Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Synthesis and herbicidal activity of optically active α-(substituted phenoxyacetoxy) (substituted phenyl) methylphosphonates.

Pesticide biochemistry and physiology·2017
Same author

S149R, a novel mutation in the <i>ABCD1</i> gene causing X-linked adrenoleukodystrophy.

Oncotarget·2017
Same author

Transgenic cotton co-expressing chimeric Vip3AcAa and Cry1Ac confers effective protection against Cry1Ac-resistant cotton bollworm.

Transgenic research·2017
Same author

Effective adsorption of nitroaromatics at the low concentration by a newly synthesized hypercrosslinked resin.

Water science and technology : a journal of the International Association on Water Pollution Research·2017
Same author

Comparative Genome Analysis Reveals Adaptation to the Ectophytic Lifestyle of Sooty Blotch and Flyspeck Fungi.

Genome biology and evolution·2017
Same author

Highly Efficient Separation of Trivalent Minor Actinides by a Layered Metal Sulfide (KInSn<sub>2</sub>S<sub>6</sub>) from Acidic Radioactive Waste.

Journal of the American Chemical Society·2017

Related Experiment Video

Updated: Sep 8, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.9K

Sunken oil detection and classification using MBES backscatter data.

Jianwei Li1, Wei An2, Chao Xu3

  • 1Key Laboratory of Marine Environment and Ecology, Ministry of Education of China, Ocean University of China, Qingdao 266100, China; CNOOC Energy Technology & Services Limited, Safety & Environmental Protection Branch, Tianjin 300450, China; School of Hydraulic Engineering, Ludong University, Yantai, China.

Marine Pollution Bulletin
|June 12, 2022
PubMed
Summary
This summary is machine-generated.

Detecting sunken oil in the Bohai Sea is challenging. Multibeam echosounder (MBES) acoustic images and support vector machine (SVM) algorithms achieved 88.5% accuracy in classifying sunken oil.

Keywords:
Backscatter strengthDetection and classificationMultibeam echosounderSunken oil

More Related Videos

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring
13:35

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring

Published on: June 13, 2025

638
A Field Primer for Monitoring Benthic Ecosystems Using Structure-From-Motion Photogrammetry
06:36

A Field Primer for Monitoring Benthic Ecosystems Using Structure-From-Motion Photogrammetry

Published on: April 15, 2021

3.8K

Related Experiment Videos

Last Updated: Sep 8, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.9K
Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring
13:35

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring

Published on: June 13, 2025

638
A Field Primer for Monitoring Benthic Ecosystems Using Structure-From-Motion Photogrammetry
06:36

A Field Primer for Monitoring Benthic Ecosystems Using Structure-From-Motion Photogrammetry

Published on: April 15, 2021

3.8K

Area of Science:

  • Marine geology
  • Acoustic sensing
  • Environmental monitoring

Background:

  • Sunken oil incidents in the Bohai Sea pose environmental risks.
  • Effective detection and classification of sunken oil remain significant challenges.

Purpose of the Study:

  • To investigate the efficacy of multibeam echosounder (MBES) backscatter images for sunken oil detection.
  • To develop a classification framework for distinguishing sunken oil from other targets.

Main Methods:

  • Conducted sonar detection experiments using an MBES in a large seawater tank.
  • Processed MBES data to generate backscatter strength images.
  • Extracted eight-dimensional features and employed a support vector machine (SVM) algorithm for classification.

Main Results:

  • MBES backscatter images effectively reflect target characteristics.
  • The SVM classification framework achieved an overall accuracy of 88.5% in classifying sunken oil.
  • Demonstrated MBES backscatter images as a viable method for sunken oil detection.

Conclusions:

  • MBES backscatter imaging offers a promising approach for sunken oil detection and classification.
  • The SVM algorithm provides a robust method for analyzing acoustic data.
  • This study lays the groundwork for future research in underwater oil spill detection.