Advances in Remote Sensing Technology, Machine Learning and Deep Learning for Marine Oil Spill Detection, Prediction and Vulnerability Assessment
importance 6/10
partially solved
Oil Spill Detection and Mitigation environmental monitoring stage: research
Problem
Distinguishing oil spills from lookalikes and accurately modeling spill trajectories remain difficult for emergency response.
Why it matters
Rapid oil spill detection and prediction are critical for disaster reduction and emergency response.
What the AI did
Review of remote sensing, machine learning and deep learning approaches for oil spill detection, discrimination, trajectory prediction and vulnerability assessment.
Results
not stated in source
Impact
Review extends prior work by covering detection, discrimination and trajectory prediction for vulnerability assessment.
Record
| Venue | Remote Sensing |
|---|---|
| Published | 2020 |
| Work type | article |
| Authors | Shamsudeen Temitope Yekeen, Abdul‐Lateef Balogun |
| Citations | 129 (OpenAlex, at import time) |
| References | 204 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/rs12203416 |
| Open access | gold |
| Keywords | oil spill detection, remote sensing, deep learning, trajectory prediction, vulnerability assessment |
Importance rating
6
significant — thousands to millions affected
Oil spill detection and trajectory prediction are critical for disaster reduction and emergency response, a significant environmental problem; no scale stated.
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