Natural Hazard Assessments through Soft Computing methods and GIS-based modeling

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (10 February 2020)

Special Issue Editors

Special Issue Information

Dear Colleagues,

The overall goal of the special issue “Natural Hazard Assessments through Soft Computing methods and GIS-based modeling” is to provide a forum for advancing the successful implementation of Soft Computing methods and Geographic Information Systems, for the assessment of Natural Hazards. Natural Hazards, which include earthquakes, floods, landslides, volcanic eruptions and wildfires, appear as a result of the progressive or extreme evolution of climatic, tectonic and geomorphological processes but also the impact of human activities.

Soft Computing methods, which include methods that are based on the concept of fuzzy and neuro-fuzzy logic, decision tree models, artificial neural networks, deep learning and evolutionary algorithms, are utilized as promising tools to analyze the spatial and temporal occurrence of Natural Hazards. Soft Computing methods are characterized by their ability to produce knowledge and discover hidden and unknown patterns and trends from large databases, whereas Geographic Information Systems (GIS) appears as significant technology equipped with tools for data manipulation and advanced modeling.

This Special Issue aims to provide an outlet for peer-reviewed publications, that implement state-of-the-art methods and techniques incorporating Soft Computing methods and GIS to map, monitor, predict, and assess Natural Hazards. This special issue aims to cover, without being limited to, the following areas: (a) Evaluating of loss and damages after earthquakes, floods, landslides and wildfires, (b) monitoring, mapping and assessing landslides, floods and wildfires.

Dr. Paraskevas Tsangaratos
Dr. Ioanna Ilia
Mr. Haoyuan Hong
Guest Editors

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Keywords

  • Soft Computing
  • Machine learning
  • Geographic Information System
  • Landslide susceptibility mapping
  • Flood susceptibility mapping
  • Wildfire susceptibility mapping • Earthquakes

Published Papers (3 papers)

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Research

21 pages, 30712 KiB  
Article
Integrated Geomorphological and Geospatial Analysis for Mapping Fluvial Landforms in Murge Basse Karst of Apulia (Southern Italy)
by Gianvito Teofilo, Dario Gioia and Luigi Spalluto
Geosciences 2019, 9(10), 418; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences9100418 - 26 Sep 2019
Cited by 6 | Viewed by 2849
Abstract
An integrated geomorphological and geospatial study was performed in order to map fluvial landforms in a sector of Lama Lamasinata close to the town of Binetto in the Murge Basse karst (metropolitan area of Bari, Apulia, Southern Italy). This study describes a combined [...] Read more.
An integrated geomorphological and geospatial study was performed in order to map fluvial landforms in a sector of Lama Lamasinata close to the town of Binetto in the Murge Basse karst (metropolitan area of Bari, Apulia, Southern Italy). This study describes a combined approach, based on geomorphological fieldwork and topographical position index (TPI)-based landform classification, aimed at identifying the main landforms in an anthropically-modified environment, which suffered a progressive transformation of original morphologies. The resulting geomorphological map of fluvial features was then compared with the available cartography in order to highlight the main strength of the applied methodology in mapping fluvial landforms. Moreover, semi-automatic landform classification was performed for the entire catchment of the Lama Lamasinata in order to evaluate the usefulness of the approach for the fast and objective delimitation of widespread geomorphological elements of the Murge area such as flat-bottomed valleys with steep- or gently-dipping flanks and relict incised valleys. We demonstrated that such an approach can efficiently support land use planning in an area affected by hydrogeological hazards. Full article
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20 pages, 4658 KiB  
Article
Study on Early Warning Method for Water Inrush in Tunnel Based on Fine Risk Evaluation and Hierarchical Advance Forecast
by Sheng Wang, Shucai Li, Liping Li, Shaoshuai Shi, Zongqing Zhou, Shuai Cheng and Huijiang Hu
Geosciences 2019, 9(9), 392; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences9090392 - 07 Sep 2019
Cited by 8 | Viewed by 2351
Abstract
Water inrush is one of the most frequent and harmful geological disasters in tunnel construction. In order to effectively prevent and control the occurrence of water inrush, an early warning method based on fine risk evaluation and hierarchical advanced forecast is proposed. Water [...] Read more.
Water inrush is one of the most frequent and harmful geological disasters in tunnel construction. In order to effectively prevent and control the occurrence of water inrush, an early warning method based on fine risk evaluation and hierarchical advanced forecast is proposed. Water inrush is a complex dynamic coupling factors system, the relationship between influencing factors and water inrush is strongly nonlinear. Therefore, the efficacy coefficient model, which has the advantages of standardization, conciseness, and freedom from subjective factors, is improved nonlinearly. The fine risk evaluation theory and method based on the improved efficacy coefficient model consisted of two parts: one is static evaluation used in design stage, and the other is dynamic evaluation applied in the construction stage. The index weights are determined scientifically and reasonably by Analytical Hierarchy Process (AHP) and the entropy method. According to the fine risk evaluation results, combined with the advantages and disadvantages of various forecasting methods, a multistep hierarchical detection method of disaster resources for water inrush is proposed to identify the occurrence characteristics and failure level of disaster sources. The theory has been successfully applied to the #3 inclined well of Yuelongmen Tunnel in Cheng-Lan Railway. The evaluation results had good agreement with the actual excavation data, which indicates that the model is of high credibility and feasibility. The method could improve the prediction accuracy of water inrush and explore geometric characteristics and filling of disaster-causing structures. It is of great significance for avoiding water inrush and guiding the rapid and safe tunnel construction. Full article
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19 pages, 9903 KiB  
Article
An Agent-Based Evaluation of Varying Evacuation Scenarios in Merapi: Simultaneous and Staged
by Jumadi Jumadi, Steve J. Carver and Duncan J. Quincey
Geosciences 2019, 9(7), 317; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences9070317 - 18 Jul 2019
Cited by 7 | Viewed by 3318
Abstract
Mass evacuation should be conducted when a disaster threatens within a regional scale. It is reported that 400,000 people were evacuated during the last eruption of Merapi Volcano in 2010. Such a large-scale evacuation can lead to chaos or congestion, unless well managed. [...] Read more.
Mass evacuation should be conducted when a disaster threatens within a regional scale. It is reported that 400,000 people were evacuated during the last eruption of Merapi Volcano in 2010. Such a large-scale evacuation can lead to chaos or congestion, unless well managed. Staged evacuation has been investigated as a solution to reducing the degree of chaos during evacuation processes. However, there is a limited conception of how the stages should be ordered in terms of which group should move first and which group should follow. This paper proposes to develop evacuation stage ordering based on the geographical character of the people at risk and examine the ordering scenarios through an agent-based model of evacuation. We use several geographical features, such as proximity to the hazard, road network conditions (accessibility), size of the population, and demographics as the parameters for ranking the order of each population unit in GIS. From this concept, we produced several scenarios of ranking based on different weightings of the parameters. We applied the scenarios in an agent-based model of volcanic evacuation experiment to observe the results. Afterwards, the results were evaluated based on the ability to reduce the risk and spatio-temporal traffic density along road networks compared to the result of simultaneous evacuation to establish the relative effectiveness of the outcome. The result shows that the staged scenario has a better ability to reduce the potential traffic congestion during the peak time of the evacuation compared to the simultaneous strategy. However, the simultaneous strategy has better performance regarding the speed of reducing the risk. An evaluation of the relative performance of the four varying staged scenarios is also presented and discussed in this paper. Full article
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