Summary and Future Chances - GNSS Remote Sensing: Theory, Methods and Applications - page 259

12.1.2 Ocean Sensing

In the last few years, several experiments were carried out and numerous
advancements have been made. For example, the National Oceanic and Atmospheric
Administration (NOAA) Hurricane Hunter research aircraft carrying a GPS
reflectometry instrument flew into Hurricane Michael off the South Carolina coast
in October 2000 (Katzberg et al. 2001 ). The first GPS signals reflected from the
sea surface inside tropical cyclones were analyzed and the wind speed results were
obtained (Katzberg et al. 2001 ). UK-DMC carried a GPS reflectometry experiment
as a secondary payload, from which geophysical parameters of the Earth surface
were successfully inferred, e.g., sea surface roughness (Gleason et al. 2005 ). Good
altimetry accuracy results have been obtained in very calm sea states with GPS
reflected signals (Gleason et al. 2010 ). Currently, the GPS reflected signals from
the ocean surface can be used to make altimetric sea surface height measurements
with the achievable accuracy an active topic of research (Martin-Neira et al. 2001 ;
Katzberg and Dunion 2009 ). Good examples of ocean roughness and wind sensing
using GPS signals have been retrieved by Armatys et al. ( 2000 ) and Cardellach
and Ruis ( 2007 ). However, further research is needed in detailed analysis of
the electromagnetic field scattering theory, power and Delay-Doppler parameter
retrieval methods (Lowe et al. 2002 ) and characterizing the L-band surface slopes'
probability density function.

12.1.3 Hydrology Sensing

The power level of the GPS reflected signal from the land contains information about
the soil moisture, dielectric constant, surface roughness, and possible vegetative
cover of the reflecting surface (Masters 2004 ). Some experiments using GPS
reflected signals have made estimates of the soil moisture. For example, Katzberg
et al. ( 2006 ) obtained the soil reflectivity and dielectric constant using a GPS
reflectometer installed on an HC130 aircraft during the Soil Moisture Experiment
2002 (SMEX02) near Ames, Iowa, which were consistent with results found for
other microwave techniques operating at L-band. Simulations have been performed
by Ferrazzoli et al. ( 2010 ), which have opened up the possibility of sensing forest
biomass using GNSS reflections. In addition, the multi-path from ground GPS
networks is possibly related to the near-surface soil moisture. Larson et al. ( 2008a , b )
found nearly consistent fluctuations in near-surface soil moisture from the ground
GPS multi-path, comparable with soil moisture fluctuations in the top 5 cm of
soil measured from conventional sensors. However, GPS multipath signals are very
complex due to various factors, e.g., vegetable, foliage, and glass debris. To infer
the soil moisture parameters from ground GPS multipath, it is necessary to further
remove the other factors' effects.