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  • 1
    Language: English
    In: Remote Sensing, 01 October 2018, Vol.10(10), p.1637
    Description: L-band radiometer measurements were performed at the Selhausen remote sensing field laboratory (Germany) over the entire growing season of a winter wheat stand. L-band microwave observations were collected over two different footprints within a homogenous winter wheat stand in order to disentangle the emissions originating from the soil and from the vegetation. Based on brightness temperature (TB) measurements performed over an area consisting of a soil surface covered by a reflector (i.e., to block the radiation from the soil surface), vegetation optical depth (τ) information was retrieved using the tau-omega (τ-ω) radiative transfer model. The retrieved τ appeared to be clearly polarization dependent, with lower values for horizontal (H) and higher values for vertical (V) polarization. Additionally, a strong dependency of τ on incidence angle for the V polarization was observed. Furthermore, τ indicated a bell-shaped temporal evolution, with lowest values during the tillering and senescence stages, and highest values during flowering of the wheat plants. The latter corresponded to the highest amounts of vegetation water content (VWC) and largest leaf area index (LAI). To show that the time, polarization, and angle dependence is also highly dependent on the observed vegetation species, white mustard was grown during a short experiment, and radiometer measurements were performed using the same experimental setup. These results showed that the mustard canopy is more isotropic compared to the wheat vegetation (i.e., the τ parameter is less dependent on incidence angle and polarization). In a next step, the relationship between τ and in situ measured vegetation properties (VWC, LAI, total of aboveground vegetation biomass, and vegetation height) was investigated, showing a strong correlation between τ over the entire growing season and the VWC as well as between τ and LAI. Finally, the soil moisture was retrieved from TB observations over a second plot without a reflector on the ground. The retrievals were significantly improved compared to in situ measurements by using the time, polarization, and angle dependent τ as a priori information. This improvement can be explained by the better representation of the vegetation layer effect on the measured TB.
    Keywords: Microwave Remote Sensing ; Vegetation Optical Depth ; Soil Moisture ; Winter Wheat ; Smos ; Smap ; Tower-Based Experiment ; Inverse Modeling ; Geography
    E-ISSN: 2072-4292
    Source: Directory of Open Access Journals (DOAJ)
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  • 2
    Language: English
    In: Remote Sensing, 01 September 2015, Vol.7(9), pp.12041-12056
    Description: We tested an off-ground ground-penetrating radar (GPR) system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.
    Keywords: Ground-Penetrating Radar ; Freeze-Thaw Cycles ; Seasonal Snow Cover ; Inversion ; Geography
    E-ISSN: 2072-4292
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  • 3
    Language: English
    In: Remote Sensing, 01 March 2015, Vol.7(3), pp.2808-2831
    Description: Leaf Area Index (LAI) is an important variable for numerous processes in various disciplines of bio- and geosciences. In situ measurements are the most accurate source of LAI among the LAI measuring methods, but the in situ measurements have the limitation of being labor intensive and site specific. For spatial-explicit applications (from regional to continental scales), satellite remote sensing is a promising source for obtaining LAI with different spatial resolutions. However, satellite-derived LAI measurements using empirical models require calibration and validation with the in situ measurements. In this study, we attempted to validate a direct LAI retrieval method from remotely sensed images (RapidEye) with in situ LAI (LAIdestr). Remote sensing LAI (LAIrapideye) were derived using different vegetation indices, namely SAVI (Soil Adjusted Vegetation Index) and NDVI (Normalized Difference Vegetation Index). Additionally, applicability of the newly available red-edge band (RE) was also analyzed through Normalized Difference Red-Edge index (NDRE) and Soil Adjusted Red-Edge index (SARE). The LAIrapideye obtained from vegetation indices with red-edge band showed better correlation with LAIdestr (r = 0.88 and Root Mean Square Devation, RMSD = 1.01 & 0.92). This study also investigated the need to apply radiometric/atmospheric correction methods to the time-series of RapidEye Level 3A data prior to LAI estimation. Analysis of the the RapidEye Level 3A data set showed that application of the radiometric/atmospheric correction did not improve correlation of the estimated LAI with in situ LAI.
    Keywords: Leaf Area Index ; Red-Edge Band ; Rapideye ; Atmospheric Correction ; Validation ; Time-Series ; Geography
    E-ISSN: 2072-4292
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  • 4
    Language: English
    In: Remote Sensing, 01 March 2018, Vol.10(3), p.427
    Description: Several studies currently strive to improve the spatial resolution of coarse scale high temporal resolution global soil moisture products of SMOS, SMAP, and ASCAT. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. We use this information for the prediction of the sub-grid soil moisture variability for each SMOS, SMAP, and ASCAT grid cell. The approach is based on a method that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean, available at https://doi.org/10.1594/PANGAEA.878889. The resulting data set helps identify adequate regions to validate coarse scale soil moisture products by providing a measure of representativeness of small-scale measurements for the coarse grid cell. Moreover, it contains important information for downscaling coarse soil moisture observations of the SMOS, SMAP, and ASCAT missions. In this study, we present a simple application of the estimated sub-grid soil moisture heterogeneity scaling down SMAP soil moisture to 1 km resolution. Validation results in the TERENO and REMEDHUS soil moisture monitoring networks in Germany and Spain, respectively, indicate a similar or slightly improved accuracy for downscaled and original SMAP soil moisture in the time domain for the year 2016, but with a much higher spatial resolution.
    Keywords: Smos ; Smap ; Ascat ; Soilgrids ; Soil Moisture Variability ; Scaling ; Soil Texture ; Geography
    E-ISSN: 2072-4292
    Source: Directory of Open Access Journals (DOAJ)
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  • 5
    Language: English
    In: Remote Sensing, 01 January 2017, Vol.9(2), p.103
    Description: The scale difference between point in situ soil moisture measurements and low resolution satellite products limits the quality of any validation efforts in heterogeneous regions. Cosmic Ray Neutron Probes (CRNP) could be an option to fill the scale gap between both systems, as they provide area-average soil moisture within a 150–250 m radius footprint. In this study, we evaluate differences and similarities between CRNP observations, and surface soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), the METOP-A/B Advanced Scatterometer (ASCAT), the Soil Moisture Active and Passive (SMAP), the Soil Moisture and Ocean Salinity (SMOS), as well as simulations from the Global Land Data Assimilation System Version 2 (GLDAS2). Six CRNPs located on five continents have been selected as test sites: the Rur catchment in Germany, the COSMOS sites in Arizona and California (USA), and Kenya, one CosmOz site in New South Wales (Australia), and a site in Karnataka (India). Standard validation scores as well as the Triple Collocation (TC) method identified SMAP to provide a high accuracy soil moisture product with low noise or uncertainties as compared to CRNPs. The potential of CRNPs for satellite soil moisture validation has been proven; however, biomass correction methods should be implemented to improve its application in regions with large vegetation dynamics.
    Keywords: Cosmic-Ray Neutron Probe ; Smos ; Smap ; Ascat ; Amsr2 ; Gldas2 ; Cosmos ; Cosmoz ; Soil Moisture ; Soil Water Content ; Validation ; Triple Collocation ; Geography
    E-ISSN: 2072-4292
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  • 6
    Language: English
    In: Remote Sensing, 16 February 2018
    Keywords: Engineering Sciences ; Electromagnetism ; Environmental Sciences ; Global Changes ; Environmental Sciences ; Environmental Engineering ; Environmental Sciences ; Geography
    ISSN: 2072-4292
    E-ISSN: 2072-4292
    Source: Hyper Article en Ligne (CCSd)
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  • 7
    Language: English
    In: Remote Sensing, 01 February 2018, Vol.10(2), p.304
    Description: Organic soils play a key role in global warming because they store large amount of soil carbon which might be degraded with changing soil temperatures or soil water contents. There is thus a strong need to monitor these soils and, in particular, their hydrological characteristics using, for instance, space-borne L-band brightness temperature observations. However, there are still open issues with respect to soil moisture retrieval techniques over organic soils. In view of this, organic soil blocks with their vegetation cover were collected from a heathland in the Skjern River catchment in western Denmark and then transported to a remote sensing field laboratory in Germany where their structure was reconstituted. The controlled conditions at this field laboratory made it possible to perform tower-based L-band radiometer measurements of the soils over a period of two months. Brightness temperature data were inverted using a radiative transfer (RT) model for estimating the time variations in the soil dielectric permittivity and the vegetation optical depth. In addition, the effective vegetation scattering albedo parameter of the RT model was retrieved based on a two-step inversion approach. The remote estimations of the dielectric permittivity were compared to in situ measurements. The results indicated that the radiometer-derived dielectric permittivities were significantly correlated with the in situ measurements, but their values were systematically lower compared to the in situ ones. This could be explained by the difference between the operating frequency of the L-band radiometer (1.4 GHz) and that of the in situ sensors (70 MHz). The effective vegetation scattering albedo parameter was found to be polarization dependent. While the scattering effect within the vegetation could be neglected at horizontal polarization, it was found to be important at vertical polarization. The vegetation optical depth estimated values over time oscillated between 0.10 and 0.19 with a mean value of 0.13. This study provides further insights into the characterization of the L-band brightness temperature signatures of organic soil surface layers and, in particular, into the parametrization of the RT model for these specific soils. Therefore, the results of this study are expected to improve the performance of space-borne remote sensing soil moisture products over areas dominated by organic soils.
    Keywords: L-Band Radiometry ; Microwave Remote Sensing ; Organic Soil ; Soil Dielectric Permittivity ; Soil Moisture ; Inverse Modelling ; Tower-Based Experiment ; Geography
    E-ISSN: 2072-4292
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  • 8
    Language: English
    In: Remote Sensing, 01 October 2019, Vol.11(20), p.2353
    Description: A considerable amount of water is stored in vegetation, especially in regions with high precipitation rates. Knowledge of the vegetation water status is essential to monitor changes in ecosystem health and to assess the vegetation influence...
    Keywords: Gravimetric Vegetation Water Content ; Vegetation Volume Fraction ; Vegetation Optical Depth ; Winter Wheat ; Smos ; Smap ; L-Band ; Geography
    E-ISSN: 2072-4292
    Source: Directory of Open Access Journals (DOAJ)
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  • 9
    Language: English
    In: Remote Sensing, 01 April 2019, Vol.11(7), p.828
    Description: Accurate characterization of forest litter is of high interest for land surface modeling and for interpreting remote sensing observations over forested areas. Due to the large spatial heterogeneity of forest litter, scattering from litter layers has to be considered when sensed using microwave techniques. Here, we apply a full-waveform radar model combined with a surface roughness model to ultrawideband ground-penetrating radar (GPR) data acquired above forest litter during controlled and in situ experiments. For both experiments, the proposed modeling approach successfully described the radar data, with improvements compared to a previous study in which roughness was not directly accounted for. Inversion of the GPR data also provided reliable estimates of the relative dielectric permittivity of the recently fallen litter (OL layer) and of the fragmented litter in partial decomposition (OF layer) with, respectively, averaged values of 1.35 and 3.8 for the controlled experiment and of 3.9 and 7.5 for the in situ experiment. These results show the promising potentialities of GPR for efficient and non-invasive characterization of forest organic layers.
    Keywords: Forest Litter ; Frequency Dependence ; Ground-Penetrating Radar (Gpr) ; Roughness ; Scattering ; Geography
    E-ISSN: 2072-4292
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