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Record W3199107852 · doi:10.1109/jstars.2021.3110198

Retrieval of Ocean Surface Radial Velocities With RADARSAT-2 Along-Track Interferometry

2021· article· en· W3199107852 on OpenAlexaff
Christoph H. Gierull

Bibliographic record

VenueIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsDepartment of National DefenceDefence Research and Development Canada
Fundersnot available
KeywordsSynthetic aperture radarRemote sensingCalibrationGeodesyInterferometryInterferometric synthetic aperture radarAbsolute phasePhase (matter)Radial velocityGeologyEnvironmental scienceComputer sciencePhysicsOpticsComputer vision

Abstract

fetched live from OpenAlex

This work provides a detailed presentation of dualaperture synthetic aperture radar (SAR) data processing scheme for the retrieval of ocean surface radial velocities. This scheme includes processing of raw SAR data, co-registration of alongtrack interferometric samples, magnitude and absolute phase calibration, and coherent averaging (multi-looking). Several approaches for absolute phase calibration are provided and compared. Some of the attempted approaches can potentially be used over open ocean (i.e. in scenes that do not contain any land). Main goal of attempting different approaches for absolute phase calibration was to determine their relative performance, and determine the potential feasibility of some approaches over open ocean. Data processing scheme is applied to a RADARSAT-2 dualchannel MODEX-1 acquisition over a section of Florida Current. For the dataset used in this study, different absolute phase calibration methods yielded similar radial velocity estimates, with relative mean and RMS differences within approximately 0.1 m/s. Estimates from SAR ATI were also compared to estimates from NASAs OSCAR dataset. Comparison of visually identified currents showed close spatial overlap between estimates from the two sources. RMS difference was found to be approximately 0.30 m/s. This difference can be attributed to the physical and temporal differences between the estimates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.207
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingSame topicOcean Waves and Remote SensingFrench-language works237,207