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A Method for Improving Hotspot Directional Signatures in BRDF Models Used for MODISThe semi-empirical, kernel-driven, linear RossThick-LiSparseReciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is used to generate the routine MODIS BRDFAlbedo product due to its global applicability and the underlying physics. A challenge of this model in regard to surface reflectance anisotropy effects comes from its underestimation of the directional reflectance signatures near the Sun illumination direction; also known as the hotspot effect. In this study, a method has been developed for improving the ability of the RTLSR model to simulate the magnitude and width of the hotspot effect. The method corrects the volumetric scattering component of the RTLSR model using an exponential approximation of a physical hotspot kernel, which recreates the hotspot magnitude and width using two free parameters (C(sub 1) and C(sub 2), respectively). The approach allows one to reconstruct, with reasonable accuracy, the hotspot effect by adjusting or using the prior values of these two hotspot variables. Our results demonstrate that: (1) significant improvements in capturing hotspot effect can be made to this method by using the inverted hotspot parameters; (2) the reciprocal nature allow this method to be more adaptive for simulating the hotspot height and width with high accuracy, especially in cases where hotspot signatures are available; and (3) while the new approach is consistent with the heritage RTLSR model inversion used to estimate intrinsic narrowband and broadband albedos, it presents some differences for vegetation clumping index (CI) retrievals. With the hotspot-related model parameters determined a priori, this method offers improved performance for various ecological remote sensing applications; including the estimation of canopy structure parameters.
Document ID
20170002736
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
External Source(s)
Authors
Ziti Jiao
(Beijing Normal University Beijing, Beijing, China)
Crystal B Schaaf
(University of Massachusetts Boston Boston, Massachusetts, United States)
Yadong Dong
(Beijing Normal University Beijing, Beijing, China)
Miguel O Roman
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Michael J Hill
(University of North Dakota Grand Forks, North Dakota, United States)
Jing M Chen
(University of Toronto Toronto, Ontario, Canada)
Zhuosen Wang
(University of Massachusetts Boston Boston, Massachusetts, United States)
Hu Zhang
(Beijing Normal University Beijing, Beijing, China)
Edward Saenz
(University of Massachusetts Boston Boston, Massachusetts, United States)
Rajesh Poudyal
(SCIENCE SYSTEMS AND APPLICATIONS INC Lanham, MD, United States)
Charles Gatebe
(Universities Space Research Association Columbia, Maryland, United States)
Francois-Marie Breon
(Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette, France)
Xiaowen Li
(Beijing Normal University Beijing, Beijing, China)
Alan Strahler
(Boston University Boston, Massachusetts, United States)
Date Acquired
March 31, 2017
Publication Date
August 23, 2016
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier
Volume: 186
Issue Publication Date: December 1, 2016
ISSN: 0034-4257
Subject Category
Geosciences (General)
Solar Physics
Report/Patent Number
GSFC-E-DAA-TN40811
Report Number: GSFC-E-DAA-TN40811
ISSN: 0034-4257
Funding Number(s)
CONTRACT_GRANT: 2013CB733400
CONTRACT_GRANT: NNG11HP16A
CONTRACT_GRANT: NSFC 41171261
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: NNG12HP08C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
airborne measurements
linear RTLSR model
hotspot kernel
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