Automated Detection, Classification, and Tracking of Internal Wave Signatures Using X-Band Radar in the Inner Shelf Article Swipe
Sean Celona
,
Sophia Merrifield
,
Tony de Paolo
,
Nate Kaslan
,
Tom Cook
,
Eric Terrill
,
John A. Colosi
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1175/jtech-d-20-0129.1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1175/jtech-d-20-0129.1
A method based on machine learning and image processing techniques has been developed to track the surface expression of internal waves in near–real time. X-band radar scans are first preprocessed and averaged to suppress surface wave clutter and enhance the signal-to-noise ratio of persistent backscatter features driven by gradients in surface currents. A machine learning algorithm utilizing a support vector machine (SVM) model is then used to classify whether or not the image contains an internal solitary wave (ISW) or internal tide bore (bore). The use of machine learning is found to allow rapid assessment of the large dataset, and provides insight on characterizing optimal environmental conditions to allow for radar illumination and detection of ISWs and bores. Radon transforms and local maxima detections are used to locate these features within images that are determined to contain an ISW or bore. The resulting time series of locations is used to create a map of propagation speed and direction that captures the spatiotemporal variability of the ISW or bore in the coastal environment. This technique is applied to 2 months of data collected near Point Sal, California, and captures ISW and bore propagation speed and direction information that currently cannot be measured with instruments such as moorings and synthetic aperture radar (SAR).
Related Topics
Concepts
Geology
Radar
Clutter
Artificial intelligence
Synthetic aperture radar
Tracking (education)
Atmospheric duct
Remote sensing
Internal wave
Computer science
Support vector machine
Radar imaging
X band
Point (geometry)
Computer vision
Physics
Meteorology
Telecommunications
Psychology
Pedagogy
Geometry
Oceanography
Atmosphere (unit)
Mathematics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1175/jtech-d-20-0129.1
- https://journals.ametsoc.org/downloadpdf/journals/atot/38/4/JTECH-D-20-0129.1.pdf
- OA Status
- bronze
- Cited By
- 23
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3121759919
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3121759919Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1175/jtech-d-20-0129.1Digital Object Identifier
- Title
-
Automated Detection, Classification, and Tracking of Internal Wave Signatures Using X-Band Radar in the Inner ShelfWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-25Full publication date if available
- Authors
-
Sean Celona, Sophia Merrifield, Tony de Paolo, Nate Kaslan, Tom Cook, Eric Terrill, John A. ColosiList of authors in order
- Landing page
-
https://doi.org/10.1175/jtech-d-20-0129.1Publisher landing page
- PDF URL
-
https://journals.ametsoc.org/downloadpdf/journals/atot/38/4/JTECH-D-20-0129.1.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://journals.ametsoc.org/downloadpdf/journals/atot/38/4/JTECH-D-20-0129.1.pdfDirect OA link when available
- Concepts
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Geology, Radar, Clutter, Artificial intelligence, Synthetic aperture radar, Tracking (education), Atmospheric duct, Remote sensing, Internal wave, Computer science, Support vector machine, Radar imaging, X band, Point (geometry), Computer vision, Physics, Meteorology, Telecommunications, Psychology, Pedagogy, Geometry, Oceanography, Atmosphere (unit), MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
23Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 4, 2023: 5, 2022: 3, 2021: 3Per-year citation counts (last 5 years)
- References (count)
-
30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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