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Improving the AVHRR Long Term Data Record BRDF CorrectionThe Long Term Data Record (LTDR) project has the goal of developing a quality and consistent surface reflectance product from coarse resolution optical sensors. This paper focuses on the Advanced Very High Resolution Radiometer (AVHRR) part of the record, using the Moderate Resolution Imaging Spectrometer (MODIS) instrument as a reference. When a surface reflectance time series is acquired from satellites with variable observation geometry, the directional variation generates an apparent noise which can be corrected by modeling the bidirectional reflectance distribution function (BRDF). The VJB (Vermote, Justice and Bréon, 2009) method estimates a target’s BRDF shape using 5 years of observation and corrects for directional effects maintaining the high temporal resolution of the measurement using the instantaneous Normalized Difference Vegetation Index (NDVI). The method was originally established on MODIS data but its viability and optimization for AVHRR data have not been fully explored. In this study we analyze different approaches to find the most robust way of applying the VJB correction to AVHRR data, considering that high noise in the red band (B1) caused by atmospheric effect makes the VJB method unstable. Firstly, our results show that for coarse spatial resolution, where the vegetation dynamics of the target don’t change significantly, deriving BRDF parameters from 15+ years of observations reduces the average noise by up to 7% in the Near Infrared (NIR) band and 6% in the NDVI, in comparison to using 3-year windows. Secondly, we find that the VJB method can be modified for AVHRR data to improve the robustness of the correction parameters and decrease the noise by an extra 8% and 9% in the red and NIR bands with respect to using the classical VJB inversion. We do this by using the Stable method, which obtains the volumetric BRDF parameter (V) based on its NDVI dependency, and then obtains the geometric BRDF parameter (R) through the inversion of just one parameter.
Document ID
20190002442
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Villaescusa Nadal, Jose Luis
(Maryland Univ. College Park, MD, United States)
Franch Gras, Belen
(Maryland Univ. College Park, MD, United States)
Vermote, Eric
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Roger, Jean-Claude
(Maryland Univ. College Park, MD, United States)
Date Acquired
April 11, 2019
Publication Date
March 1, 2019
Publication Information
Publication: Remote Sensing
Publisher: MDPI
Volume: 11
Issue: 5
ISSN: 2072-4292
e-ISSN: 2072-4292
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN66741
Funding Number(s)
CONTRACT_GRANT: NNX17AJ63A
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Keywords
LTDR
VJB
AVHRR
MODIS
Directional correction
BRDF
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