肖志强等:Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product
被阅读 881 次
2016-05-30
Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product
作者:Xiao, ZQ (Xiao, Zhiqiang)[ 1 ] ; Wang, TT (Wang, Tongtong)[ 1 ] ; Liang, SL (Liang, Shunlin)[ 1,2 ] ; Sun, R (Sun, Rui)[ 1 ]
REMOTE SENSING
卷: 8  期: 4
文献号: 337
DOI: 10.3390/rs8040337
出版年: APR 2016
 
摘要
The fractional vegetation cover (FCover) is an essential biophysical variable and plays a critical role in the carbon cycle studies. Existing FCover products from satellite observations are spatially incomplete and temporally discontinuous, and also inaccurate for some vegetation types to meet the requirements of various applications. In this study, an operational method is proposed to calculate high-quality, accurate FCover from the Global LAnd Surface Satellite (GLASS) leaf area index (LAI) product to ensure physical consistency between LAI and FCover retrievals. As a result, a global FCover product (denoted by TRAGL) were generated from the GLASS LAI product from 2000 to present. With no missing values, the TRAGL FCover product is spatially complete. A comparison of the TRAGL FCover product with the Geoland2/BioPar version 1 (GEOV1) FCover product indicates that these FCover products exhibit similar spatial distribution pattern. However, there were relatively large discrepancies between these FCover products over equatorial rainforests, broadleaf crops in East-central United States, and needleleaf forests in Europe and Siberia. Temporal consistency analysis indicates that TRAGL FCover product has continuous trajectories. Direct validation with ground-based FCover estimates demonstrated that TRAGL FCover values were more accurate (RMSE = 0.0865, and R-2 = 0.8848) than GEOV1 (RMSE = 0.1541, and R-2 = 0.7621).
 
通讯作者地址: Xiao, ZQ (通讯作者)
Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA