崔倩等:An Approach for Monitoring Global Vegetation Based on Multiangular Observations From SMOS
被阅读 873 次
2015-10-23
An Approach for Monitoring Global Vegetation Based on Multiangular Observations From SMOS
作者:Cui, Q (Cui, Qian)[ 1 ] ; Shi, JC (Shi, Jiancheng)[ 2,3,4 ] ; Du, JY (Du, Jinyang)[ 1 ] ; Zhao, TJ (Zhao, Tianjie)[ 2,3,4 ] ; Xiong, C (Xiong, Chuan)[ 1 ]
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷: 8  期: 2  页: 604-616
DOI: 10.1109/JSTARS.2015.2388698
出版年: FEB 2015
 
摘要
Vegetation monitoring is important for the study of the global carbon cycle and ecosystem. The soil moisture and ocean salinity (SMOS) mission that launched in 2009 is the first operational L-band passive microwave spaceborne sensor using synthetic aperture techniques; the sensor provides global L-band multiangular observations. In this study, based on the commonly used zero-order radiative transfer model (omega - tau model), we developed an approach for retrieving vegetation optical depth (VOD) using only SMOS H-polarized multiangular measurements. This was done by minimizing the soil signal and separating the vegetation signal from the multiangular brightness temperature. The uniqueness of this approach is that the angular feature of soil emission is used and that the VOD is retrieved directly from the H-polarized multiangular brightness temperature without any field correction or auxiliary soil or vegetation data. This approach is first validated by theoretical modeling and experimental data. The results demonstrate that VOD can be reliably estimated using this approach. The retrieved VOD is then compared with above-ground biomass, which shows strong correlation. Global mean VOD for the years 2010-2011 generally shows a clear global pattern and corresponds well to the land cover types. The VOD of nine representative regions that are homogeneously covered with different vegetation types from 2010 to 2011 is compared with normalized difference vegetation index (NDVI). The results indicate that the VOD can generally reveal vegetation seasonal changes and can provide unique information for vegetation monitoring.
 
通讯作者地址: Cui, Q (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth RADI, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 3 ] Beijing Normal Univ, Beijing 100101, Peoples R China
[ 4 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China