scholarly journals A STUDY ON THE EARTHQUAKE RISK ASSESSMENT OF HILLSIDE CITIES BASED ON A GIS DATABASE : A case study for Nagasaki City

1996 ◽  
Vol 61 (490) ◽  
pp. 237-246
Author(s):  
Toshihiko MIZUTA ◽  
Sumio NAGAHASHI
Keyword(s):  
Risk Assessment ◽  
Earthquake Risk ◽  
Gis Database ◽  
Earthquake Risk Assessment

scholarly journals Geospatial Multicriteria Analysis for Earthquake Risk Assessment: Case Study of Fujairah City in the UAE

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Diena Al-Dogom ◽  
Rami Al-Ruzouq ◽  
Bahareh Kalantar ◽  
Karen Schuckman ◽  
Saeed Al-Mansoori ◽  
...  
Keyword(s):  
Risk Assessment ◽  
United Arab Emirates ◽  
Multicriteria Analysis ◽  
Earthquake Risk ◽  
Support Vector ◽  
Clear Understanding ◽  
The Social ◽  
Earthquake Risk Assessment ◽  
Very High

A clear understanding of the spatial distribution of earthquake events facilitates the prediction of seismicity and vulnerability among researchers in the social, physical, environmental, and demographic aspects. Generally, there are few studies on seismic risk assessment in United Arab Emirates (UAE) within the geographic information system (GIS) platform. Former researches and recent news events have demonstrated that the eastern part of the country experiences jolts of 3-5 magnitude, specifically near Fujairah city and surrounding towns. This study builds on previous research on the seismic hazard that extracted the eastern part of the UAE as the most hazard-prone zone. Therefore, this study develops an integrated analytical hierarchical process (AHP) and machine learning (ML) for risk mapping considering eight geospatial parameters—distance from shoreline, schools, hospitals, roads, residences, streams, confined area, and confined area slope. Experts’ opinions and literature reviews were the basis of the AHP ranking and weighting system. To validate the AHP system, support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers were applied to the datasets. The datasets were split into 60 : 40 ratio for training and testing. Results show that SVM has the highest accuracy of 79.6% compared to DT and RF with a “predicted high” precision of 87.5% attained from the model. Risk maps from both AHP and ML approaches were developed and compared. Risk analysis was categorised into 5 classes “very high,” “high,” “moderate,” “low,” and “very low.” Both approaches modelled relatable spatial patterns as risk-prone zones. AHP approach concluded 3.6% as “very high” risk zone, whereas only 0.3% of total area was identified from ML. The total area for the “very high” (20 km2) and “high” (114 km2) risk was estimated from ML approach.

Earthquake Risk Assessment. Case Study: Cyprus

2005 ◽  
Vol 90 (3) ◽  
pp. 67-74 ◽  
Author(s):  
Nicholas Kyriakides ◽  
Kypros Pilakoutas ◽  
Stella Kythreoti
Keyword(s):  
Risk Assessment ◽  
Earthquake Risk ◽  
Earthquake Risk Assessment

Hysteresis effect on earthquake risk assessment of moment resisting frame structures

2021 ◽  
Vol 242 ◽  
pp. 112532
Author(s):  
Zhenhua Huang ◽  
Liping Cai ◽  
Yashica Pandey ◽  
Yong Tao ◽  
William Telone
Keyword(s):  
Risk Assessment ◽  
Hysteresis Effect ◽  
Frame Structures ◽  
Earthquake Risk ◽  
Moment Resisting Frame ◽  
Moment Resisting ◽  
Earthquake Risk Assessment

scholarly journals Communicating earthquake risk: mapped parameters and cartographic representation

2011 ◽  
Vol 11 (2) ◽  
pp. 359-366 ◽  
Author(s):  
J. M. Gaspar-Escribano ◽  
T. Iturrioz
Keyword(s):  
Risk Assessment ◽  
Seismic Risk ◽  
Risk Information ◽  
Decision Makers ◽  
Earthquake Risk ◽  
Graphical Representations ◽  
Related Risk ◽  
Different Types ◽  
Earthquake Effects ◽  
Earthquake Risk Assessment

Abstract. Earthquake risk assessment is probably the most effective tool for reducing adverse earthquake effects and for developing pre- and post-event planning actions. The related risk information (data and results) is of interest for persons with different backgrounds and interests, including scientists, emergency planners, decision makers and other stakeholders. Hence, it is important to ensure that this information is properly transferred to all persons involved in seismic risk, considering the nature of the information and the particular circumstances of the source and of the receiver of the information. Some experience-based recommendations about the parameters and the graphical representations that can be used to portray earthquake risk information to different types of audiences are presented in this work.

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