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Generating Vegetation Leaf Area Index Earth System Data Record from Multiple SensorsThe generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.
Document ID
20110005518
Document Type
Reprint (Version printed in journal)
Authors
Ganguly, Sangram (Boston Univ. Boston, MA, United States)
Schull, Mitchell A. (Boston Univ. Boston, MA, United States)
Samanta, Arindam (Boston Univ. Boston, MA, United States)
Shabanov, Nikolay V. (National Environmental Satellite Service Camp Springs, MD, United States)
Milesi, Cristina (NASA Ames Research Center Moffett Field, CA, United States)
Nemani, Ramakrishna R. (NASA Ames Research Center Moffett Field, CA, United States)
Knyazikhin, Yuri (Boston Univ. Boston, MA, United States)
Myneni, Ranga B. (Boston Univ. Boston, MA, United States)
Date Acquired
August 25, 2013
Publication Date
July 29, 2008
Publication Information
Publication: Remote Sensing of Environment
Volume: 112
Issue: 12
ISSN: 0034-4257
Subject Category
Earth Resources and Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NNX08AE81G
Distribution Limits
Public
Copyright
Other