Evidence map›Paper›PMID 36082339›Full record

ArticleRemote sensing2021

Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor.

Charlotte De Grave, Luca Pipia, Bastian Siegmann, Pablo Morcillo-Pallarés, Juan Pablo Rivera-Caicedo, José Moreno, Jochem Verrelst

Abstract read
In one paragraph

Article in Remote sensing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

7 authors.

Charlotte De GraveImage Processing Laboratory (IPL), Parc Científic, Universitat de Valencia, 46980 Paterna, Spain.ORCID https://orcid.org/0000-0002-9327-9420
Luca PipiaInstitut Cartogrfic i Geològic de Catalunya (ICGC), Parc de Montjüic, 08038 Barcelona, Spain.ORCID https://orcid.org/0000-0003-0759-4422
Bastian SiegmannForschungszentrum Jülich GmbH, Institute of Bio- and Geosciences, Plant Sciences (IBG-2), D-52425 Jülich, Germany.
Pablo Morcillo-PallarésImage Processing Laboratory (IPL), Parc Científic, Universitat de Valencia, 46980 Paterna, Spain.ORCID https://orcid.org/0000-0002-0970-9492
Juan Pablo Rivera-CaicedoCONACyT-UAN, Secretaría de Investigación y Posgrado, Universidad Autónoma de Nayarit, Ciudad de la Cultura Amado Nervo, 63155 Tepic, Nayarit, Mexico.ORCID https://orcid.org/0000-0003-3188-1448
José MorenoImage Processing Laboratory (IPL), Parc Científic, Universitat de Valencia, 46980 Paterna, Spain.ORCID https://orcid.org/0000-0002-5283-3333
Jochem VerrelstImage Processing Laboratory (IPL), Parc Científic, Universitat de Valencia, 46980 Paterna, Spain.ORCID https://orcid.org/0000-0002-6313-2081

Funding

European Research Council 755617
6 · The paper itself

Abstract

ESA's Eighth Earth Explorer mission "FLuorescence EXplorer" (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem formation with Sentinel-3 (S3), which conveys the Ocean and Land Color Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In support of FLEX's preparatory activities, this paper presents a first validation exercise of OLCI vegetation products against in situ data coming from the 2018 FLEXSense campaign. During this campaign, leaf chlorophyll content (LCC) and leaf area index (LAI) measurements were collected over croplands, while HyPlant DUAL images of the area were acquired at a 3 m spatial resolution. A multiscale validation strategy was pursued. First, estimates of these two variables, together with the combined canopy chlorophyll content (CCC = LCC × LAI), were obtained at the HyPlant spatial resolution and were compared against the in situ measurements. Second, the fine-scale retrieval maps from HyPlant were coarsened to the S3 spatial scale as a reference to assess the quality of the OLCI vegetation products. As an intermediary step, vegetation products extracted from Sentinel-2 data were used to compare retrievals at the in-between spatial resolution of 20 m. For all spatial scales, CCC delivered the most accurate estimates with the smallest prediction error obtained at the 300 m resolution (R

Indexed as

canopy chlorophyll contentFLEXHyPlantleaf area indexleaf chlorophyll contentmoderate spatial resolutionOLCIpixel heterogeneitySentinel-3

Identifiers

PMID36082339
PMCPMC7613399

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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.