatial variability of landslide susceptibility in the Nam Dan commune, Ha Giang province, Vietnam. Information on 76 historical landslides and ten geo-environmental factors (slope degree, slope aspect, elevation, topographic wetness index, curvature, weathering crust, geology, river density, fault density, and distance from roads) were used for the construction of the training and validation datasets that are the prerequisites for building and testing the proposed models. Using different performance metrics (i.e., the area under the receiver operating characteristic curve (AUC), negative predictive value, positive predictive value, accuracy, sensitivity, specificity, root mean square error, and Kappa), we verified the proficiency of all five ensemble learning techniques in increasing the fitness and predictive powers of the base HP model. Based on the AUC values derived from the models, the ensemble ABHP model that yielded an AUC value of 0.922 was identified as the most efficient model for mapping the landslide susceptibility in the Nam Dan commune, followed by RABHP (AUC = 0.919), BHP (AUC = 0.909), Dagging-HP (AUC = 0.897), Decorate-HP (AUC = 0.865), and the single HP model (AUC = 0.856), respectively. The novel ensemble models proposed for the Nam Dan commune and the resultant susceptibility maps can aid land-use planners in the development of efficient mitigation strategies in response to destructive landslides. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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14 pages, 8405 KiB  
Article
Mine Fire Behavior under Different Ventilation Conditions: Real-Scale Tests and CFD Modeling
by Florencio Fernández-Alaiz, Ana Maria Castañón, Fernando Gómez-Fernández and Marc Bascompta
Appl. Sci. 2020, 10(10), 3380; https://0-doi-org.brum.beds.ac.uk/10.3390/app10103380 - 13 May 2020
Cited by 16 | Viewed by 2754
Abstract
Fires in underground spaces are especially relevant due to their potential mortality. However, there is not much research in real-scale spaces done so far. In this study, several fire scenarios were analyzed in an underground drift, taking into account the main environmental variables: [...] Read more.
Fires in underground spaces are especially relevant due to their potential mortality. However, there is not much research in real-scale spaces done so far. In this study, several fire scenarios were analyzed in an underground drift, taking into account the main environmental variables: airflow, temperature, oxygen, and pollutants. The behavior before and after the fire load was determined, as well as the evolution of the fire over time throughout the drift and its cross-section, finding important trends of the fire based on the airflow–fuel load ratio. Furthermore, the five most representative scenarios were modeled using the fire dynamics simulator (FDS). Results obtained in the simulations, with the adjusted parameters, display a good correlation between simulated and experimental values, being able to extrapolate these values to know the performance of potential fires in other underground spaces or mines. The outcomes could also be a very useful tool to study the effectiveness of possible emergency measures or the potential impact of a fire in this type of environments. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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20 pages, 12923 KiB  
Article
Integral Seismic Risk Assessment through Fuzzy Models
by J. Rubén G. Cárdenas, Àngela Nebot and Francisco Mugica
Appl. Sci. 2020, 10(9), 3017; https://0-doi-org.brum.beds.ac.uk/10.3390/app10093017 - 26 Apr 2020
Cited by 2 | Viewed by 1897
Abstract
The usage of indicators as constituent parts of composite indices is an extended practice in many fields of knowledge. Even if rigorous statistical analyses are implemented, many of the methodologies follow simple arithmetic assumptions to aggregate indicators to build an index. One of [...] Read more.
The usage of indicators as constituent parts of composite indices is an extended practice in many fields of knowledge. Even if rigorous statistical analyses are implemented, many of the methodologies follow simple arithmetic assumptions to aggregate indicators to build an index. One of the consequences of such assumptions can be the concealment of the influence of some of the composite index’s components. We developed a fuzzy method that aggregates indicators using non-linear methods and, in this paper, compare it to a well-known example in the field of risk assessment, called Moncho’s equation, which combines physical and social components and uses a linear aggregation method to estimate a level of seismic risk. By comparing the spatial pattern of the risk level obtained from these two methodologies, we were able to evaluate to what extent a fuzzy approach allows a more realistic representation of how social vulnerability levels might shape the seismic risk panorama in an urban environment. We found that, in some cases, this approach can lead to risk level values that are up to 80% greater than those obtained using a linear aggregation method for the same areas. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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17 pages, 2000 KiB  
Article
Evaluating Seismic Soil Liquefaction Potential Using Bayesian Belief Network and C4.5 Decision Tree Approaches
by Mahmood Ahmad, Xiao-Wei Tang, Jiang-Nan Qiu and Feezan Ahmad
Appl. Sci. 2019, 9(20), 4226; https://0-doi-org.brum.beds.ac.uk/10.3390/app9204226 - 10 Oct 2019
Cited by 37 | Viewed by 3590
Abstract
Liquefaction is considered a damaging phenomenon of earthquakes and a major cause of concern in civil engineering. Therefore, its predictory assessment is an essential task for geotechnical experts. This paper investigates the performance of Bayesian belief network (BBN) and C4.5 decision tree (DT) [...] Read more.
Liquefaction is considered a damaging phenomenon of earthquakes and a major cause of concern in civil engineering. Therefore, its predictory assessment is an essential task for geotechnical experts. This paper investigates the performance of Bayesian belief network (BBN) and C4.5 decision tree (DT) models to evaluate seismic soil liquefaction potential based on the updated and relatively large cone penetration test (CPT) dataset (which includes 251 case histories), comparing them to a simplified procedure and an evolutionary-based approach. The BBN model was developed using the K2 machine learning algorithm and domain knowledge (DK) with data fusion methodology, while the DT model was created using a C4.5 algorithm. This study shows that the BBN model is preferred over the others for evaluation of seismic soil liquefaction potential. Owing to its overall performance, simplicity in practice, data-driven characteristics, and ability to map interactions between variables, the use of a BBN model in assessing seismic soil liquefaction is quite promising. The results of a sensitivity analysis show that ‘equivalent clean sand penetration resistance’ is the most significant factor affecting liquefaction potential. This study also interprets the probabilistic reasoning of the robust BBN model and most probable explanation (MPE) of seismic soil liquefied sites, based on an engineering point of view. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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17 pages, 9659 KiB  
Article
Dome Roof Fall Geohazards of Full-Seam Chamber with Ultra-Large Section in Coal Mine
by Rui Gao, Hongchun Xia, Kun Fang and Chunwang Zhang
Appl. Sci. 2019, 9(18), 3891; https://0-doi-org.brum.beds.ac.uk/10.3390/app9183891 - 17 Sep 2019
Cited by 8 | Viewed by 2537
Abstract
The roof fall hazard is more likely to take place within chamber with ultra-large section, which would not only damage mechanical equipment, but also cause casualties. In this paper, the strap joint chamber of the Tashan coal mine is studied, and finite and [...] Read more.
The roof fall hazard is more likely to take place within chamber with ultra-large section, which would not only damage mechanical equipment, but also cause casualties. In this paper, the strap joint chamber of the Tashan coal mine is studied, and finite and discrete element method (FDEM) is used to establish the numerical model of the roof fall of the chamber dome. The simulation results show that the chamber dome mainly undergoes shear failure and forms a large number of cracks. With further development and penetration of cracks, a distinct roof separation is found in the chamber dome. When the crack develops to the dome surface of the chamber, under the effect of the mine pressure, the coal body is separated from the surface of the chamber and the roof fall hazard occurs. Based on the mechanism of roof fall hazard of the chamber dome, it is concluded that improving the shear strength of the surrounding rock and reducing the crack penetration are the main ways to control the roof fall. Therefore, the high-strength anchor bolt and cable support is adopted to fill the cracks and improve the shear strength of the surrounding rock. The result showed that the roof separation of the chamber dome in the field is confined to 0.012 m. The surrounding rock is well controlled and no roof fall occurs. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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18 pages, 8184 KiB  
Article
The Prevention and Control Mechanism of Rockburst Hazards and Its Application in the Construction of a Deeply Buried Tunnel
by Heng Zhang, Yimo Zhu, Liang Chen, Weidong Hu and Shougen Chen
Appl. Sci. 2019, 9(17), 3629; https://0-doi-org.brum.beds.ac.uk/10.3390/app9173629 - 03 Sep 2019
Cited by 11 | Viewed by 5073
Abstract
Rockburst hazards induced by high geostress are particularly prominent during the construction of underground engineering. Prevention and control of rockburst is still a global challenge in the field of geotechnical engineering, which is of great significance. Based on the tunnel group of the [...] Read more.
Rockburst hazards induced by high geostress are particularly prominent during the construction of underground engineering. Prevention and control of rockburst is still a global challenge in the field of geotechnical engineering, which is of great significance. Based on the tunnel group of the Jinping II hydropower station of China, this paper analyzed the mechanical principle of support in the process of construction, and discussed in detail the active release and passive support by numerical simulation and field application. The results show that as two active measures, stress relieve holes and advanced stress relief blasting can release the energy of the microseismic source and transfer the high stress to the deeper surrounding rock, make the surface rock wall with a relatively low stress act as a protective barrier. Their stress release rate is about 12% and 33% in this project, respectively. In term of passive measure, the combined rapid support, which is mainly composed of water swelling anchor and nano-admixture shotcrete, is also an effective way to prevent and control the rockburst under high geostress. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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Review

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34 pages, 5554 KiB  
Review
Risk Assessment Methods in Mining Industry—A Systematic Review
by Agnieszka Tubis, Sylwia Werbińska-Wojciechowska and Adam Wroblewski
Appl. Sci. 2020, 10(15), 5172; https://0-doi-org.brum.beds.ac.uk/10.3390/app10155172 - 28 Jul 2020
Cited by 38 | Viewed by 11893
Abstract
Recently, there has been a growing interest in the mining industry in issues related to risk assessment and management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies have indicated that risk [...] Read more.
Recently, there has been a growing interest in the mining industry in issues related to risk assessment and management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies have indicated that risk in mining should be analyzed not only in the human factor aspect, but also in strategic (environmental impact) and operational ones. However, there is a lack of research on systematic literature reviews and surveys of studies that would focus on these identified risk aspects simultaneously. Therefore, the purpose of this article is to develop a literature review in the area of analysis, assessment and risk management in the mining sector, published in the last decade and based on the concept of a human engineering system. Following this, a systematic search was performed with the use of Primo multi-search tool following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The main inclusion criteria were: (a) not older than 10 years, (b) article written in English, (c) publication type (scientific article, book, book chapter), (d) published in chosen electronic collections (Springer, Taylor and Francis, Elsevier, Science Direct, JSTOR). This resulted in the selection of the 94 most relevant papers in the area. First, the general bibliometric analysis was conducted. Later, the selected papers in this review were categorized into four groups and the critical review was developed. One of the main advantages of this study is that the results are obtained from different scientific sources/databases thanks to using a multi-search tool. Moreover, the authors identified the main research gaps in the area of the implementation of risk management in the mining industry. Full article
(This article belongs to the Special Issue New Directions in Hazard and Disaster Science: Advances in Applied Sciences)
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