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Record W3197778412 · doi:10.1109/tgrs.2021.3104626

Statistical Comparison of Melting Iceberg Backscatter Embedded in Sea Ice and Open Water Using RADARSAT-2 Images of the Newfoundland Sea

2021· article· en· W3197778412 on OpenAlexafffundabout
Umma H. Himi, Md. Saimoom Ferdous, Desmond Power, Peter McGuire

Bibliographic record

VenueIEEE Transactions on Geoscience and Remote Sensing · 2021
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsCentre For Cold Ocean Resources EngineeringMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIcebergSea iceOpen waterGeologySynthetic aperture radarRemote sensingPolarimetryBackscatter (email)ClutterOceanographyMeteorologyRadarScatteringGeographyComputer sciencePhysics

Abstract

fetched live from OpenAlex

This article investigates and compares polarimetric signatures of icebergs embedded in sea ice and icebergs in open water. The main objective is to study on the backscatter properties of melting iceberg and to check on whether there is any distinguishable property in them in the case of different background clutter conditions (i.e. sea ice and open water). This study results will improve the potential of iceberg detection using radar polarimetry. RADARSAT-2 images have been used for the analysis acquired over locations near the coastline (approximately 3–35 km) of the island of Newfoundland. For analysis, polarimetry parameters, such as co-(HH) and cross-(HV) polarization and several popular decomposition techniques, specifically Pauli, Freeman–Durden, Yamaguchi, Cloud–Pottier, and van Zyl, have been used to determine the polarimetric signatures of icebergs and sea ice. The statistical hypothesis T-test has been applied to achieve a precise comparison among backscatters from different icebergs groups. Statistical results tend to show a dominant surface scattering mechanism for icebergs in all types of clutter conditions. Moreover, icebergs in open water produce larger volume scatter than icebergs in sea ice, whereas icebergs in sea ice produce larger surface scatter than icebergs in open water.

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 score0.900
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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

Citations6
Published2021
Admission routes3
Has abstractyes

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