Estimates of long term surface soil moisture in the midwestern US derived from satellite microwave observations

被引:0
|
作者
Owe, M [1 ]
de Jeu, R [1 ]
Van de Griend, A [1 ]
机构
[1] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
关键词
remote sensing; microwave; SMMR; soil moisture; vegetation indices;
D O I
10.1117/12.373100
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
A database of long-term soil moisture was compared to satellite microwave observations over a test site in the Midwestern United States. Ground measurements of average volumetric surface soil moisture in the top ten cm were made several times per month at 19 locations throughout the state of Illinois. Nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. At 6.6 GHz, the instrument provides a spatial resolution of approximately 150 ion and a temporal frequency over the test area of about 3 nighttime orbits per week Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Because the time of satellite coverage does not always coincide with the ground measurements of sail moisture, the existing ground data were used to calibrate a water balance for the top TO cm surface layer in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area average soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface sail moisture at global scales. Real time estimates should improve weather and climate modelling: efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.
引用
收藏
页码:16 / 23
页数:8
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