The suitability mapping of an urban spatial structure for earthquake disaster response using a gradient rain...

Area of Science:

• Urban planning and disaster management
• Geographic Information Systems (GIS)
• Optimization algorithms

Background:

• Urban spatial structure significantly impacts earthquake response effectiveness.
• Vulnerable areas require assessment for efficient search and rescue operations.
• Existing frameworks lack optimized identification of critical zones for disaster reaction.

Purpose of the Study:

• To compute the suitability of municipal spatial structures for crisis reaction post-earthquake.
• To identify critical areas prone to emergency response disruption.
• To enhance a GIS-based framework for earthquake disaster suitability analysis.

Main Methods:

• Developed a hybrid framework integrating Fuzzy Analytical Hierarchical Process (FAHP) and Gradient Rain Optimization Algorithm (GROA).
• Modified the Rain Optimization Algorithm (ROA) to GROA using gradient descent to prevent local optima.
• Applied the framework to Tehran, Iran, for suitability mapping.

Main Results:

• Identified critical emergency response areas in Tehran's west and southwest.
• Determined road junction degree and width as most significant factors for urban suitability.
• Demonstrated GROA's efficiency over ROA, showing less sensitivity to local optima and better economy.

Conclusions:

• The GROA-enhanced GIS framework effectively identifies crucial areas for earthquake emergency response.
• Urban planners and rescue experts showed high satisfaction with the suitability and critical area maps.
• The study provides a valuable tool for prioritizing troop deployment and mitigating casualties.