Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Multi-criteria decision making (MCDM) model for seismic vulnerability assessment (SVA) of urban residential buildings

© 2018 by the authors. Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world

A GIS-based multi-criteria evaluation framework for uncertainty reduction in earthquake disaster management using granular computing

One of the most important steps in earthquake disaster management is the prediction of probable damages which is called earthquake vulnerability assessment. Earthquake vulnerability assessment is a multicriteria problem and a number of multi-criteria decision making models have been proposed for the problem. Two main sources of uncertainty including uncertainty associated with experts‘ point of views and the one associated with attribute values exist in the earthquake vulnerability assessment problem. If the uncertainty in these two sources is not handled properly the resulted seismic vulnerability map will be unreliable. The main objective of this research is to propose a reliable model for earthquake vulnerability assessment which is able to manage the uncertainty associated with the experts‘ opinions. Granular Computing (GrC) is able to extract a set of if-then rules with minimum incompatibility from an information table. An integration of Dempster-Shafer Theory (DST) and GrC is applied in the current research to minimize the entropy in experts‘ opinions. The accuracy of the model based on the integration of the DST and GrC is 83%, while the accuracy of the single-expert model is 62% which indicates the importance of uncertainty management in seismic vulnerability assessment problem. Due to limited accessibility to current data, only six criteria are used in this model. However, the model is able to take into account both qualitative and quantitative criteria

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

A review of multi-criteria decision-making methods for building assessment, selection, and retrofit

Multiple criteria decision-making (MCDM) has experienced significant growth in recent years, owing to its capacity to integrate even contradictory criteria. This study conducted a comprehensive literature review of MCDM for assessing, selecting, and retrofitting buildings. The bibliometric search used a search algorithm in specialized databases. A filtering and expansion process was done by reviewing references, and 91 relevant articles were selected. The analysis revealed that in a group of studies, socioeconomic criteria were used to assess the vulnerability of buildings. On the other hand, some research integrated the three dimensions of sustainability (economic, social, and environmental) along with safety considerations when identifying optimal retrofit alternatives. Classic MCDMs are prevalent in research within this field. Among the most used methods, the Analytic Hierarchy Process (AHP) was employed for criteria weighting, Simple Additive Weighting (SAW) for constructing vulnerability indices, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for building retrofitting. This literature review contributes to the path toward a holistic renovation of the existing building stock, providing recommendations for future research to improve decision-making solutions for integrating the safety and sustainability of existing buildings

Zoning the Vulnerability of Nahavand Settlements to Earthquakes

Recent studies on the catastrophic consequences and widespread human and financial losses caused by natural disasters, especially earthquakes, show that no effective measures have been taken in this regard. One of the earthquake-prone areas of Hamadan province is Nahavand city, which is also one of the widest plains in the province. In this regard, the present study aims to zone the vulnerability of settlements to earthquakes using FAHP and GIS methods. For this purpose, 14 criteria which are soil texture, magnitude, centers of previous earthquakes, hazardous facilities, main and secondary roads of the region, rivers, geological layers, landslide position, slope, soil erosion, land use, regional faults, digital elevation model and Population points were used. In this regard, a zoning map of the settlement's vulnerability to earthquakes has been prepared for environmental analysis and assessments. According to studies conducted by other researchers around the world, in this study, to overlay the weight of criteria in fuzzy space, the gamma function with initial values of 0.5, 0.7, and 0.9 was used; after validating the results and reviewing their values, a gamma of 0.9 was selected and used in the present study. Results of Nahavand in 5 classes, with very low vulnerability potential in the area of 25065 hectares, relatively low potential in the area of 48173 hectares, medium potential in the area of 39000 hectares, relatively high potential in the area of 25571 hectares, and very high potential in the area of 13980 hectares he does. The results show that 28 villages are in the area with high vulnerability potential and 3 cities and 26 villages are in the area with relatively high vulnerability potential

Multi-criteria decision making in civil engineering. Part II – applications

The first part of the paper shortly presented developments of multi-criteria decision making (MCDM) methods and general data about their use in civil engineering, i.e. distribution by years, countries, authors and journals (Zavadskas et al. 2015). The current part of the paper focuses on MCDM application areas and domains. Web of Science Category “Engineering Civil” in Thomson Reuters Web of Science Core Collection academic data base is searched for a topic of MCDM. Only articles and review document types are selected for a detailed survey. They are grouped by Research Areas as presented in Web of Science data base. The most numerous research areas as Construction Building Technology, Transportation, Water Resources and Engineering (other topics) are analysed in detail. Research domains and solved problems are described as well as applied MCDM methods are highlighted. A total of 114 articles are reviewed, showing a wide possibilities of applying MCDM methods for civil engineering problems

Reviewing seismic vulnerability dimensions: Current trends and methodological challenges

Traditionally, seismic vulnerability has been assessed considering, for the most part, infrastructure as the main evaluation component, leaving aside other dimensions of study. This result does not adequately evaluate all the anthropogenic characteristics that make a certain system more susceptible to experiencing economic, patrimonial, and human losses in the face of natural phenomena. In this context, Peru is exposed to many different phenomena of the earth’s internal and external geodynamics (i.e., earthquakes, tsunamis, volcanism, mass movements, heavy rains, drought, etc.), earthquakes being the ones that have caused the most damage and repercussions. It is for the latter, considering that seismic hazards are determined by the geographical conditions of the study area, that the main objective of this review is to study and highlight different perspectives of vulnerability analysis (i.e., social, cultural, economic, etc.) when seismic events happen. This review shows the main assessment parameters used to describe each dimension of analysis and in addition, a review of the main existing methodological frameworks is carried out, aimed at showing a comprehensive perspective of the context analyzed in order to improve the conditions and livelihoods of the population exposed to these hazards.Campus Lima Centr

Toward an integrated disaster management approach: How artificial intelligence can boost disaster management

Technical and methodological enhancement of hazards and disaster research is identified as a critical question in disaster management. Artificial intelligence (AI) applications, such as tracking and mapping, geospatial analysis, remote sensing techniques, robotics, drone technology, machine learning, telecom and network services, accident and hot spot analysis, smart city urban planning, transportation planning, and environmental impact analysis, are the technological components of societal change, having significant implications for research on the societal response to hazards and disasters. Social science researchers have used various technologies and methods to examine hazards and disasters through disciplinary, multidisciplinary, and interdisciplinary lenses. They have employed both quantitative and qualitative data collection and data analysis strategies. This study provides an overview of the current applications of AI in disaster management during its four phases and how AI is vital to all disaster management phases, leading to a faster, more concise, equipped response. Integrating a geographic information system (GIS) and remote sensing (RS) into disaster management enables higher planning, analysis, situational awareness, and recovery operations. GIS and RS are commonly recognized as key support tools for disaster management. Visualization capabilities, satellite images, and artificial intelligence analysis can assist governments in making quick decisions after natural disasters

A systematic review of application of multi-criteria decision analysis for aging-dam management

[EN] Decisions for aging-dam management requires a transparent process to prevent the dam failure, thus to avoid severe consequences in socio-economic and environmental terms. Multiple criteria analysis arose to model complex problems like this. This paper reviews specific problems, applications and Multi-Criteria Decision Making techniques for dam management. Multi-Attribute Decision Making techniques had a major presence under the single approach, specially the Analytic Hierarchy Process, and its combination with Technique for Order of Preference by Similarity to Ideal Solution was prominent under the hybrid approach; while a high variety of complementary techniques was identified. A growing hybridization and fuzzification are the two most relevant trends observed. The integration of stakeholders within the decision making process and the inclusion of trade-offs and interactions between components within the evaluation model must receive a deeper exploration. Despite the progressive consolidation of Multi-Criteria Decision Making in dam management, further research is required to differentiate between rational and intuitive decision processes. Additionally, the need to address benefits, opportunities, costs and risks related to repair, upgrading or removal measures in aging dams suggests the Analytic Network Process, not yet explored under this approach, as an interesting path worth investigating.This research was funded by the Spanish Ministry of Economy and Competitiveness along with FEDER funding (Projects BIA201456574-R and ECO2015-66673-R).Zamarrón-Mieza, I.; Yepes, V.; Moreno-Jiménez, JM. (2017). A systematic review of application of multi-criteria decision analysis for aging-dam management. Journal of Cleaner Production. 147:217-230. https://doi.org/10.1016/j.jclepro.2017.01.092S21723014