Document Type : Original Article

Authors

• Alireza Gharagozlou ¹
• Atena Soheilazizi ²
• Mohamad mahdi Kalantari ²

¹ Geotechnical Engineering department, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

² Bachelor Student in Geography, Specializing in Remote Sensing and GIS, Shahid Beheshti University, Tehran

Abstract

The increasing frequency of environmental hazards such as floods, landslides, earthquakes, and wildfires has highlighted the need for innovative risk management solutions, particularly in countries with diverse climates like Iran. This study aims to explore the potential for integrating UAV-based photogrammetry technology with Spatial Decision Support Systems (SDSS) to improve environmental hazard management processes. The methodology is both review-based and analytical, involving a systematic review of reputable domestic and international scientific sources from 2015 to 2023, and a comparative analysis of the application of these technologies in Iran and other countries. Findings show that integrating precise UAV data with the analytical capacities of SDSS can play a significant role in the stages of hazard identification, prediction, and impact mitigation. This combination, leveraging machine learning algorithms, significantly enhances real-time analysis capabilities, crisis scenario modeling, and prioritization of high-risk areas. However, challenges such as high costs, legal restrictions on UAV flights, and a shortage of skilled personnel remain significant barriers to practical implementation in Iran. Ultimately, the study emphasizes the necessity of developing localized frameworks, specialized training, and supportive policies to effectively utilize these technologies.

Keywords

• UAV
• Spatial Decision Support Systems (SDSS)
• Machine Learning
• Risk Management