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Record W1942800547

Soil moisture retrieval over the Mackenzie River basin using AMSR-E 6.9 GHz brightness temperature.

2007· article· en· W1942800547 on OpenAlexaboutno aff
Naira Chaouch, Robert Leconte, Ramata Magagi, Marouane Temimi

Bibliographic record

VenueEspace ÉTS (ETS) · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceBrightness temperatureWater contentMicrowaveRemote sensingAtmospheric radiative transfer codesMoistureSoil scienceHydrology (agriculture)Radiative transferMeteorologyGeologyGeography
DOInot available

Abstract

fetched live from OpenAlex

An approach is proposed to estimate soil moisture and to monitor its change from AMSR-E 6.9 GHz passive microwave data acquired over a large northern basin. The lack of in situ direct measurements is a major issue to be resolved to reach the aim of this work. Therefore, external ancillary data were used as a surrogate for available measurements. The methodology is based on the inversion of a microwave radiative transfer model. A sequential method based on the sensitivity of the emitted microwave signal to soil roughness and vegetation parameters was applied to calibrate the model. The roughness parameter was determined from AMSR-E data acquired under dry watershed conditions. The vegetation parameters were estimated under wet conditions. The method was first applied in the Peace-Athabasca Delta area located in Northern Alberta, Canada. The estimated geophysical parameters were then used to retrieve soil moisture estimates for sites with similar LAI values. It was found that the variations of the estimated soil moisture compared well with soil moisture imported from NARR data. A satisfactory agreement was obtained between soil moisture, precipitation and temperature.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.235
Teacher spread0.226 · 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 designObservational
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
Published2007
Admission routes1
Has abstractyes

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