29 research outputs found
Neural Network Emulation of the Integral Equation Model with Multiple Scattering
No full textThe Integral Equation Model with multiple scattering (IEMM) represents a well-established method that provides a theoretical framework for the scattering of electromagnetic waves from rough surfaces. A critical aspect is the long computational time required to run such a complex model. To deal with this problem, a neural network technique is proposed in this work. In particular, we have adopted neural networks to reproduce the backscattering coefficients predicted by IEMM at L- and C-bands, thus making reference to presently operative satellite radar sensors, i.e., that aboard ERS-2, ASAR on board ENVISAT (C-band), and PALSAR aboard ALOS (L-band). The neural network-based model has been designed for radar observations of both flat and tilted surfaces, in order to make it applicable for hilly terrains too. The assessment of the proposed approach has been carried out by comparing neural network-derived backscattering coefficients with IEMM-derived ones. Different databases with respect to those employed to train the networks have been used for this purpose. The outcomes seem to prove the feasibility of relying on a neural network approach to efficiently and reliably approximate an electromagnetic model of surface scattering
Towards an operational procedure to map soil moisture using SAR: Results of a seven-year-experiment over an agricultural area
No full textIn this work, the outcomes of a research activity, that lasted approximately seven years (2003-2010), in which soil moisture was monitored on a test site in Northern Italy by collecting a series of SAR images and in situ data are presented. Radar data were provided by the C-band ENVISAT/ASAR instrument. The research activity aimed at calibrating and validating a pre-operational algorithm, conceived to be used by the Italian Civil Protection, for high resolution soil moisture mapping from SAR data. The algorithm is focused on the Bayesian theory of parameter estimation. The Maximum A Posteriori (MAP) probability criterion or the Minimum Variance one are used to retrieve soil moisture by inverting a forward scattering model. Ancillary data such as optical images and land cover data are also used. The results of the validation activity have confirmed the validity of the proposed mapping approach. In particular, the algorithm allowed us to retrieve soil moisture with a R-2 coefficient of 0.77 and with a root mean square error in the order of 0.07 m(3)/m(3)
Radar bistatic configurations for soil moisture retrieval: A simulation study
No full textThe possible contribution of bistatic radar measurements for bare soil moisture retrieval is investigated in this paper. A simulation study based on well-established electromagnetic models of rough surface scattering (both coherent and incoherent components) has been accomplished for this purpose. The retrieval accuracy has been evaluated by using both the Cramer-Rao lower bound and the error variance of a linear regression estimator, thus considering slightly different assumptions on retrieval conditions. Both methods have allowed us to identify the optimal system configurations in terms of observation directions, polarizations, and frequency. This identification has been carried out for single-polarization and multipolarization receivers and for the case in which bistatic measurements are complemented by monostatic ones, which are expected to be available through already-existing spaceborne synthetic aperture radars. The optimal systems have first been singled out by considering a Gaussian autocorrelation function (ACF) and a constant value of correlation length. Successively, the simulations for an exponential ACF and a variable correlation length have been analyzed, demonstrating that the results substantially remain the same. The comparison between the soil moisture estimation accuracy yielded by the optimal configurations and that provided by the standard monostatic radar has shown that a significant improvement in the quality of retrieval can be achieved by complementing bistatic and monostatic measurements. © 2008 IEEE
Study on Optimal Configurations of Bistatic Radar to Retrieve Soil Moisture and Vegetation Biomass
No full textRetrieval and analysis of land surface microwave emissivity from SSM/I data
No full textThe retrieval of land surface emissivity from microwave radiometric measurements is useful for monitoring the surface properties without being affected by the contribution of the atmosphere, which can be significant at higher frequencies. It is based on the inversion of the radiative transfer equation, assuming the absence of scattering phenomena. In this work, a method to improve the accuracy of the emissivity estimates through the removal of the effects of the atmosphere from the radiometric data and through the consideration of the surface elevation information is proposed. We have used the Special Sensor Microwave/Imager (SSM/I) observations over Italy throughout 1995. The atmospheric parameters have been derived from the NCEP vertical profiles, whilst the presence of clouds has been detected through METEOSAT images co-located with the SSM/I ones. The data provided by a digital elevation model (DEM) have been also exploited. Monthly average maps of microwave emissivity relative to a geographical area including Italy have been produced to assess the whole estimation procedure, as well as to give examples of monitoring the seasonal trend of this parameter in a mountainous zone (Alps) and in a flat area (Po Plain)
Sensitivity of bistatic scattering to soil moisture and surface roughness of bare soils
No full textThe sensitivity of bistatic scattering coefficient sigma degrees to soil moisture content (SMC) and surface roughness was investigated by means of model simulations of the incoherent scattered fields performed with the advanced integral equation model (AIEM) and the second order small perturbation model (SPM). The study was performed by simulating scattering on the whole upper half space, for different values of incident angles. The achieved results, represented as maps of sigma degrees as a function of azimuth and zenith angles, were evaluated by means of a quality index which takes into consideration the effect of roughness on SMC measurement. The sensitivity analysis has pointed out that for measuring SMC a bistatic observation, by itself or combined with the monostatic one, can make appreciable improvements with respect to classical monostatic radar. Appendix A contains the AIEM formulas corrected for several typographical errors present in the specific literature
On the modeling of the bistatic coherent scattering from a rough surface
No full textIn this contribution, we investigate on the coherent bistatic scattering generated by a radar system when illuminating a rough surface. Moving from the well-known scattering theory based on the Kirchhoff approximation, we propose an extended formulation of the Fung-Eom model, by introducing a higherorder expansion on the phase term of the impinging spherical wave. We demonstrate and discuss the importance of such correction for the accurate characterization of the coherent scattering generated in bistatic radar system. We give insight, for the first time, on the role played by both the antenna pattern and the wavefront sphericity in bistatic scattering in the whole incidence plane, not limiting the analysis to the backscattering and specular directions. This is particularly important for practical applications, such as the modeling of the scattering generated by sources of opportunity
Optimization of bistatic radar configurations for vegetation monitoring
No full textBistatic radars have been recently proposed as an alternative to conventional monostatic radars since they can provide additional information in many fields of remote sensing applications. However, up to now, no bistatic radar campaigns, nor laboratory experiments, having vegetation as the target have been set up. This paper presents theoretical simulations of the bistatic scattering coefficient of crop and forest canopies. The electromagnetic model developed at Tor Vergata has been used to analyse scattering as a function of the observation angle, both in azimuth and elevation, and it will be shown that biomass monitoring can be optimized at out-of-incidence scattering planes
hCG and Its Disruption by Environmental Contaminants during Human Pregnancy
No full textHuman chorionic gonadotropin (hCG) is a hormone of considerable importance in the establishment, promotion and maintenance of human pregnancy. It has been clearly demonstrated that hCG exerts multiple endocrine, paracrine and autocrine actions on a variety of gestational and non-gestational cells and tissues. These actions are directed to promote trophoblast invasiveness and differentiation, placental growth, angiogenesis in uterine vasculature, hormone production, modulation of the immune system at the maternal-fetal interface, inhibition of myometrial contractility as well as fetal growth and differentiation. In recent years, considerable interest has been raised towards the biological effects of environmental contaminants, particularly endocrine disrupting chemicals (EDCs). Emerging evidence suggests that prenatal exposure to selected EDCs can have a deleterious impact on the fetus and long-lasting consequences also in adult life. The results of the in vitro effects of commonly found EDCs, particularly Bisphenol A (BPA) andpara-Nonylphenol (p-NP), indicate that these substances can alter hCG production and through this action could exert their fetal damage, suggesting that hCG could represent and become a potentially useful clinical biomarker of an inappropriate prenatal exposure to these substances
Monitoring Soil Moisture in an Agricultural Test Site Using SAR Data: Design and Test of a Pre-Operational Procedure
No full textAn algorithm for pre-operational high resolution soil moisture mapping using Synthetic Aperture Radar (SAR) data is presented. It has been conceived to be inserted in the operational weather alert system of the Italian Department of Civil Protection. The Maximum A Posteriori (MAP) probability criterion is applied to retrieve soil moisture by inverting a forward backscattering model, and ancillary data such as optical images and land cover maps are also used to identify areas in which the retrieval can be carried out. The well-established semiempirical water cloud model is adopted to correct for the effect of vegetation on SAR data. In anticipation of the use of the algorithm in an operational system, in which the SAR-derived high resolution soil moisture product can be assimilated within weather prediction models or hydrological ones, an uncertainty index is associated to each estimate. The algorithm has been tested on a dataset consisting of ground data gathered for seven years (2003-2010) on an agricultural test site in Northern Italy and radar data provided by the C-band ENVISAT/ASAR instrument. A comparison, performed at field scale, between estimated and in situ soil moisture data has shown that, by discarding the estimates with the largest uncertainty, the correlation coefficient can exceed 0.80 and the root mean square estimation error is less than 0.05 m(3)/m(3). Moreover, the uncertainty index has turned out to be fairly correlated to the actual estimation error
