حمید کریمی کیوی

INTRODUCTION: The unpredictable magnitude and scope of disasters make it particularly challenging to respond effectively and provide timely assistance to affected populations. In many situations, geographical location, regional topography, and adverse weather conditions, especially in the early stages, hinder rapid access to disaster-affected areas. In recent years, Unmanned Aerial Vehicles (UAVs), commonly known as drones, have emerged as an innovative technology that offers rapid data collection, real-time surveillance, and access to remote areas, thereby enhancing situational awareness and decision-making during disasters. METHODS: This study employed a narrative review methodology to synthesize existing research on the application of UAVs across the pre-disaster, during and post-disaster phases of disaster management. A comprehensive search of relevant databases yielded a total of 1,986 articles. After removing duplicate records and screening titles, abstracts, and full texts based on predefined inclusion criteria, nine articles were selected for final analysis and review. FINDINGS: The findings were categorized into four main phases of disaster management: prevention and mitigation, preparedness, response, and recovery. The reviewed studies demonstrated that UAVs play a significant role in improving situational awareness, damage assessment, Search and Rescue (SAR) operations, infrastructure monitoring, and recovery planning. Despite certain technical, regulatory, and operational challenges, the overall evidence highlights the substantial potential of UAVs to enhance disaster management effectiveness across all phases. CONCLUSION: According to the results of this review, systematic planning for the integration of UAV technology across various stages of disaster management is essential. Although challenges remain, these can be addressed through the adoption of advanced technologies such as deep learning algorithms, as well as improved equipment, software, and analytical tools for data collection and processing. Such advancements can significantly enhance the cost-effectiveness and operational value of UAVs, supporting more efficient disaster response, mitigation, and recovery strategies.

INTRODUCTION: One of the environmental issues faced by the majority of large human settlements in the world is natural disasters and their effects. Thus, the purpose of this paper is to present a model using Interpretive Structural Modeling (ISM) for explaining the relationship between the factors affecting disaster management in order to improve its effectiveness. METHODS: In this study, quantitative method were used. For identifying the factors influencing disaster management, thematic analysis and second-order confirmatory factor analysis were used and confirmed through SmartPLS. Then the main model of the study was developed based on ISM using the views of experts in the field of disaster management. FINDINGS: The findings showed that risk evaluation, risk management, and management actions were the fundamental factors in the disaster management model which consisted of 19 sub-factors. Convergent validity of the study was found to be higher than 0.5 based on Average Variance Extracted (AVE) and reliability was higher than 0.7 based on Cronbach’s alpha, also Composite Reliability (CR) was calculated to be larger than 0.6, which showed that the suggested factors completely measure the intended concept in the study. CONCLUSION: According to the results, the proposed model shows the relation between factors affecting reduction of damages caused by disasters using the ISM. It can be used in different stages of disaster management because it explains the relation between 12 levels of different factors and enables managers and planners to clearly understand what activities need to be taken for more effective disaster management.