吴晓丹等：Assessment of NPP VIIRS Albedo Over Heterogeneous Crop Land in Northern China

Assessment of NPP VIIRS Albedo Over Heterogeneous Crop Land in Northern China

作者:Wu, XD (Wu, Xiaodan)[ 1,2,3,4 ] ; Wen, JG (Wen, Jianguang)[ 1 ] ; Xiao, Q (Xiao, Qing)[ 1 ] ; Yu, YY (Yu, Yunyue)[ 5 ] ; You, DQ (You, Dongqin)[ 1 ] ; Hueni, A (Hueni, Andreas)[ 3 ]

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

卷: 122  期: 24  页: 13138-13154

DOI: 10.1002/2017JD027262

出版年: DEC 27 2017

摘要

In this paper, the accuracy of Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) land surface albedo, which is derived from the direct estimation algorithm, was assessed using ground-based albedo observations from a wireless sensor network over a heterogeneous cropland in the Huailai station, northern China. Data from six nodes spanning 2013-2014 over vegetation, bare soil, and mixed terrain surfaces were utilized to provide ground reference at VIIRS pixel scale. The performance of VIIRS albedo was also compared with Global LAnd Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) albedos (Collection 5 and 6). The results indicate that the current granular VIIRS albedo has a high accuracy with a root-mean-square error of 0.02 for typical land covers. They are significantly correlated with ground references indicated by a correlation coefficient (R) of 0.73. The VIIRS albedo shows distinct advantages to GLASS and MODIS albedos over bare soil and mixed-cover surfaces, while it is inferior to the other two products over vegetated surfaces. Furthermore, its time continuity and the ability to capture the abrupt change of surface albedo are better than that of GLASS and MODIS albedo.

通讯作者地址: Wen, JG (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China

[ 2 ] Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou, Gansu, Peoples R China

[ 3 ] Univ Zurich, Remote Sensing Labs, Zurich, Switzerland

[ 4 ] Univ Chinese Acad Sci, Beijing, Peoples R China

[ 5 ] NOAA, NESDIS, STAR, Camp Springs, MD USA