李云青等:Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation
被阅读 1068 次
2016-01-08
Effective vegetation optical depth retrieval using microwave vegetation indices from WindSat data for short vegetation
作者:Li, YQ (Li, Yunqing)[ 1,2 ] ; Shi, JC (Shi, Jiancheng)[ 1,3 ] ; Zhao, TJ (Zhao, Tianjie)[ 1,3 ]
JOURNAL OF APPLIED REMOTE SENSING
卷: 9
文献号: 096003
DOI: 10.1117/1.JRS.9.096003
出版年: OCT 6 2015
 
摘要
Vegetation optical depth (VOD) and effective vegetation optical depth (EVOD) are key factors for estimating soil moisture and vegetation parameters. Microwave vegetation indices (MVIs, including A and B parameters) have been recently developed for short-vegetation covered surfaces. The MVIs parameter B (MVIs_B) is mainly related to vegetation conditions, which makes it provide a potential way of EVOD retrieval. A theoretical expression deriving EVOD was deduced using MVIs_B from WindSat data. Global patterns of EVOD were analyzed subsequently. It has been shown that EVOD retrieved from MVIs performed a consistent global pattern and seasonal variation with normalized difference vegetation index. Time-series data from the Central Tibetan Plateau Soil Moisture/Temperature Monitoring Network, which is grassland dominated, was selected for temporal analysis. It was found that the temporal EVOD from WindSat MVIs can capture the growth trend of vegetation. Comparisons between EVOD estimations from MVIs and a radiative transfer model were also performed over this network. It was found that EVOD from the two methods exhibited comparable values and similar trends. MVIs_B-derived EVOD can be obtained without any other auxiliary data and has great potential in land-surface parameter retrieval over short-vegetation covered areas. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
 
通讯作者地址: Shi, JC (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, CAS Olymp S&T Pk 20 Da Tun Rd,POB 9718, 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 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 3 ] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China