A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future...

Area of Science:

• Environmental Science
• Forestry
• Natural Hazard Management

Background:

• Forest fire risk assessment is vital for environmental management and species protection.
• Evolving environmental changes necessitate updated research in forest fire risk assessment.
• Existing literature lacks a structured overview of methodologies and research trends.

Purpose of the Study:

• To develop a comprehensive taxonomic framework for classifying forest fire risk assessment literature.
• To identify current trends, research gaps, and underrepresented methodologies in the field.
• To guide future research directions for improved forest fire risk assessment.

Main Methods:

• A systematic review and classification of 170 articles on forest fire risk assessment.
• Development of a taxonomy with 8 primary categories and 23 subcategories.
• Analysis of categorized literature to identify trends and gaps.

Main Results:

• The developed taxonomy provides a structured overview of existing research.
• Identified underrepresented methodologies include optimization modeling and advanced machine learning.
• Research gaps exist in tailored regional models with global adaptability.

Conclusions:

• There is significant potential for novel modeling techniques, particularly integrating machine learning and multi-criteria decision analysis.
• Future research should focus on developing adaptable models balancing regional specificity and global applicability.
• Increased collaboration is needed to enhance the effectiveness of forest fire risk assessment.