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A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case StudyIn- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.
Document ID
20170002732
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Claverie, Martin
(Maryland Univ. College Park, MD, United States)
Matthews, Jessica L.
(National Centers for Environmental Information (NCEI) Asheville, CO, United States)
Vermote, Eric F.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Justice, Christopher O.
(Maryland Univ. College Park, MD, United States)
Date Acquired
March 31, 2017
Publication Date
March 22, 2016
Publication Information
Publication: Remote Sensing
Publisher: MDPI
Volume: 8
Issue: 3
e-ISSN: 2072-4292
Subject Category
Geosciences (General)
Report/Patent Number
GSFC-E-DAA-TN40720
Funding Number(s)
CONTRACT_GRANT: NNX14AR70A
Distribution Limits
Public
Copyright
Other
Keywords
MODIS
AVHRR
climate data record
FAPAR
LAI

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