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Record W4400579367 · doi:10.1109/tgrs.2024.3427411

Radar Scattering Features Under High Wind Conditions From Spaceborne Quad-Polarization SAR Observations

2024· article· en· W4400579367 on OpenAlexaff
Shengren Fan, Vladimir Kudryavtsev, Biao Zhang, William Perrie

Bibliographic record

VenueIEEE Transactions on Geoscience and Remote Sensing · 2024
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersMinistry of Science and Higher Education of the Russian FederationNational Natural Science Foundation of China
KeywordsRemote sensingSynthetic aperture radarSpace-based radarRadarRadar imagingScatteringGeologyPolarization (electrochemistry)Early-warning radarSide looking airborne radarRadar cross-sectionEnvironmental scienceRadar engineering detailsComputer scienceOpticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

This study examines the impact of wave breaking (WB) and Bragg scattering on the normalized radar cross section (NRCS) to reveal radar scattering features during high wind conditions. This is conducted by decomposing C-band quasi-synchronous wide-swath quad-polarization synthetic aperture radar (SAR) observations acquired from the RADARSAT Constellation Mission (RCM) and RADARSAT-2 (RS-2). The analysis results clearly demonstrate that the polarization difference (PD) associated with Bragg scattering saturates at high wind speeds, while still maintaining azimuthal modulation. Notably, the radar returns from breaking waves at cross-polarization (HV or VH) exhibit higher sensitivity to wind speeds but lower sensitivity to wind direction, compared to co-polarization (HH or VV). Moreover, our analyses show that WB contributes 40%, 80%, and 90% of VV-, HH-, and HV-polarized NRCS, respectively. This study highlights the unique capabilities provided by collocated RCM and RS-2 observations for investigating radar scattering features under high wind conditions. Results of this study can be further used to develop empirical models for estimating co- and cross-polarization radar backscatters induced by WB under high wind speeds.

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: Methods · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.771

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 head0.013
GPT teacher head0.229
Teacher spread0.217 · 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
GenreMethods

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

Citations3
Published2024
Admission routes1
Has abstractyes

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