Machine learning-based analysis of sea fog’s spatial and temporal impact on near-miss ship collisions using remote sensing and AIS data
Sea fog is a severe marine environmental disaster that significantly threatens the safety of maritime transportation. It is a major environmental factor contributing to ship collisions. The Himawari-8 satellite’s remote sensing capabilities effectively bridge the spatial and temporal gaps in data fr...
Saved in:
Main Authors: | Dan Liu, Ling Ke, Zhe Zeng, Shuo Zhang, Shanwei Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
|
Series: | Frontiers in Marine Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2024.1536363/full |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Collision Avoidance for Maritime Autonomous Surface Ships Based on Model Predictive Control Using Intention Data and Quaternion Ship Domain
by: Hanxuan Zhang, et al.
Published: (2025-01-01) -
A Dynamic Discretization Algorithm for Learning BN Model: Predicting Causation Probability of Ship Collision in the Sunda Strait, Indonesia
by: Iis Dewi Ratih, et al.
Published: (2024-12-01) -
Retrospective evaluation of patients admitted to the intensive care unit due to obstetric reasons in terms of maternal near-miss, a five-year case-control study
by: Özgür Erdem, et al.
Published: (2025-01-01) -
Analysis of the Characteristics of Ship Collision-Avoidance Behavior Based on Apriori and Complex Network
by: Shipeng Wang, et al.
Published: (2024-12-01) -
Neonatal near miss and associated factors among neonates delivered at East Gojjam zone public health hospitals, Northwest Ethiopia
by: Melesse Tesfa, et al.
Published: (2025-01-01)