Evidence map›Paper›PMID 31510035›Full record

ArticleSensors (Basel, Switzerland)2019

Observing the Ocean Submesoscale with Enhanced-Color GOES-ABI Visible Band Data.

Jason K Jolliff, M David Lewis, Sherwin Ladner, Richard L Crout

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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. Remote Sensing Applications in Coastal Areas.Sensors (Basel, Switzerland) · 2020
    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

4 authors.

Jason K JolliffU.S. Naval Research Laboratory, Stennis Space Center, Hancock County, MS 39529, USA. jason.jolliff@nrlssc.navy.mil.
M David LewisU.S. Naval Research Laboratory, Stennis Space Center, Hancock County, MS 39529, USA. david.lewis@nrlssc.navy.mil.
Sherwin LadnerU.S. Naval Research Laboratory, Stennis Space Center, Hancock County, MS 39529, USA. sherwin.ladner@nrlssc.navy.mil.
Richard L CroutU.S. Naval Research Laboratory, Stennis Space Center, Hancock County, MS 39529, USA. richard.crout@nrlssc.navy.mil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ocean color remote sensing has long been utilized as a fundamental research tool in the oceanographic investigations of coupled biological-physical processes. Despite numerous technical advances in the application of space borne ocean-viewing radiometers, host satellite platforms in a polar-orbiting configuration often render the temporal frequency of sensor data acquisition insufficient for studies of ocean processes that occur within increasingly smaller space-time scales. Whereas geostationary ocean color missions are presently the exception (GOCI) rather than the rule, this paper presents a method to convolve ocean reflectance data obtained from contemporary ocean-viewing multispectral radiometers (VIIRS, OLCI) with spectrally-limited Advanced Baseline Imager (ABI) data obtained from the GOES-R meteorological satellites. The method, Chromatic Domain Mapping (CDM), employs a colorimetry approach to visible range ocean reflectance data. The true color space is used as a frame-of-reference that is mapped by the dedicated yet temporally sparse ocean color sensors; coincident and spectrally coarse information from ABI is then used to estimate the evolution of the true color scene. The procedure results in very high resolution (~5 min) true color image sequences. Herein, example CDM applications of rapid frontal boundary evolution and feature displacement in the Gulf of Mexico are presented and future applications of this technique are discussed.

Indexed as

coastal ocean processescolorimetryocean colorocean remote sensing

Identifiers

PMID31510035
PMCPMC6767312

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Registered trials

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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.