张涛等:Estimating Mixed-Pixel Component Soil Moisture Contents Using Biangular Observations From the HiWATER Airborne Passive Microwave Data
被阅读 840 次
2015-10-20
Estimating Mixed-Pixel Component Soil Moisture Contents Using Biangular Observations From the HiWATER Airborne Passive Microwave Data
作者:Zhang, T (Zhang, Tao)[ 1,2 ] ; Jiang, LM (Jiang, Lingmei)[ 1,2 ] ; Chai, LN (Chai, Linna)[ 1,2 ] ; Zhao, TJ (Zhao, Tianjie)[ 3 ] ; Wang, Q (Wang, Qi)[ 1,2 ]
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷: 12  期: 5  页: 1146-1150
DOI: 10.1109/LGRS.2015.2388572
出版年: MAY 2015
 
摘要
Determination of the component soil moisture content within one pixel using passive microwave remote sensing data is important for predicting soil moisture contents in ecohydrological research within the Heihe River Basin. The Heihe Watershed Allied Telemetry Experimental Research was conducted in 2012 to address this issue. An airborne polarimetric L-band microwave radiometer (PLMR) instrument was used to measure surface emissions over the middle stream of the Heihe River Basin. Extensive ground-based soil moisture content and temperature data were obtained during the PLMR flights. In this letter, an algorithm for estimating the component soil moisture content was developed using biangular PLMR observations. Based on a theoretical analysis, the linear relationship between the soil emissivities at two different incidence angles was obtained. Therefore, the component soil moisture could be derived based on the tau-omega model. In addition, the component soil moisture contents determined over the bare surface were lower than those over the vegetated surface. The root-mean-square errors between the calculated soil moisture contents and the measured soil moisture contents over the bare and vegetated surfaces were 0.050 and 0.051 cm(3)/cm(3), respectively. Overall, the results indicate that the component soil moisture contents can be estimated using biangular observations from airborne radiometer data.
 
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, Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China