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Author: search.filters.author.Liang, ShunlinSubject: search.filters.subject.snow albedo

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    Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach
    (MDPI, 2015-05-04) He, Tao; Liang, Shunlin; Wang, Dongdong; Chen, Xiaona; Song, Dan-Xia; Jiang, Bo
    Monitoring surface albedo at medium-to-fine resolution (<100 m) has become increasingly important for medium-to-fine scale applications and coarse-resolution data evaluation. This paper presents a method for estimating surface albedo directly using top-of-atmosphere reflectance. This is the first attempt to derive surface albedo for both snow-free and snow-covered conditions from medium-resolution data with a single approach. We applied this method to the multispectral data from the wide-swath Chinese HuanJing (HJ) satellites at a spatial resolution of 30 m to demonstrate the feasibility of this data for surface albedo monitoring over rapidly changing surfaces. Validation against ground measurements shows that the method is capable of accurately estimating surface albedo over both snow-free and snow-covered surfaces with an overall root mean square error (RMSE) of 0.030 and r-square (R2) of 0.947. The comparison between HJ albedo estimates and the Moderate Resolution Imaging Spectral Radiometer (MODIS) albedo product suggests that the HJ data and proposed algorithm can generate robust albedo estimates over various land cover types with an RMSE of 0.011–0.014. The accuracy of HJ albedo estimation improves with the increase in view zenith angles, which further demonstrates the unique advantage of wide-swath satellite data in albedo estimation.
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    Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach
    (Multidisciplinary Digital Publishing Institute (MDPI), 2015-05-04) He, Tao; Liang, Shunlin; Wang, Dongdong; Chen, Xiaona; Song, Dan-Xia; Jiang, Bo
    Monitoring surface albedo at medium-to-fine resolution (<100 m) has become increasingly important for medium-to-fine scale applications and coarse-resolution data evaluation. This paper presents a method for estimating surface albedo directly using top-of-atmosphere reflectance. This is the first attempt to derive surface albedo for both snow-free and snow-covered conditions from medium-resolution data with a single approach. We applied this method to the multispectral data from the wide-swath Chinese HuanJing (HJ) satellites at a spatial resolution of 30 m to demonstrate the feasibility of this data for surface albedo monitoring over rapidly changing surfaces. Validation against ground measurements shows that the method is capable of accurately estimating surface albedo over both snow-free and snow-covered surfaces with an overall root mean square error (RMSE) of 0.030 and r-square (R2) of 0.947. The comparison between HJ albedo estimates and the Moderate Resolution Imaging Spectral Radiometer (MODIS) albedo product suggests that the HJ data and proposed algorithm can generate robust albedo estimates over various land cover types with an RMSE of 0.011–0.014. The accuracy of HJ albedo estimation improves with the increase in view zenith angles, which further demonstrates the unique advantage of wide-swath satellite data in albedo estimation.
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    Mapping daily snow/ice shortwave broadband albedo from Moderate Resolution Imaging Spectroradiometer (MODIS): The improved direct retrieval algorithm and validation with Greenland in situ measurement
    (American Geophysical Union, 2005-05-26) Liang, Shunlin; Stroeve, Julienne; Box, Jason E.
    Snow/ice albedo is a critical variable in surface energy balance calculations. The Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used routinely to provide global land surface albedo. The MODIS algorithm includes atmospheric correction, surface reflectance angular modeling, and narrowband to broadband albedo conversion. In an earlier study, a "direct retrieval" methodology was proposed to calculate instantaneous albedo over snow and ice-covered surfaces directly from top-of-atmosphere (TOA) MODIS reflectance data. The method consists of extensive radiative transfer simulations for a variety of atmospheric and surface snow conditions and links the TOA reflectance with surface broadband albedo through regression analysis. Therefore the direct retrieval algorithm implicitly incorporates in a single step all three procedures used in the standard MODIS surface albedo algorithm. This study presents improvements to the retrieval algorithm including validation with in situ measurements distributed over the Greenland ice sheet. Comparison with surface observations demonstrates that the direct retrieval algorithm can produce very accurate daily snow/ice albedo with mean bias of less than 0.02 and residual standard error of 0.04.