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Record W4220969092 · doi:10.1080/10106049.2022.2060313

Effects of the new Priestly-Taylor equation on determining the boundary of LST/FVC space for soil moisture monitoring

2022· article· en· W4220969092 on OpenAlex
Hao Sun, Zhiyu Zhao

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeocarto International · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBoundary (topology)Remote sensingVegetation (pathology)Space (punctuation)MoistureEnvironmental scienceMathematicsPhysicsMeteorologyComputer scienceGeographyMathematical analysis

Abstract

fetched live from OpenAlex

Land Surface Temperature and Fractional Vegetation Coverage (LST/FVC) space is a classical model in remote sensing of soil moisture (SM). Its most vital issue is the determination of the boundary i.e. dry and wet edges. Visual interpretation and automatic fitting methods are very demanding for the research area. In contrast, theoretical calculation of the boundary has great application potential, where the traditional Priestley-Taylor (PT) equation has been introduced to derive a Sun2016 method. Recently, a new Priestly-Taylor equation was suggested. In order to furtherly improve the optical & thermal remote sensing of SM, we evaluated the new PT equation for boundary determination through deriving a Sun 2021 Sun H, Liu H, Ma Y, Xia Q. 2021. Optical remote sensing indexes of soil moisture: evaluation and improvement based on aircraft experiment observations. Remote Sens. 13(22):4638.[Crossref] , [Google Scholar] method. The evaluation was conducted using data from three aircraft experiments for SM observation i.e. SMAPVEX12, SMAPVEX16 in Iowa, and SMAPVEX16 in Manitoba. Simulated data with the Simsphere model was also used. Results demonstrated that the effects of the new PT equation are related to air temperature (Ta). For a certain range of Ta such as from 290 K to 310 K, the Sun 2021 Sun H, Liu H, Ma Y, Xia Q. 2021. Optical remote sensing indexes of soil moisture: evaluation and improvement based on aircraft experiment observations. Remote Sens. 13(22):4638.[Crossref] , [Google Scholar] method is close to the Sun2016 method, which implies limited influence of the new PT equation within that range. For Ta out of that range, the Sun 2021 Sun H, Liu H, Ma Y, Xia Q. 2021. Optical remote sensing indexes of soil moisture: evaluation and improvement based on aircraft experiment observations. Remote Sens. 13(22):4638.[Crossref] , [Google Scholar] method presented better performance than the Sun2016, which implies stronger suitability of the new PT equation. Sensitivity analysis indicated that the new PT equation increases the sensitivity of calculated wet edge to Ta while decreases its sensitivity to the other input variables. For future extensive application, we also explored convenient ways for determining some essential parameters in the Sun 2021 Sun H, Liu H, Ma Y, Xia Q. 2021. Optical remote sensing indexes of soil moisture: evaluation and improvement based on aircraft experiment observations. Remote Sens. 13(22):4638.[Crossref] , [Google Scholar] method. The new PT equation has potential to promote the optical & thermal remote sensing of SM, evapotranspiration, drought, etc.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.222

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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