Evaluation Model of Regional Comprehensive Disaster Reduction Capacity under Complex Environment.

Area of Science:

• Earth and Environmental Sciences
• Remote Sensing Technology
• Disaster Management

Background:

• Evaluating regional disaster reduction capacity in complex environments is challenging.
• Existing methods may lack the precision needed for intricate settings.
• Remote sensing offers a powerful tool for large-scale environmental monitoring.

Purpose of the Study:

• To propose an evaluation model for regional comprehensive disaster reduction capacity in complex environments.
• To leverage remote sensing monitoring and image feature analysis for this evaluation.
• To enhance the accuracy and reliability of disaster reduction capacity assessments.

Main Methods:

• Utilizing remote sensing to extract geographical images of disaster spots in complex environments.
• Applying image texture feature extraction and tone mapping for rapid filtering and analysis.
• Developing a comparison model using parameter analysis and gradient operators for reliability evaluation.

Main Results:

• The proposed method demonstrates high accuracy in evaluating regional disaster reduction capability.
• Accurate geographical location marking of disaster spots in complex environments was achieved.
• The model showed good fusion performance and reliability for evaluation parameters.

Conclusions:

• The developed remote sensing-based model effectively evaluates regional disaster reduction capacity in complex environments.
• The method provides reliable and accurate data for disaster management and preparedness.
• This approach significantly improves the assessment of resilience in challenging geographical areas.