% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Minet:21352,
author = {Minet, J. and Bogaert, P. and Vanclooster, M. and Lambot,
S.},
title = {{V}alidation of ground penetrating radar full-waveform
inversion for field scale soil moisture mapping},
journal = {Journal of hydrology},
volume = {424-425},
issn = {0022-1694},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {PreJuSER-21352},
pages = {112 - 123},
year = {2012},
note = {We acknowledge Guido Rentmeesters for the GPR platform
construction. The research presented in this paper was
funded by the Belgian Science Policy Office in the frame of
the Stereo II programme - project SR/00/100 (HYDRASENS), the
DIGISOIL project financed by the European Commission under
the 7th Framework Programme for Research and Technological
Development, Area "Environment", Activity 6.3 "Environmental
Technologies", and the Fonds de la Recherche Scientifique
(FNRS), Belgium.},
abstract = {Ground penetrating radar (GPR) is an efficient method for
soil moisture mapping at the field scale, bridging the scale
gap between small-scale invasive sensors and large-scale
remote sensing instruments. Nevertheless, commonly-used GPR
approaches for soil moisture characterization suffer from
several limitations and the determination of the
uncertainties in GPR soil moisture sensing has been poorly
addressed. Herein, we used a proximal GPR method based on
full-waveform inversion of ultra-wideband radar data for
mapping soil moisture and we evaluated uncertainties in the
soil moisture maps by three methods. First, GPR-derived soil
moisture uncertainties were computed from GPR data
inversions, according to measurements and modeling errors,
and to the sensitivity of the electromagnetic model to soil
moisture. Second, the repeatability of soil moisture mapping
was evaluated. Third, GPR-derived soil moisture was compared
with ground-truth measurements (soil core sampling). The
proposed GPR method appeared to be highly precise and
accurate, with a spatially averaged GPR inversion
uncertainty of 0.0039 m(3) m(-3), a repetition uncertainty
of 0.0169 m(3) m(-3), and an uncertainty of 0.0233 m(3)
m(-3) when compared with ground-truth measurements. These
uncertainties were mapped and appeared to be related to some
local model inadequacies and to small-scale variability of
soil moisture. In a soil moisture mapping framework, the
interpolation was found to be the main source of the
observed uncertainties. The proposed GPR method was proven
to be largely reliable in terms of accuracy and precision
and appeared to be highly efficient for soil moisture
mapping at the field scale. (C) 2012 Elsevier B.V. All
rights reserved.},
keywords = {J (WoSType)},
cin = {IBG-3},
ddc = {690},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {Terrestrische Umwelt},
pid = {G:(DE-Juel1)FUEK407},
shelfmark = {Engineering, Civil / Geosciences, Multidisciplinary / Water
Resources},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000301326600009},
doi = {10.1016/j.jhydrol.2011.12.034},
url = {https://juser.fz-juelich.de/record/21352},
}