Impact of Conifer Forest Litter on Microwave Emission at L-Band

Kurum, Mehmet; O'Neill, Peggy E.; Lang, Roger H.; Cosh, Michael H.; Joseph, A. T.; Jackson, Thomas J.

doi:10.1109/tgrs.2011.2166272

Cited by 26 publications

(22 citation statements)

References 45 publications

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“…At both sites, the Decagon 5TE sensors are installed at permanent network stations (Bircher et al, 2012a;Ikonen et al, 2016) providing data to the International Soil Moisture Network (ISMN, Dorigo et al, 2011) -a global in situ soil moisture database to support validation and improvement of satellite observations and land surface models. Meanwhile, ThetaProbes are used for hand-held measurement campaigns (e.g., Bircher et al, 2012b), a current method for spatial variation studies of soil water content at different scales (e.g., Baggaley et al, 2009;Lopez-Vicente et al, 2009) and thus, frequently applied in the scope of satellite validation (e.g., Cosh et al, 2005;Kurum et al, 2012).…”

Section: S Bircher Et Al: Soil Moisture Sensor Calibration For Orgamentioning

confidence: 99%

“…ε a can then be related to moisture content using the manufacturer's calibrations for mineral and organic substrates. The probe has been evaluated in different studies and calibration functions are already reported for a range of natural organic substrates (e.g., Kurum et al, 2012;Overduin et al, 2005;Yoshikawa et al, 2004), and artificial potting/compost substrates (e.g., Nemali et al, 2007;Kargas and Kerkides, 2008;Kang et al, 2010;Vaz et al, 2013). Major probe characteristics are listed in Table 3.…”

Section: Delta-t Thetaprobe Ml2xmentioning

confidence: 99%

“…A lot of attention was paid to proper application of the ThetaProbes: the four rods of the instrument were inserted vertically and pushed firmly into the substrate in order to assure good contact and avoid air gaps, and yet careful not to compress the material too much. This is common practice with this sensor type, in the case of organic material, for example, applied by Nemali et al (2007), Kargas and Kerkdis (2008), and Vaz et al (2013) in the laboratory as well as by Kurum et al (2012) in the field. In our case, three readings were taken at a given time step in order to check the repeatability of the measurements, while the mean was recorded each time.…”

Section: Laboratory Calibration Measurementsmentioning

confidence: 99%

“…In the case of the Decagon 5TE sensor (left column) this includes the calibration for an organic plant potting mix reported by Vaz et al (2013) for the same sensor type (orange line) as well as the following calibration laws for organic samples obtained from TDR measurements (blue and green lines): Pepin et al (1992), Roth et al (1992), Paquet et al (1993), Malicki et al (1996) using a bulk density of 0.1 g cm −3 , Schaap et al (1996), Kellner and Lundin (2001), Yoshikawa et al (2004) for living sphagnum, and Pumpanen and Ilvesniemi (2005). Concerning the ThetaProbe (right column panels), only functions derived for organic soil layers with the same sensor type were selected, namely those of Nemali et al (2007), Kurum et al (2012) for an OL layer using a bulk density of 0.1 g cm −3 , and Vaz et al (2013) for the relationship between mV output and moisture content (wine red, dark red, and orange lines in top row panels), and Yoshikawa et al (2004, living sphagnum) as well as Kargas and Kerkides (2008) for the relationship between ε a and moisture content (beige and yellow lines in bottom row panels), respectively. Manufacturer calibration curves are also included in the plots (continuous and dashed black lines in the case of curves for organic and mineral materials, respectively).…”

Section: Curve Fits For Organic Materialsmentioning

confidence: 99%

“…As practiced in our experimental setup, Nemali et al (2007), Kurum et al (2012), and Vaz et al (2013) also removed and reinserted the ThetaProbe after each measurement, while in the studies by Yoshikawa et al (2004) and Kargas and Kerkidis (2008) probes remained installed throughout the entire experiments. Certainly, a hand-held application with slightly changed sampling location each time results in increased data variability compared to permanently installed probes, the effect being more pronounced in organic substrate of complex structure compared to more homogeneously distributed mineral soils.…”

Section: Comparison Of Fitted Versus the Literature Calibrations For mentioning

confidence: 99%

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Soil moisture sensor calibration for organic soil surface layers

Bircher

Andreasen

Vuollet

et al. 2016

Geosci. Instrum. Method. Data Syst.

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Abstract. This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finnish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology (HOBE). For the Decagon 5TE sensor such a function is currently not reported in the literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified. For the Decagon 5TE, apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large specific surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger nonlinearity in the sensor response and signal saturation in the high-level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here-proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the hereproposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but prove to be of value for the acquisition of instantaneous large-scale soil moisture estimates.

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Section: S Bircher Et Al: Soil Moisture Sensor Calibration For Orgamentioning

confidence: 99%

Section: Delta-t Thetaprobe Ml2xmentioning

confidence: 99%

Section: Laboratory Calibration Measurementsmentioning

confidence: 99%

Section: Curve Fits For Organic Materialsmentioning

confidence: 99%

Section: Comparison Of Fitted Versus the Literature Calibrations For mentioning

confidence: 99%

See 3 more Smart Citations

Soil moisture sensor calibration for organic soil surface layers

Bircher

Andreasen

Vuollet

et al. 2016

Geosci. Instrum. Method. Data Syst.

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In situ characterization of forest litter using ground‐penetrating radar

André

Jonard

et al. 2016

JGR Biogeosciences

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Decomposing litter accumulated on the soil surface in forests plays a major role in several ecosystem processes; its detailed characterization is therefore essential for thorough understanding of ecosystem functioning. In addition, litter is known to affect remote sensing radar data over forested areas and their proper processing requires accurate quantification of litter scattering properties. In the present study, ultrawideband (0.8-2.2 GHz) ground-penetrating radar (GPR) data were collected in situ for a wide range of litter types to investigate the potential of the technique to reconstruct litter horizons in undisturbed natural conditions. Radar data were processed resorting to full-wave inversion. Good agreement was generally found between estimated and measured litter layer thicknesses, with root-mean-square error values around 1 cm for recently fallen litter (OL layer) and around 2 cm for fragmented litter in partial decomposition (OF layer) and total litter (OL + OF). Nevertheless, significant correlations between estimated and measured thicknesses were found for total litter only. Inaccuracies in the reconstruction of the individual litter horizons were mainly attributed to weak dielectric contrasts amongst litter layers, with absolute differences in relative dielectric permittivity values often lower than 2 between humus horizons, and to uncertainties in the ground truth values. Radar signal inversions also provided reliable estimates of litter electromagnetic properties, with average relative dielectric permittivity values around 2.9 and 6.3 for OL and OF litters, respectively. These results are encouraging for the use of GPR for noninvasive characterization and mapping of forest litter. Perspectives for the application of the technique in biogeosciences are discussed.

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