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@ARTICLE{Altdorff:203399,
author = {Altdorff, D. and Bechtold, M. and van der Kruk, J. and
Vereecken, H. and Huisman, J. A.},
title = {{M}apping peat layer properties with multi-coil offset
electromagnetic induction and laser scanning elevation data},
journal = {Geoderma},
volume = {261},
issn = {0016-7061},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2015-05342},
pages = {178 - 189},
year = {2016},
abstract = {Peatlands store large amounts of soil organic carbon (SOC).
Depending on their present condition, they act as a source
or sink of carbon dioxide. Therefore, peatlands are highly
relevant for climate change investigations and there is
considerable interest to assess spatial heterogeneity of
peat soil properties in order to assess the total amount of
stored carbon. However, reliable information about peat
properties remains difficult to obtain at the field scale. A
potential way to acquire this information is the indirect
mapping of easily recordable physical variables that
correlate with peat properties, such as the apparent
electrical conductivity (ECa). In this study, we aim to
explore the potential of multi-coil offset electromagnetic
induction (EMI) measurements to provide spatial estimates of
SOC content, bulk density, and SOC stock for a highly
variable and disturbed peatland relict (~ 35 ha) with a
remaining peat layer thickness of less than 1 m. EMI
measurements comprised six integral depths that varied from
0–0.25 to 0–1.80 m. In combination with ancillary
laser-scanning elevation data, a multiple linear regression
model was calibrated to reference data from 34 soil cores
that were used to calculate integral properties of the upper
0.25, 0.5, and 1 m layer, as well as for the total peat
layer. Leave-one-out cross-validation for the different
depth ranges resulted in a root mean square error of
prediction (RMSEP) between 1.36 and $5.16\%$ for SOC
content, between 0.108 and 0.183 g cm− 3 for bulk density,
and between 3.56 and 9.73 kg m− 2 for SOC stocks, which
corresponds to roughly $15\%,$ $10\%,$ and $20\%$ of the
total field variability, respectively. The selection of
explanatory variables in the regression models showed that
the EMI data were important for accurate model predictions,
while the topography-based variables mainly acted as noise
suppressors. The accuracy of the SOC content estimates
roughly equalled the quality of SOC content predictions
obtained in previous field applications of the visible-near
infrared technique (vis-NIR). The spatial variation of the
predicted peat layer properties showed similarities to the
former land use distribution. Overall, it was concluded that
EMI measurements offer a useful alternative to the
established vis-NIR method for SOC content mapping in
carbon-rich soils.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {255 - Terrestrial Systems: From Observation to Prediction
(POF3-255)},
pid = {G:(DE-HGF)POF3-255},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000362130900018},
doi = {10.1016/j.geoderma.2015.07.015},
url = {https://juser.fz-juelich.de/record/203399},
}