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Remote Sens. 2016, 8(3), 263; doi:10.3390/rs8030263

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description and Validation

1
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
2
NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA
3
NOAA’s National Centers for Environmental Information (NCEI), 151 Patton Avenue, Asheville, NC 28801, USA
4
Cooperative Institute for Climate and Satellites–NC (CICS-NC), North Carolina State University, 151 Patton Avenue, Asheville, NC 28801, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Xuepeng Zhao, Wenze Yang, Viju John, Hui Lu, Ken Knapp, Alfredo R. Huete and Prasad S. Thenkabail
Received: 31 December 2015 / Revised: 3 February 2016 / Accepted: 22 February 2016 / Published: 22 March 2016
(This article belongs to the Special Issue Satellite Climate Data Records and Applications)
View Full-Text   |   Download PDF [2950 KB, uploaded 24 March 2016]   |  

Abstract

In- land surface models, which are used to evaluate the role of vegetation in the context of global climate change and variability, LAI and FAPAR play a key role, specifically with respect to the carbon and water cycles. The AVHRR-based LAI/FAPAR dataset offers daily temporal resolution, an improvement over previous products. This climate data record is based on a carefully calibrated and corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitable for climate studies. It spans from mid-1981 to the present. Further, this operational dataset is available in near real-time allowing use for monitoring purposes. The algorithm relies on artificial neural networks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparison with MODIS products and in situ data show the dataset is consistent and reliable with overall uncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect is observed in the broadleaf forest biomes with high LAI (>4.5) and FAPAR (>0.8) values. View Full-Text
Keywords: LAI; FAPAR; AVHRR; MODIS; climate data record; land product validation LAI; FAPAR; AVHRR; MODIS; climate data record; land product validation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Claverie, M.; Matthews, J.L.; Vermote, E.F.; Justice, C.O. A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description and Validation. Remote Sens. 2016, 8, 263.

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