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  • 1
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, August, 2011, Vol.49(8), p.2863(13)
    Description: Accurate estimates of surface soil moisture are essential in many research fields, including agriculture, hydrology, and meteorology. The objective of this study was to evaluate two remote-sensing methods for mapping the soil moisture of a bare soil, namely, L-band radiometry using brightness temperature and ground-penetrating radar (GPR) using surface reflection inversion. Invasive time-domain reflectometry (TDR) measurements were used as a reference. A field experiment was performed in which these three methods were used to map soil moisture after controlled heterogeneous irrigation that ensured a wide range of water content. The heterogeneous irrigation pattern was reasonably well reproduced by both remote-sensing techniques. However, significant differences in the absolute moisture values retrieved were observed. This discrepancy was attributed to different sensing depths and areas and different sensitivities to soil surface roughness. For GPR, the effect of roughness was excluded by operating at low frequencies (0.2-0.8 GHz) that were not sensitive to the field surface roughness. The root mean square (rms) error between soil moisture measured by GPR and TDR was 0.038 m〈sup〉3〈/sup〉·m〈sup〉-3〈/sup〉. For the radiometer, the rms error decreased from 0.062 (horizontal polarization) and 0.054 (vertical polarization) to 0.020 m〈sup〉3〈/sup〉·m〈sup〉-3〈/sup〉 (both polarizations) after accounting for roughness using an empirical model that required calibration with reference TDR measurements. Monte Carlo simulations showed that around 20% of the reference data were required to obtain a good roughness calibration for the entire field. It was concluded that relatively accurate measurements were possible with both methods, although accounting for surface roughness was essential for radiometry.
    Keywords: Soil Moisture -- Research ; Radiometers -- Usage ; Ground Penetrating Radar -- Usage ; Surface Roughness -- Measurement ; Remote Sensing -- Usage
    ISSN: 0196-2892
    E-ISSN: 15580644
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  • 2
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, July 2014, Vol.52(7), pp.3947-3958
    Description: Ground-penetrating radar (GPR) uses the recording of electromagnetic waves and is increasingly applied for a wide range of applications. Traditionally, the main focus was on the analysis of the medium permittivity since estimates of the conductivity using the far-field approximation contain relatively large errors and cannot be interpreted quantitatively. Recently, a full-waveform inversion (FWI) scheme has been developed that is able to reliably estimate permittivity and conductivity values by analyzing reflected waves present in on-ground GPR data. It is based on a frequency-domain solution of Maxwell's equations including far, intermediate, and near fields assuming a 3-D subsurface. Here, we adapt the FWI scheme for on-ground GPR to invert the direct ground wave traveling through the shallow subsurface. Due to possible interference with the airwaves and other reflections, an automated time-domain filter needed to be included in the inversion. In addition to the obtained permittivity and conductivity values, also the wavelet center frequency and amplitude return valuable information that can be used for soil characterization. Combined geophysical measurements were carried out over a silty loam with significant variability in the soil texture. The obtained medium properties are consistent with Theta probe, electromagnetic resistivity tomography, and electromagnetic induction results and enable the formulation of an empirical relationship between soil texture and soil properties. The permittivities and conductivities increase with increasing clay and silt and decreasing skeleton content. Moreover, with increasing permittivities and conductivities, the wavelet center frequency decreases, whereas the wavelet amplitude increases, which is consistent with the radiation pattern and the antenna coupling characteristics.
    Keywords: Conductivity ; Permittivity ; Ground Penetrating Radar ; Soil ; Permittivity Measurement ; Electromagnetic Interference ; Optimization ; Antenna Radiation Patterns ; Conductivity ; Deconvolution ; Electromagnetic Measurements ; Frequency-Domain Analysis ; Ground-Penetrating Radar (Gpr) ; Permittivity ; Wavelets ; Engineering ; Physics
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 3
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, February 2014, Vol.52(2), pp.1489-1501
    Description: Knowledge about the surface soil water content is essential because it controls the surface water dynamics and land-atmosphere interaction. In high mountain areas in particular, soil surface water content controls infiltration and flood events. Although satellite-derived surface soil moisture data from passive microwave sensors are readily available for most regions globally, mountainous areas are often excluded from these data (or at least flagged as biased) due to the strong topographic influence on the retrieved signal. Even though a substantial volume of literature is available dealing with topographic effects on spaceborne brightness temperature, no systematic analysis has been reported. Therefore, we present a comprehensive analysis of topographic effects on brightness temperature at C-band using a two-step approach. First, a well-controlled field experiment is carried out using a mobile truck-mounted C-band radiometer to analyze the impact of geometric and adjacent effects on the radiometer signal. Additionally, a comprehensive radiative transfer model is developed accounting for both effects and tested on the ground-based data. Second, recorded Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) data over the Tibetan Plateau were used to analyze the error due to the impact of topography using the developed model. The results of the field experiment clearly show that the geometric effect of a single hill has a much larger impact on brightness temperature compared to the adjacent effect of multiple hills, whereby, due to the geometric effect, the bias is up to +20 K for horizontal and -13 K for vertical polarization. For the adjacent effect, the bias is less than 3 K for both polarizations. Additionally, the developed radio transfer model was able to reproduce both effects with high accuracy. For the AMSR-E data, the model shows that the brightness temperature recorded is biased in the same way as the ground-based measurements and that uncertainties induced by the wide existence of atypical mountain regions in the Tibetan Plateau will have a great impact on the retrieving error (maximum 30%). The largest impact on the retrieval error, on the other hand, is calculated for the soil moisture with a maximum relative error of 44%. The negligible impact can be attributed to false parameterization of the soil texture, soil surface temperature, and sky temperature. Finally, the overall absolute error in the estimated water content is quantified on average with 4%, whereby single pixels indicate a maximum absolute error of up to 16%. In conclusion, we show that recorded spaceborne brightness temperatures are highly biased by topographic effects in mountainous regions using a comprehensive radiative transfer model. Additionally, we suggest using this model to invert the effective surface emissivity of mountain areas for standard processing of higher level data products such as surface soil water content.
    Keywords: Advaned Microwave Scanning Radiometer-Earth Observing System (Amsr-E) ; Mountain Area ; Passive Microwave Remote Sensing ; Radiometer ; Topography ; Engineering ; Physics
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 4
    In: IEEE Transactions on Geoscience and Remote Sensing, 05/2011, Vol.49(5), pp.1649-1662
    Description: The antenna of a zero-offset off-ground ground-penetrating radar can be accurately modeled using a linear system of frequency-dependent complex scalar transfer functions under the assumption that the electric field measured by the antenna locally tends to a plane wave. First, we analyze to which extent this hypothesis holds as a function of the antenna height above a multilayered medium. Second, we compare different methods to estimate the antenna phase center, namely, 1) extrapolation of peak-to-peak reflection values in the time domain and 2) frequency-domain full-waveform inversion assuming both frequency-independent and -dependent phase centers. For that purpose, we performed radar measurements at different heights above a perfect electrical conductor. Two different horn antennas operating, respectively, in the frequency ranges 0.2-2.0 and 0.8-2.6 GHz were used and compared. In the limits of the antenna geometry, we observed that antenna modeling results were not significantly affected by the position of the phase center. This implies that the transfer function model inherently accounts for the phase-center positions. The results also showed that the antenna transfer function model is valid only when the antenna is not too close to the reflector, namely, the threshold above which it holds corresponds to the antenna size. The effect of the frequency dependence of the phase-center position was further tested for a two-layered sandy soil subject to different water contents. The results showed that the proposed antenna model avoids the need for phase-center determination for proximal soil characterization.
    Keywords: Geoscience ; Signal Processing and Analysis;
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 5
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, June 2015, Vol.53(6), pp.3095-3109
    Description: In this paper, we experimentally analyzed the feasibility of estimating soil hydraulic properties from 1.4 GHz radiometer and 0.8-2.6 GHz ground-penetrating radar (GPR) data. Radiometer and GPR measurements were performed above a sand box, which was subjected to a series of vertical water content profiles in hydrostatic equilibrium with a water table located at different depths. A coherent radiative transfer model was used to simulate brightness temperatures measured with the radiometer. GPR data were modeled using full-wave layered medium Green's functions and an intrinsic antenna representation. These forward models were inverted to optimally match the corresponding passive and active microwave data. This allowed us to reconstruct the water content profiles, and thereby estimate the sand water retention curve described using the van Genuchten model. Uncertainty of the estimated hydraulic parameters was quantified using the Bayesian-based DREAM algorithm. For both radiometer and GPR methods, the results were in close agreement with in situ time-domain reflectometry (TDR) estimates. Compared with radiometer and TDR, much smaller confidence intervals were obtained for GPR, which was attributed to its relatively large bandwidth of operation, including frequencies smaller than 1.4 GHz. These results offer valuable insights into future potential and emerging challenges in the development of joint analyses of passive and active remote sensing data to retrieve effective soil hydraulic properties.
    Keywords: Soil ; Ground Penetrating Radar ; Microwave Radiometry ; Soil Measurements ; L-Band ; Antenna Measurements ; Sea Measurements ; Bayesian Uncertainty ; Ground-Penetrating Radar (Gpr) ; Inverse Modeling ; Microwave Radiometry ; Soil Hydraulic Properties ; Engineering ; Physics
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 6
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, July 2016, Vol.54(7), pp.3878-3889
    Description: The objective of the NASA Soil Moisture Active Passive (SMAP) mission is to provide global measurements of soil moisture and freeze/thaw states. SMAP integrates L-band radar and radiometer instruments as a single observation system combining the respective strengths of active and passive remote sensing for enhanced soil moisture mapping. Airborne instruments are a key part of the SMAP validation program. Here, we present an airborne campaign in the Rur catchment, Germany, in which the passive L-band system Polarimetric L-band Multi-beam Radiometer and the active L-band system F-SAR of DLR were flown simultaneously on six dates in 2013. The flights covered the full heterogeneity of the area under investigation, i.e., the main land cover types and all experimental monitoring sites. Here, we used the obtained data sets as a test bed for the analysis of three active-passive fusion techniques: 1) estimation of soil moisture by passive sensor data and subsequent disaggregation by active sensor backscatter data; 2) disaggregation of passive microwave brightness temperature by active microwave backscatter and subsequent inversion to soil moisture; and 3) fusion of two single-source soil moisture products from radar and radiometer. Results indicate that the regression parameters β are dependent on the radar vegetation index. The best performance was obtained by the fusion of radiometer brightness temperatures and radar backscatter, which was able to reach the same accuracy as single-source coarse-scale radiometer soil moisture retrieval but on a higher spatial resolution.
    Keywords: Microwave Radiometry ; Soil Moisture ; L-Band ; Radar ; Soil Measurements ; Microwave Measurement ; Active-Passive Fusion ; L-Band Microwave ; Radar ; Radiometer ; Soil Moisture Active Passive (Smap) ; Soil Moisture ; Engineering ; Physics
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 7
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, 2016, Vol.54(7), p.3878(12)
    Keywords: Microwave Radiometers – Usage ; Synthetic Aperture Radar – Research ; Remote Sensing – Research
    ISSN: 0196-2892
    Source: Cengage Learning, Inc.
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  • 8
    In: IEEE Transactions on Geoscience and Remote Sensing, 03/2013, Vol.51(3), pp.1728-1743
    Description: The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite was launched in November 2009 and delivers now brightness temperature and soil moisture products over terrestrial areas on a regular three-day basis. In 2010, several airborne campaigns were conducted to validate the SMOS products with microwave emission radiometers at L-band (1.4 GHz). In this paper, we present results from measurements performed in the Rur and Erft catchments in May and June 2010. The measurement sites were situated in the very west of Germany close to the borders to Belgium and The Netherlands. We developed an approach to validate spatial and temporal SMOS brightness temperature products. An area-wide brightness temperature reference was generated by using an area-wide modeling of top soil moisture and soil temperature with the WaSiM-ETH model and radiative transfer calculation based on the L-band Microwave Emission of the Biosphere model. Measurements of the airborne L-band sensors EMIRAD and HUT-2D on-board a Skyvan aircraft as well as ground-based mobile measurements performed with the truck mounted JÜLBARA L-band radiometer were analyzed for calibration of the simulated brightness temperature reference. Radiative transfer parameters were estimated by a data assimilation approach. By this versatile reference data set, it is possible to validate the spaceborne brightness temperature and soil moisture data obtained from SMOS. However, comparisons with SMOS observations for the campaign period indicate severe differences between simulated and observed SMOS data.
    Keywords: Geoscience ; Signal Processing and Analysis;
    ISSN: 0196-2892
    E-ISSN: 1558-0644
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  • 9
    Language: English
    In: IEEE Transactions on Geoscience and Remote Sensing, October 2019, Vol.57(10), pp.7671-7681
    Description: Horizontally stratified media are commonly used to represent naturally occurring and man-made structures, such as soils, roads, and pavements, when probed by ground-penetrating radar (GPR). Electromagnetic (EM) wave scattering from such multilayered media is dependent on the roughness of the interfaces. In this paper, we developed a closed-form asymptotic EM model considering random rough layers based on the scalar Kirchhoff-tangent plane approximation (SKA) model that we combined with planar multilayered media Green's functions. In order to validate our extended SKA model, we conducted simulations using a numerical EM solver based on the finite-difference time-domain (FDTD) method. We modeled a medium with three layers-a base layer of perfect electric conductor (PEC) overlaid by two layers of different materials with rough interfaces. The reflections at the first and at the second interface were both well reproduced by the SKA model for each roughness condition. For the reflection at the PEC surface, the extended SKA model slightly overestimated the reflection, and this overestimation increased with the roughness amplitude. Good agreement was also obtained between the FDTD simulation input values and the inverted root mean square (rms) height estimates of the top interface, while the inverted rms heights of the second interface were slightly overestimated. The accuracy and the performances of our asymptotic forward model demonstrate the promising perspectives for simulating rough multilayered media and, hence, for the full waveform inversion of GPR data to noninvasively characterize soils and materials.
    Keywords: Media ; Scattering ; Ground Penetrating Radar ; Rough Surfaces ; Surface Roughness ; Sea Surface ; Green'S Function Methods ; Finite-Difference Time-Domain (Fdtd) ; Gprmax ; Green’s Function ; Ground-Penetrating Radar (Gpr) ; Kirchhoff-Tangent Plane Approximation (Ka) ; Model Inversion ; Multilayered Media ; Radar ; Rough Interfaces ; Scattering ; Engineering ; Physics
    ISSN: 0196-2892
    E-ISSN: 1558-0644
    Source: IEEE Conference Publications
    Source: IEEE Journals & Magazines 
    Source: IEEE Xplore
    Source: IEEE Journals & Magazines
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