1,720,966 research outputs found
Airborne SAR polarimetric decompositions for soil moisture retrieval
No full textSoil moisture is one of the key parameters needed to study the hydrological properties of the ground, playing an important role in many land applications such as agricultural management and flooding risk assessment. In this context, polarimetric SAR decompositions can separate individual scattering mechanisms (surface, double-bounce, volume), giving the possibility to study how soil moisture changes not only over bare soils but also over agricultural areas covered by different crops during the year. In this work, the sensitivity to soil moisture of different scattering mechanisms discriminated by an airborne polarimetric radar operating at L-band has been investigated. The main objective was assessing the capability of a fully polarimetric system to distinguish the change in soil moisture under different vegetation covers. We used data collected by the NASA UAVSAR airborne radar flying over the Yucatan Lake site in Louisiana. Six overflights were analysed, and six regions of interest characterized by different vegetation covers were selected. The NDVI derived from the Sentinel-2 satellite and data from a nearby precipitation gauge were used as an indication of the vegetation growing stage and moisture changes. The temporal trends of the magnitude of different scattering mechanisms, according to the Freeman-Durden and Nonnegative Eigenvalue decompositions, of NDVI and rain rate are analysed and discussed with reference to the theoretical expectations. The Freeman-Durden physical decomposition exhibited quite a reasonable behaviour, with the co-polarization ratio of the surface and double bounce components being particular effective for the forest plots to identify change in moisture
Sensitivity to soil Moisture over an agricultural area by exploiting a model-based polarimetric decomposition
No full textIn this work, the sensitivity to soil moisture of different scattering mechanisms observed by an airborne polarimetric radar operating at L-band has been investigated. The main objective was assessing the capability of a fully polarimetric radar system to disentangle the change in soil moisture under different vegetation covers. We used polarimetric data collected by the NASA UA VSAR airborne radar flying over the Yucatan Lake site in Louisiana. Six overflights were analysed, and six regions of interest characterized by different vegetation covers were selected. The temporal trends of the magnitude of different scattering mechanisms, according to the Freeman-Durden and the Nonnegative Eigenvalue decompositions, as well as of the NDVI and a nearby precipitation gauge are analysed and discussed with reference to the theoretical expectations
Sensitivity of polarimetric SAR decompositions to soil moisture and vegetation over three agricultural sites across a latitudinal gradient
Full text linkThe goal of this work is to assess the impact of polari-metric SAR decompositions for soil moisture retrieval, and identify the decomposition that performs best for varying vegetation covers and soil conditions. Seven polarimetric decompositions are applied to three L-band radar time-series to evaluate their relative performances for future inclusion within a soil moisture retrieval scheme. Three agricultural sites with different soil and vegetation characteristics are selected across a latitudinal gradient in America. Two time-series of quad-polarimetric data collected by the NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR)airborne instrument are considered for the first two sites, while quad-polarimetric images acquired by the SAOCOM-1A mission are examined for the third site. We extract a set of radar polarimetric descriptors, including the backscattering coefficients, to analyze their sensitivity to soil moisture and vegetation through correlation analysis. We also apply a simple linear regression model to each crop type and site for estimating soil moisture (or Soil Water Index)by alternatively considering a combination of the decomposition powers and of the total backscattering coefficients (gamma(0),sigma(0)). The linear regression analysis shows that the estimates are generally comparable in terms of linear correlation and root mean square error. Results also reveal that the sensitivity of polarimetric de-composition descriptors to soil moisture and vegetation parameters depend both on crop type and area of interest, without significant differences among the various decompositions tested in this study
Sensitivity to soil moisture by applying a model-based polarimetric decomposition to a time-series of airborne radar L-band data over an agricultural area
No full textIn this paper, the sensitivity to soil moisture variations over an agricultural area characterized by different vegetation covers has been investigated. The objectives of the study were identifying the correlation of one or more polarimetric parameters with soil moisture changes over time. In this respect, we assessed the possibility to separate three individual scattering mechanisms (i.e., surface, double-bounce, volume) offered by radar polarimetry. We apply a model-based polarimetric decomposition to a time-series of high-resolution SAR data collected at L-band by the NASA/JPL UAVSAR airborne radar over the Yucatan Lake region in Louisiana, USA. Thirteen flights were considered and five regions of interest characterized by different surface properties and vegetation covers were selected. The temporal evolution of different polarimetric parameters, obtained by applying the Freeman-Durden decomposition, is reported and discussed. The polarimetric features were compared not only to the NDVI variations derived from Sentinel-2 satellite, but also to precipitation data recorded by a nearby precipitation station as well as to the Soil Water Index derived from the ASCAT sensor onboard Metop satellites. The improved sensitivity of the polarimetric features with respect to the single backscattering coefficients at different polarizations was also assessed
Analysis of multi-frequency SAR data for evaluating their sensitivity to soil moisture over an agricultural area in Argentina
No full textIn this paper, a joint analysis of multi-frequency SAR data has been performed to assess their sensitivity to soil moisture variations over an agricultural area. The main objective was evaluating the performances offered by C and L bands in terms of sensitivity to soil moisture. We used L-band quad-polarimetric data acquired by SAOCOM-1A and C-band dual-polarimetric data collected by Sentinel-1A over an agricultural area located in the Córdoba Province, Argentina. We analyzed the temporal evolution of the backscattering coefficient at different polarizations with respect to in-situ soil moisture measurements collected during a field campaign conducted by the Argentinian Space Agency as well as data recorded by a permanent network of ground stations. Sensitivity to other variables, such as the NDVI, is also discussed and analyzed
Polarimetric SAR decompositions for soil moisture retrieval over corn fields in Argentina
No full textIn this study, we investigate the synergic use of polarimetric Synthetic Aperture Radar (SAR) decompositions and electromagnetic models for soil moisture retrieval over corn fields. The Generalized Freeman-Durden decomposition (GFD) is applied to a time-series of L-band full-polarimetric SAOCOM-1A data collected during the 2019-2020 growing season over an agricultural area. The scattering mechanisms (i.e., surface, double-bounce, and volume) derived from the decomposition are compared with the ones simulated using the Tor Vergata electromagnetic model. The goal of the work is to evaluate the capabilities of the GFD to consistently assign each scattered power to the corresponding scattering mechanism, so that the sensitivity to soil moisture and vegetation can be highlighted. Results point out significative discrepancies, especially for the volume term, while a good agreement is found for the double-bounce contribution. Differences are further confirmed when a simple linear regression model is applied to retrieve soil moisture using the GFD scattered powers or the model powers
Joint analysis of Sentinel-1 and SAOCOM data sensitivity to soil moisture content over an agricultural area
No full textA joint analysis of C-band dual-pol Sentinel-1A data and L-band full-pol SAOCOM-1A data is presented to investigate their sensitivity to soil moisture over an agricultural area located near the city of Monte Buey in the Córdoba Province, Argentina. The temporal evolution of the backscattering coefficient σ0 at different polarizations is analyzed with respect to in-situ soil moisture measurements collected during a field campaign as well as data recorded by ground stations from a permanent network. Sensitivity to vegetation parameters is also discussed. The fully polarimetric electromagnetic model developed at Tor Vergata University is used to compare simulated and measured σ0 for corn fields
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Analysis of polarimetric SAR data for soil moisture retrieval
No full textIn this paper, the results obtained by applying two polarimetric SAR decompositions to a time-series of L-band radar data, in terms of scattering contributions, are compared with the simulations of the Tor Vergata electromagnetic model. The objective was to evaluate the capability of polarimetric SAR decompositions to single out those scattering mechanisms mostly correlated to soil moisture or vegetation. We performed the analysis by using L-band full-polarimetric SAOCOM-1A data acquired over an agricultural region in the Monte Buey site (Córdoba Province, Argentina) and by considering five corn fields
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