Study of the seismic activity of the Almalyk-Angren industrial zone based on lineament analysis

SİCHUGOVA, Lola; FAZİLOVA, Dilbarkhon

doi:10.26833/ijeg.1192118

Cited by 4 publications

References 22 publications

(29 reference statements)

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Beyond the richter scale: a fuzzy inference system approach for measuring objective earthquake risk

Mohammadi,

Balouei,

Amini

et al. 2024

Nat Hazards

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Earthquakes pose significant natural hazards and impact populations worldwide. Iran is among the most susceptible countries to seismic activity, making comprehensive earthquake risk assessment crucial. This study employs geospatial methods, including integrating satellite, ground-based, and auxiliary data to model earthquake risk across this country. A Fuzzy Inference System (FIS) is used to generate earthquake hazard probability and vulnerability layers, considering factors such as slope, elevation, fault density, building density, proximity to main roads, proximity to buildings, population density, and earthquake epicenter, magnitude, proximity to the epicenter, depth density, peak ground acceleration (PGA). The results highlight high-risk areas in the Alborz and Zagros Mountain ranges and coastal regions. Moreover, the findings indicate that 39.7% (approximately 31.7 million people) of Iran’s population resides in high-risk zones, with 9.6% (approximately 7.7 million) located in coastal areas vulnerable to earthquakes. These findings offer valuable insights for crisis management and urban planning initiatives.

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Beyond the richter scale: a fuzzy inference system approach for measuring objective earthquake risk

Mohammadi,

Balouei,

Amini

et al. 2024

Nat Hazards

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Investigation of lineament extraction: Analysis and comparison of digital elevation models in the Ait Semgane region, Morocco

Ali EL-Omairi,

El Garouani,

Shebl

2024

Remote Sensing Applications: Society and Environment

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An Innovative Fusion of New Smile Random Forest and Fuzzy Analysis for Comprehensive Seismic hazard Assessment: A Case Study in Mersin, Türkiye

Yakar,

Kamran,

Alptekin

et al. 2024

Preprint

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This study addresses the critical issue of earthquake vulnerability in Mersin, Türkiye, given its susceptibility to seismic threats due to factors such as high population density, substandard constructions, narrow roads, and urban congestion. The research employs a comprehensive approach, utilizing a multi-criteria evaluation model and a novel hybrid random forest model to estimate the city's vulnerability proportionally. Spatial data encompassing physical, population, building quality, accessibility, relief, and hazard facilities were incorporated into the assessment. Weights for these components were determined through the Analytic Network Process (ANP) model, and a hybrid approach using Linear, Small, and Large functions calculated distances between options with fuzzy-fication. Resampling 10m x 10m maps addressed variations in spatial resolutions, while an 80% training set and 20% test set mitigated overfitting concerns. Expert opinions were pivotal in establishing criteria and sub-criteria for determining safe areas for temporary accommodation, rescue centers, and a seismic vulnerability map. The Smile Random Forest hybrid model was instrumental in generating these outcomes. Notably, the vulnerability map indicated that 24% of Mersin's areas fall within the high and very high vulnerability range. Key contributors to vulnerability included Geology factors (26.4), Land use (16.1), Epicenters (13.1), and slope and DEM (6.4). These findings underscore the imperative for strategic planning and interventions to minimize earthquake-induced damage in Mersin.

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Study of the seismic activity of the Almalyk-Angren industrial zone based on lineament analysis

Cited by 4 publications

References 22 publications

Beyond the richter scale: a fuzzy inference system approach for measuring objective earthquake risk

Beyond the richter scale: a fuzzy inference system approach for measuring objective earthquake risk

Investigation of lineament extraction: Analysis and comparison of digital elevation models in the Ait Semgane region, Morocco

An Innovative Fusion of New Smile Random Forest and Fuzzy Analysis for Comprehensive Seismic hazard Assessment: A Case Study in Mersin, Türkiye

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