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1.
An inversion technique based on the merging of microwave remotely sensed data is applied to ground-based radiometer and scatterometer data acquired for the same area. The purpose of this technique is to retrieve the dielectric constant of bare soils. The algorithm is based on a Bayesian approach and combines prior information on the dielectric constant and surface roughness with observed data, in order to obtain a marginal posterior probability density function. The function describes how the probability is distributed within the range of the dielectric constant values, given the measured values of emissivity and backscattering coefficient. The algorithm allows for the incorporation of all the available sources of information, such as multipolarization and multifrequency data. Several criteria, which have been used to compare the predicted and the observed values, show that for dielectric constant values higher than 10 the best performance is achieved when data with one polarization and one or two frequencies are exploited. For dielectric constant values of less than 10, the configuration with two polarizations produces the best estimates. 相似文献
2.
The product covariance model, the product–sum covariance model, and the integrated product and integrated product–sum models have the advantage of being easily fitted by the use of marginal variograms. These models and the use of the marginals are described in a series of papers by De Iaco, Myers, and Posa. Such models allow not only estimating values at nondata locations but also prediction in future times, hence, they are useful for analyzing air pollution data, meteorological data, or ground water data. These three kinds of data are nearly always multivariate and because the processes determining the deposition or dynamics will affect all variates, a multivariate approach is desirable. It is shown that the use of marginal variograms for space–time modeling can be extended to the multivariate case and in particular to the use of the Linear Coregionalization Model (LCM) for cokriging in space–time. An application to an environmental data set is given. 相似文献
3.
Covariance functions and models for complex-valued random fields 总被引：1，自引：1，他引：0
S.?De IacoEmail author M.?Palma D.?Posa 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(3):145-156
In Geostatistics, primary interest often lies in the study of the spatial, or spatial-temporal, correlation of real-valued random fields, anyway complex-valued random field theory is surely a natural extension of the real domain. In such a case, it is useful to consider complex covariance functions which are composed of an even real part and an odd imaginary part. Generating complex covariance functions is not simple at all, but the procedure, developed in this paper, allows generating permissible covariance functions for complex-valued random fields in a straightforward way. In particular, by recalling the spectral representation of the covariance and translating the spectral density function by using a shifting factor, complex covariances are obtained. Some general aspects and properties of complex-valued random fields and their moments are pointed out and some examples are given. 相似文献
4.
Complex-valued random fields represent a natural extension of real-valued random fields and can be useful for modeling vectorial data in two dimensions (i.e., a wind field). In such a case, some theoretical issues arise concerning generating and fitting complex covariance functions to be used for prediction purposes. In this paper, some general aspects and properties of complex-valued random fields are summarized and a procedure to fit complex stationary covariance functions is proposed. A case study for analyzing wind speed data is presented. 相似文献
5.
D. Posa 《Mathematical Geology》1991,23(5):695-702
A natural extrapolation of stochastic operations (continuity and differentiation) already described in time domain (one-dimensional case) is established for spatial processes (two- or three-dimensional case). If stationarity decision is assumed, the continuity and differentiability (in the mean square sense) of a spatial process depends on the continuity and differentiability of the correlation function at the origin. Spatial processes described by stationary random functions are not continuous (in the mean square sense) when the covariance function presents a nugget effect, and they are not differentiable when the same covariance function is described by a spherical or an exponential covariance (models which are often used in geostatistics). 相似文献
6.
R.M.C. Lopes K.L. Mitchell J.I. Lunine R. Lorenz R.L. Kirk S.D. Wall A.D. Fortes J. Radebaugh S.J. Ostro M.D. Allison R. Boehmer P. Callahan E. Flamini Y. Gim S. Hensley W.T.K. Johnson D.O. Muhleman R. Orosei F. Posa R. Seu L.A. Soderblom S. Vetrella L. Wye 《Icarus》2007,186(2):395-412
The Cassini Titan Radar Mapper obtained Synthetic Aperture Radar images of Titan's surface during four fly-bys during the mission's first year. These images show that Titan's surface is very complex geologically, showing evidence of major planetary geologic processes, including cryovolcanism. This paper discusses the variety of cryovolcanic features identified from SAR images, their possible origin, and their geologic context. The features which we identify as cryovolcanic in origin include a large (180 km diameter) volcanic construct (dome or shield), several extensive flows, and three calderas which appear to be the source of flows. The composition of the cryomagma on Titan is still unknown, but constraints on rheological properties can be estimated using flow thickness. Rheological properties of one flow were estimated and appear inconsistent with ammonia-water slurries, and possibly more consistent with ammonia-water-methanol slurries. The extent of cryovolcanism on Titan is still not known, as only a small fraction of the surface has been imaged at sufficient resolution. Energetic considerations suggest that cryovolcanism may have been a dominant process in the resurfacing of Titan. 相似文献
7.
Although there are multiple methods for modeling matrix covariance functions and matrix variograms in the geostatistical literature, the linear coregionalization model is still widely used. In particular it is easy to check to ensure whether the matrix covariance function is positive definite or that the matrix variogram is conditionally negative definite. One of the difficulties in using a linear coregionalization model is in determining the number of basic structures and the corresponding covariance functions or variograms. In this paper, a new procedure is given for identifying the basic structures of the space–time linear coregionalization model and modeling the matrix variogram. This procedure is based on the near simultaneous diagonalization of the sample matrix variograms computed for a set of spatiotemporal lags. A case study using a multivariate spatiotemporal data set provided by the Environmental Protection Agency of Lombardy, Italy, illustrates how nearly simultaneous diagonalization of the empirical matrix variograms simplifies modeling of the matrix variograms. The new methodology is compared with a previous one by analyzing various indices and statistics. 相似文献
8.
The construction of a spatial model for several variables in the Mar Piccolo of Taranto, Italy, is important for understanding the effect that polluted streams entering the bay have on the saltwater environment.This study describes the geostatistical techniques used to interpolate dissolved oxygen values over a three-dimensional grid within the First Bay of the Mar Piccolo.Emphasis is placed in describing in detail the step-by-step methodology applied in the case study. The stationarity decision that allows for statistical inference is discussed, and its implication on the variography analysis is presented. The subsequent three-dimensional kriging algorithm with a trend model is described and implemented. 相似文献
9.
Cappello Claudia De Iaco Sandra Maggio Sabrina Posa Donato 《Mathematical Geosciences》2021,53(5):999-1025
Surface ocean currents are often of interest in environmental monitoring. These vectorial data can be reasonably treated as a finite realization of a complex-valued random field, where the decomposition in modulus (current speed) and direction (current direction) of the current field is natural. Moreover, when observations are also available for different time points (other than at several locations), it is useful to evaluate the evolution of their complex correlation over time (rather than in space) and the corresponding modeling which is required for estimation purposes. This paper illustrates a first approach where the temporal profile of surface ocean currents is considered. After introducing the fundamental aspects of the complex formalism of a random field indexed in time, a new class of models suitable for including the temporal component is proposed and applied to describe the time-varying complex covariance function of current data. The analysis concerns ocean current observations, taken hourly on 30 April 2016 through high frequency radar systems at some stations located in the Northeastern Caribbean Sea. The selected complex covariance model indexed in time is used for estimation purposes and its reliability is confirmed by a numerical analysis.
相似文献10.
C.?Cappello S.?De IacoEmail authorView author&#;s OrcID profile D.?Posa 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(1):17-35
In statistical space-time modeling, the use of non-separable covariance functions is often more realistic than separable models. In the literature, various tests for separability may justify this choice. However, in case of rejection of the separability hypothesis, none of these tests include testing for the type of non-separability of space-time covariance functions. This is an important and further significant step for choosing a class of models. In this paper a method for testing positive and negative non-separability is given; moreover, an approach for testing some well known classes of space-time covariance function models has been proposed. The performance of the tests has been shown using real and simulated data. 相似文献