Estimating the broadband longwave emissivity of global bare soil from the MODIS shortwave albedo product
作者:Cheng, J (Cheng, Jie)[ 1 ] ; Liang, SL (Liang, Shunlin)[ 1,2 ]
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
卷: 119  期: 2  页: 614-634
DOI: 10.1002/2013JD020689
出版年: JAN 27 2014

摘要
A constant land surface longwave emissivity value, or very simple parameterization, has been adopted by current land surface models because of a current lack of reliable observations. Of all the various Earth surface types, bare soil has the highest variations in broadband emissivity (BBE). We propose here a new algorithm to estimate BBE in the 8-13.5 mu m spectral range based on the Moderate Resolution Imaging Spectrometer (MODIS) albedo product for bare soil. This algorithm takes advantage of both Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) longwave emissivity and MODIS shortwave albedo products, as well as the established linear relationship between ASTER BBE and seven MODIS spectral albedos for bare soil. In order to mitigate step discontinuities in the global land surface BBE product, a transition zone was established and the BBE estimation method was also provided. Three linear formulae were derived for bare soil and transition zones, respectively. Given the accuracy of 0.01 for MODIS spectral albedo, the absolute accuracy of BBE retrieval is better than 0.017. The validation results obtained from the three field trials conducted in China and one field trial in western/southwestern U.S. indicated that the average difference between the estimated BBE and the measured BBE was 0.016. We have introduced a new strategy to generate global land surface BBE using MODIS data. This strategy was used to generate global 8day 1km land surface BBE products from 2000 through 2010.

通讯作者地址: Cheng, J (通讯作者)
Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA