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Record W2889410258 · doi:10.1016/j.rse.2018.08.025

Preliminary assessment of 20-m surface albedo retrievals from sentinel-2A surface reflectance and MODIS/VIIRS surface anisotropy measures

2018· article· en· W2889410258 on OpenAlexaff
Zhan Li, Angela Erb, Qingsong Sun, Yan Liu, Yanmin Shuai, Zhuosen Wang, Peter B. Boucher, Crystal Schaaf

Bibliographic record

VenueRemote Sensing of Environment · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersEuropean CommissionU.S. Geological SurveyNational Aeronautics and Space Administration
KeywordsBidirectional reflectance distribution functionRemote sensingEnvironmental scienceAlbedo (alchemy)Moderate-resolution imaging spectroradiometerShortwaveVisible Infrared Imaging Radiometer SuiteSatelliteAtmospheric radiative transfer codesRadiometerSpectroradiometerPyranometerRadiative transferGeologyRadiationReflectivityPhysicsOptics

Abstract

fetched live from OpenAlex

Satellite-based retrievals of land surface albedo at 20-m resolution are generated by coupling the surface reflectances from the recently launched Sentinel-2A satellite with surface anisotropy information (as described by Bidirectional Reflectance Distribution Function, BRDF) from either the MODerate-resolution Imaging Spectroradiometer (MODIS) or the Visible Infrared Imaging Radiometer Suite (VIIRS). The intrinsic black-sky albedo (BSA) and white-sky albedo (WSA) values of the surface are derived at the six shortwave spectral bands of Sentinel-2A's Multi Spectral Instrument (MSI). A specific set of narrow-to-broadband conversion coefficients is derived from radiative transfer simulations and presented for the generation of broadband albedos. Initial evaluation uses well-calibrated ground-based albedo measurements by pyranometers mounted on the towers at seven sites of the Surface Radiation Network (SURFRAD). Over those sites where pyranometer measurement footprints are not spatially representative of the landscape covered by the satellite pixels (i.e., spatially nonrepresentative) at the grid scales (500 m to 1 km) of the MODIS and VIIRS products, the finer-resolution Sentinel-2A albedos manifested a pronounced decrease in root mean squared error (RMSE) and mean bias in the evaluation against the ground-based data as compared to the coarser resolution albedo products of MODIS and VIIRS. This decrease occurs because the 20-m Sentinel-2A albedo values are better able to resolve the spatial details of surface albedo within the ground-based instrument footprints than the coarser resolution sensors. This preliminary evaluation also demonstrates the consistency of the Sentinel-2A albedo results whether using the MODIS BRDF or the VIIRS BRDF products for the surface anisotropy information. The RMSEs and mean biases of the Sentinel-2A albedos over all the seven validation sites are both within the accuracy requirement of ±0.05 absolute albedo units for satellite derived albedo products. This study, to generate Sentinel-2A MSI albedo with either MODIS or VIIRS BRDFs, extends previous efforts of Landsat TM, ETM+ and OLI albedo and enhances the continuity of finer-resolution albedo data. Such long-term and higher resolution records of surface albedo improve the investigations into the changes and drivers of local/regional surface energy balance over heterogeneous regions and increasingly fragmented landscapes across the globe due to natural and human-induced land cover changes.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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

Citations79
Published2018
Admission routes1
Has abstractyes

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