Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor.
FLEX
HyPlant
OLCI
Sentinel-3
canopy chlorophyll content
leaf area index
leaf chlorophyll content
moderate spatial resolution
pixel heterogeneity
Journal
Remote sensing
ISSN: 2072-4292
Titre abrégé: Remote Sens (Basel)
Pays: Switzerland
ID NLM: 101624426
Informations de publication
Date de publication:
07 Apr 2021
07 Apr 2021
Historique:
entrez:
9
9
2022
pubmed:
7
4
2021
medline:
7
4
2021
Statut:
ppublish
Résumé
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
Identifiants
pubmed: 36082339
doi: 10.3390/rs13081419
pmc: PMC7613399
mid: EMS152670
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1419Subventions
Organisme : European Research Council
ID : 755617
Pays : International
Déclaration de conflit d'intérêts
Conflicts of Interest: The authors declare no conflict of interest.
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