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Record W2197439631

Biomass Estimation of Boreal Forests Using Single-Pass Polarimetric SAR Tomography at L-band

2014· article· en· W2197439631 on OpenAlexaboutno aff
Yué Huang, Qiaoping Zhang, Marcus Schwaebisch, Ming Wei, Bryan Mercer

Bibliographic record

VenueEUSAR 2014; 10th European Conference on Synthetic Aperture Radar; Proceedings of · 2014
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsTaigaRemote sensingBiomass (ecology)PolarimetryLidarEnvironmental scienceBorealL bandTomographySynthetic aperture radarForestryGeologyGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper addresses forest heights and biomass estimation by applying single-pass polarimetric SAR tomography to PolInSAR data acquired by Intermap's L-Band SAR system. For the purpose of biomass estimation, the feasibility of this special single-pass tomographic configuration is demonstrated over boreal forests at the test site of Edson in Alberta, Canada. The estimated ground topography and tree top heights have been validated against LiDAR data[1]. The corresponding allometric model is calculated from the in-situ data provided by West Fraser Mills Ltd forest company and the biomass over our test sites is estimated via this allometic model.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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.

Study designBench or experimental
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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEUSAR 2014; 10th European Conference on Synthetic Aperture Radar; Proceedings ofSame topicSynthetic Aperture Radar (SAR) Applications and TechniquesFrench-language works237,207