## 1 Introduction
Regarding the second perspective, the potential hazards posed by sunken ships were identified, and risk assessment tools were used to manage these risks. In the U.K., the Maritime and Coastguard Agency (MCA) categorizes sunken ships into three risk categories: \"High risk: a sunken ship poses a significant risk to humans and the environment and requires further work to reduce the risk\", \"Medium risk: a sunken ship poses a low risk to humans and the environment and requires ongoing monitoring\", and \"Low risk: the impact of a sunken ship is so minor that no further action is required\" [19]. The Scandinavian risk assessment model, developed by Denmark's National Environmental Research Institute and Sweden's Chalmers University of Technology, also assesses the risk in three categories: \"Unacceptable risk: unacceptable under any circumstances\", \"As Low As Reasonably Possible (ALARP) risk: acceptable if the risk level can be reduced from an economic and technical point of view\", and \"Acceptable risk: a risk level that is considered acceptable\" [19]. The Development of European Guidelines for Potentially Polluting Shipwrecks (DEEPP), developed by Italy, France, and Monaco, assesses the risk of sunken ships based on eleven risk levels. It considers factors such as the \"amount of pollutants\", \"distance from the coastline or sensitive waters\", and \"age of the ship\" [20; 21]. The National Maritime Research Institute (NMRI), in Tokyo, Japan, developed a hazard model to assess the risk of oil leakage from sunken ships and to make informed decisions on hazard reduction measures [19]. Please refer to Appendix A for a detailed summary of the previous research on collision risk and pollution risk. This study offers a unique contribution by proposing a comprehensive approach that simultaneously addresses both collision and pollution risks associated with navigational obstacles. Previous research has primarily focused on evaluating these risks separately, limiting the ability to conduct a holistic assessment of the overall risks. For instance, [PERSON] et al. [8] and [PERSON] et al. [9] analyzed navigational obstacles from the perspective of collision risk, focusing on the impacts of climate change and employing geographical and methodological analyses. Similarly, [PERSON] et al. [16] and [PERSON] et al. [17] investigated optical remote sensing methods for detecting navigational obstacles, while [PERSON] et al. [18] examined economic losses stemming from warship accidents caused by floating debris. From the perspective of pollution risk, tools and models such as the UK Maritime and Coastguard Agency (MCA)'s three-tier risk classification system, the Scandinavian risk assessment model, the DEEPP project in Europe, and the hazard model developed by Japan's National Maritime Research Institute (NMRI) primarily focused on managing environmental risks posed by sunken ships. These models evaluated factors such as pollutant quantities, proximity to environmentally sensitive areas, and the age of the ship to categorize and mitigate risks. However, none of these studies considered collision and pollution risks simultaneously, leading to fragmented assessments of the risks posed by navigational obstacles. To address this gap, this study develops a comprehensive model that evaluates both types of risks concurrently. By integrating these two perspectives, this study provides a more holistic framework for understanding and managing the overall risks posed by navigational obstacles. This approach enhances risk assessment and decision-making, bridging the gap in previous research and advancing the field. Therefore, this study proposes a fuzzy set theory-based navigational obstacle risk assessment system that simultaneously considers both collision and pollution risks to facilitate the rapid removal of navigational obstacles. Fuzzy set theory is particularly well-suited to this problem due to its ability to handle uncertainty and ambiguity, which are inherent in assessing risks associated with navigational obstacles.