王功学等:Fractional Snow Cover Mapping from FY-2 VISSR Imagery of China
被阅读 207 次
2017-12-11
Fractional Snow Cover Mapping from FY-2 VISSR Imagery of China 
作者:Wang, GX (Wang, Gongxue)[ 1 ] ; Jiang, LM (Jiang, Lingmei)[ 1 ] ; Wu, SL (Wu, Shengli)[ 2 ] ; Shi, JC (Shi, Jiancheng)[ 3 ] ; Hao, SR (Hao, Shirui)[ 1 ] ; Liu, XJ (Liu, Xiaojing)[ 1 ]  
REMOTE SENSING 
卷: 9 
期: 10 
文献号: 983 
DOI: 10.3390/rs9100983 
出版年: OCT 2017 
 
摘要
Daily fractional snow cover (FSC) products derived from optical sensors onboard low Earth orbit (LEO) satellites are often discontinuous, primarily due to prevalent cloud cover. To map the daily cloud-reduced FSC over China, we utilized clear-sky multichannel observations from the first-generation Chinese geostationary orbit (GEO) satellites (namely, the FY-2 series) by taking advantage of their high temporal resolution. The method proposed in this study combines a newly developed binary snow cover detection algorithm designed for the Visible and Infrared Spin Scan Radiometer (VISSR) onboard FY-2F with a simple linear spectral mixture technique applied to the visible (VIS) band. This method relies upon full snow cover and snow-free end-members to estimate the daily FSC. The FY-2E/F VISSR FSC maps of China were compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) FSC data based on the multiple end-member spectral mixture analysis (MESMA), and with Landsat-8 Operational Land Imager (OLI) FSC maps based on the SNOWMAP approach. The FY-2E/F VISSR FSC maps, which demonstrate a lower cloud coverage, exhibit the root mean squared errors (RMSEs) of 0.20/0.19 compared with the MODIS FSC data. When validated against the Landsat-8 OLI FSC data, the FY-2E/F VISSR FSC maps, which display overall accuracies that can reach 0.92, have an RMSE of 0.18-0.29 with R-2 values ranging from 0.46 to 0.80.
 
通讯作者地址: Jiang, LM (通讯作者)
 Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:  
 [ 1 ] Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
 [ 2 ] China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
 [ 3 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China