Advances of Underwater Remote Sensing of Methane: Spatiotemporal Distribution
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".
Deadline for manuscript submissions: 15 August 2024 | Viewed by 449
Special Issue Editors
Interests: multi-sensor navigation; under water remote sensing; underwater LiDAR
Special Issues, Collections and Topics in MDPI journals
Interests: positioning and navigation technologies; multi-sensor fusion; robotics; LiDAR scanning
Special Issues, Collections and Topics in MDPI journals
Interests: multi-sensor fusion; seamless positioning and navigation; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: positioning and navigation technologies; multi-sensor fusion; LiDAR scanning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The current research status of underwater methane pipeline leak detection is a complex issue involving multiple fields. Current research primarily focuses on developing and improving various technologies and methods to timely and accurately detect leaks in underwater methane pipelines, in order to minimize the environmental and human health impacts of leaks. Some commonly used technologies include acoustic detection, remote sensing techniques, chemical sensors, and machine learning algorithms.
Acoustic detection is a commonly used method that involves monitoring changes in sound waves around the pipeline using underwater acoustic sensors to identify possible leaks. Remote sensing techniques utilize equipment such as satellites, underwater drones, or underwater robots to detect pipeline leaks by monitoring underwater surface temperature, gas concentration, or underwater optical features. Chemical sensors can directly measure gas concentrations in the underwater environment to identify possible leak points. Additionally, machine learning algorithms are widely used to process and analyze large amounts of sensor data to improve the accuracy and efficiency of leak detection.
Despite some progress being made, underwater methane pipeline leak detection still faces challenges such as the complex underwater environment, interference from underwater noise, and the identification of leak signals. Therefore, future research needs to further enhance the sensitivity and accuracy of detection technologies to address the increasing demands of underwater methane development activities and environmental protection.
This Special Issue aims to and methods of underwater methane pipeline leakage detection, sensing and positioning, including but not limited to the following topics:
- Underwater methane pipeline leak remote sensing and locating technology;
- MEMS sensors of underwater methane pipeline leak detection and remote sensing;
- Algorithms of remote sensing, detecting and locating underwater methane pipeline leaks;
- AI-enabled methods of the underwater methane leak sensing remotely;
- New sensors, i.e., MEMS sensors, sensors arrays, to detect the underwater methane pipeline leak;
- Multi-sensor integration of the underwater methane pipeline leak detection and position;
- Real-time monitoring and mapping of the underwater methane pipeline leak.
- Other remote sensing technologies or sensors for underwater methane pipeline leak remote sensing.
Prof. Dr. Changhui Jiang
Dr. Zuoya Liu
Dr. Yue Yu
Dr. Yuwei Chen
Guest Editors
Manuscript Submission Information
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Keywords
- underwater remote sensing
- methane leak detection
- artificial intelligence
- methane leak detection sensors
- methane leak remote sensing
