Volume 1, Issue 2 — Year 2024 — Article e100016

Anis Akbarzadeh¹; Shahbaz Radfar²; Shahram Shafiei Bafti³

1. Department of Geology, Shahid Bahonar University of Kerman, Kerman 7616913439, Iran
2. Department of Geology, Shahid Bahonar University of Kerman, Kerman 7616913439, Iran
3. Department of Geology, Shahid Bahonar University of Kerman, Kerman 7616913439, Iran

This study evaluates high-risk dynamic zones in northeastern Kerman, focusing on the effects of kinematic brittle deformation and their correlation with recorded earthquakes. The region is tectonically active, influenced by major fault systems that contribute to seismic hazards and surface deformation. Identifying these hazardous zones is crucial for risk assessment, infrastructure development, and disaster management. The research integrates geological surveys, remote sensing techniques, and seismic data analysis to assess fault dynamics, lithological characteristics, and historical earthquake occurrences. High-resolution Digital Elevation Models (DEMs) and satellite imagery are employed to map structural discontinuities and deformation patterns. Additionally, seismic records and fault activity data are analyzed to determine the relationship between brittle deformation zones and earthquake distribution. Findings indicate that areas with intense brittle deformation align with active fault zones, making them highly susceptible to seismic hazards. The study reveals that northeastern Kerman experiences frequent moderate-to-strong earthquakes, with significant deformation occurring along major thrust and strike-slip faults. These deformations increase the likelihood of future seismic activity and ground instability. The results provide valuable insights for urban planners, engineers, and policymakers to enhance seismic hazard mitigation strategies. By identifying high-risk zones, the study contributes to informed decision-making for infrastructure planning, land-use management, and disaster preparedness. Future research should focus on integrating machine learning models with geophysical data to improve earthquake prediction accuracy and hazard assessments in tectonically active regions.

Seismic hazard, Brittle deformation, Earthquake susceptibility, Fault dynamics, Northeastern Kerman