Monitoring snow cover using Chinese meteorological satellite data over China
作者:Yang, JT (Yang, Juntao)[ 1,2 ] ; Jiang, LM (Jiang, Lingmei)[ 1,2 ] ; Shi, JC (Shi, Jiancheng)[ 3 ] ; Wu, SL (Wu, Shengli)[ 4 ] ; Sun, RJ (Sun, Ruijing)[ 4 ] ; Yang, H (Yang, Hu)[ 5 ]
REMOTE SENSING OF ENVIRONMENT
卷: 143  页: 192-203
DOI: 10.1016/j.rse.2013.12.022
出版年: MAR 5 2014

摘要
Snow cover plays an important role in hydrological processes and global climate change research. Geostationary satellites with high temporal resolution provide multiple observations in one day, which highlights their potential for monitoring real-time snow-cover information. In this paper, data from the Chinese meteorological satellites Fengyun-2D (FY-2D), Fengyun-2E (FY-2E) and Fengyun-3B (FY-3B) was used for snow-cover mapping over China. A new method of detecting snow-cover information is proposed, that combines the Visible and Infrared Spin Scan-Radiometer (VISSR) on board the geostationary satellites FY-2D and FY-2E and the Microwave Radiation Imager (MWRI) on board the polar orbiting satellite FY-3B. The snow cover estimated from Fengyun satellites was compared by the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover products (MOD10A1 and MYD10A1), and Interactive Multisensor Snow and Ice Mapping System (IMS) snow-cover products. The Fengyun satellite snow-cover images and IMS snow-cover products were validated with meteorological station observations for the 2010-2011 and 2011-2012 winter seasons. The influence of elevation and land-cover types on the accuracy of snow retrievals was also analyzed. The results showed that the combined use of FY-2D and FY-2E VISSR data reduced cloud obscuration by 30.47% compared to the MODIS products. The validation demonstrated that the accuracy of the final multi-sensor snow-cover images was 91.28%, which is similar to that for IMS snow-cover products. This work indicates that combined data from geostationaly satellites and passive microwave remote sensing monitored snow cover over China to a high level of accuracy. (C) 2014 Elsevier Inc. All rights reserved.

作者信息
通讯作者地址: Jiang, LM (通讯作者)
Beijing Normal Univ, Res Ctr Remote Sensing & GIS, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, Res Ctr Remote Sensing & GIS, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China
[ 3 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 4 ] Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
[ 5 ] Univ Maryland, Earth Sci Syst Interdisciplinary Ctr, College Pk, MD 20742 USA