Fred Baret

Dr. Fred Baret


Research Focus & Metrics

Academic Career Length

40Years (1987-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 1996 in Remote Sensing of Environment
Verified
Journal Article
Closed access
GRGeneviève Rondeaux
Geneviève Rondeaux
MSMichael Steven
Michael Steven
FBFred Baret
Fred Baret

1 November 1990 in Remote Sensing of Environment
Verified
Journal Article
Closed access
SJS. Jacquemoud
S. Jacquemoud
FBFred Baret
Fred Baret

1 September 2009 in Remote Sensing of Environment
Verified
Journal Article
Closed access
SJStéphane Jacquemoud
Stéphane Jacquemoud
WVWout Verhoef
Wout Verhoef
FBFred Baret
Fred Baret
CBCédric Bacour
Cédric Bacour
PZPablo J. Zarco-Tejada
Pablo J. Zarco-Tejada
SUSusan Ustin
Susan Ustin

1 February 1991 in Remote Sensing of Environment
Verified
Journal Article
Closed access
FBFred Baret
Fred Baret
GGG. Guyot
G. Guyot

1 January 2004 in Agricultural and Forest Meteorology
Verified
Journal Article
Closed access
IJInge Jonckheere
Inge Jonckheere
SFStefan Fleck
Stefan Fleck
KNKris Nackaerts
Kris Nackaerts
BMBart Muys
Bart Muys
PCPol Coppin
Pol Coppin
FBFred Baret
Fred Baret

16 July 2019 in Reviews of Geophysics
Verified
Journal Article
Open access
PDF file
HFHongliang Fang
Hongliang Fang
FBFred Baret
Fred Baret
SPStephen Plummer
Stephen Plummer
GSGabriela Schaepman‐Strub
Gabriela Schaepman‐Strub
Leaf area index (LAI) is a critical vegetation structural variable and is essential in the feedback of vegetation to the climate system. The advancement of the global Earth Observation has enabled the development of global LAI products and boosted global Earth system modeling studies. This overview provides a comprehensive analysis of LAI field measurements and remote sensing estimation methods, the product validation methods and product uncertainties, and the application of LAI in global studies. First, the paper clarifies some definitions related to LAI and introduces methods to determine LAI from field measurements and remote sensing observations. After introducing some major global LAI products, progresses made in temporal compositing and prospects for future LAI estimation are analyzed. Subsequently, the overview discusses various LAI product validation schemes, uncertainties in global moderate resolution LAI products, and high resolution reference data. Finally, applications of LAI in global vegetation change, land surface modeling, and agricultural studies are presented. It is recommended that (1) continued efforts are taken to advance LAI estimation algorithms and provide high temporal and spatial resolution products from current and forthcoming missions; (2) further validation studies be conducted to address the inadequacy of current validation studies, especially for underrepresented regions and seasons; and (3) new research frontiers, such as machine learning algorithms, light detection and ranging technology, and unmanned aerial vehicles be pursued to broaden the production and application of LAI.