Evidence map›Paper›PMID 35859986›Full record

ArticleJournal of geophysical research. Biogeosciences2022

Atmospheric Lengthscales for Global VSWIR Imaging Spectroscopy.

David R Thompson, Niklas Bohn, Philip G Brodrick, Nimrod Carmon, Michael L Eastwood, Regina Eckert, Cédric G Fichot, Joshua P Harringmeyer, Hai M Nguyen, Marc Simard and 1 more

Abstract read
In one paragraph

Article in Journal of geophysical research. Biogeosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Atmospheric Lengthscales for Global VSWIR Imaging Spectroscopy.Journal of geophysical research. Biogeosciences · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

David R ThompsonJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.ORCID https://orcid.org/0000-0003-1100-7550
Niklas BohnHelmholtz Centre Potsdam GFZ German Research Centre for Geosciences Potsdam Germany.ORCID https://orcid.org/0000-0003-4078-886X
Philip G BrodrickJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.ORCID https://orcid.org/0000-0001-9497-7661
Nimrod CarmonJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.
Michael L EastwoodJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.
Regina EckertJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.
Cédric G FichotDepartment of Earth and Environment Boston University Boston MA USA.ORCID https://orcid.org/0000-0002-1099-5764
Joshua P HarringmeyerDepartment of Earth and Environment Boston University Boston MA USA.ORCID https://orcid.org/0000-0001-8108-0644
Hai M NguyenJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.ORCID https://orcid.org/0000-0003-0690-0619
Marc SimardJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.ORCID https://orcid.org/0000-0002-9442-4562
Andrew K ThorpeJet Propulsion Laboratory California Institute of Technology Pasadena CA USA.ORCID https://orcid.org/0000-0001-7968-5433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Future global Visible Shortwave Infrared Imaging Spectrometers, such as the Surface Biology and Geology (SBG) mission, will regularly cover the Earth's entire terrestrial land area. These missions need high fidelity atmospheric correction to produce consistent maps of terrestrial and aquatic ecosystem traits. However, estimation of surface reflectance and atmospheric state is computationally challenging, and the terabyte data volumes of global missions will exceed available processing capacity. This article describes how missions can overcome this bottleneck using the spatial continuity of atmospheric fields. Contemporary imaging spectrometers oversample atmospheric spatial variability, so it is not necessary to invert every pixel. Spatially sparse solutions can train local linear emulators that provide fast, exact inversions in their vicinity. We find that estimating the atmosphere at 200 m scales can outperform traditional atmospheric correction, improving speed by one to two orders of magnitude with no measurable penalty to accuracy. We validate performance with an airborne field campaign, showing reflectance accuracies with RMSE of 1.1% or better compared to ground measurements of diverse targets. These errors are statistically consistent with retrieval uncertainty budgets. Local emulators can close the efficiency gap and make rigorous model inversion algorithms feasible for global missions such as SBG.

Indexed as

atmospheric correctionhyperspectral imageryimaging spectroscopy

Identifiers

PMID35859986
PMCPMC9285454

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.