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an algorithm for the retrieval of 30-m snow-free albedo from landsat surface reflectance and modis brdfWe present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.
Document ID
20120010478
Document Type
Reprint (Version printed in journal)
Authors
Shuai, Yanmin
(Earth Resources Technology, Inc. Laruel, MD, United States)
Masek, Jeffrey G.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Gao, Feng
(Earth Resources Technology, Inc. Laruel, MD, United States)
Schaaf, Crystal B.
(Boston Univ. Boston, MA, United States)
Date Acquired
August 26, 2013
Publication Date
May 17, 2011
Publication Information
Publication: Remote Sensing of Environment
Volume: 115
Subject Category
Earth Resources and Remote Sensing
Report/Patent Number
GSFC.JA.00335.2012
Funding Number(s)
CONTRACT_GRANT: NNX08AE94A
Distribution Limits
Public
Copyright
Other