Evaluation of Moderate-resolution Imaging Spectroradiometer (MODIS) snow albedo product (MCD43A) over tundra

Zhuosen Wang, Crystal B. Schaaf, Mark J. Chopping, Alan H. Strahler, Jindi Wang, Miguel O. Román, Adrian V. Rocha, Curtis E. Woodcock, Yanmin Shuai

Research output: Contribution to journalArticlepeer-review

135 Scopus citations

Abstract

This study assesses the MODIS standard Bidirectional Reflectance Distribution Function (BRDF)/Albedo product, and the daily Direct Broadcast BRDF/Albedo algorithm at tundra locations under large solar zenith angles and high anisotropic diffuse illumination and multiple scattering conditions. These products generally agree with ground-based albedo measurements during the snow cover period when the Solar Zenith Angle (SZA) is less than 70°. An integrated validation strategy, including analysis of the representativeness of the surface heterogeneity, is performed to decide whether direct comparisons between field measurements and 500-m satellite products were appropriate or if the scaling of finer spatial resolution airborne or spaceborne data was necessary. Results indicate that the Root Mean Square Errors (RMSEs) are less than 0.047 during the snow covered periods for all MCD43 albedo products at several Alaskan tundra areas. The MCD43 1-day daily albedo product is particularly well suited to capture the rapidly changing surface conditions during the spring snow melt. Results also show that a full expression of the blue sky albedo is necessary at these large SZA snow covered areas because of the effects of anisotropic diffuse illumination and multiple scattering. In tundra locations with dark residue as a result of fire, the MODIS albedo values are lower than those at the unburned site from the start of snowmelt.

Original languageEnglish
Pages (from-to)264-280
Number of pages17
JournalRemote Sensing of Environment
Volume117
DOIs
StatePublished - 15 Feb 2012

Keywords

  • High latitude tundra
  • MODIS standard and daily Albedo product
  • Snow
  • Spatial representativeness

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