In this paper we present a new model to describe the interaction of electromagnetic waves with spheres covered by metamaterials. The model is based on a field expansion and the definition of reflection coefficients as ratios between travelling waves. The introduced formulation allows a clear physical interpretation of several electromagnetic scattering phenomena. In this work, it is used to investigate the scattering suppression that is the phenomenon that allows the cloaking of spherical objects. The obtained results are consistent with other published results and introduce a new interpretation framework that can be used to design future materials in a plethora of applications.
In semi-arid regions, small reservoirs are widely employed for facing seasonal in water availability due to the alternation of a short rainy season and of a very long dry season. Therefore, their monitoring is fundamental for local rural communities wellness. In this paper, we present a novel framework for water resources management exploiting the synergy of synthetic aperture radar (SAR) data and hydrological models. The pilot project was implemented in Burkina Faso, showing good potentialities for cheap and continuous monitoring of the environment through the exploitation of a multi-disciplinary framework.
In this paper, we present a new framework for the generation of two new classes of RGB products derived from multitemporal SAR data. The aim of our processing chain is to provide products characterized by a high degree of interpretability (thanks to a consistent rendering of the underlying electromagnetic scattering mechanisms) and by the possibility to be exploited in combination with simple algorithms for information extraction. The physical rationale of the proposed RGB products is presented through examples highlighting their principal properties. Finally, the suitability of these products with applications is demonstrated through two examples dealing with feature extraction and classification activities.
In this paper we model those features on a SAR image that are related to "multiple interactions" between different
buildings, a phenomenon typical of urban areas characterized by tall and/or closely spaced buildings. We employ a set of
conditions, as function of the distance between two subsequent buildings, to verify the occurrence of multiple reflections.
We use a deterministic approach to calculate the amplitude value of multiple reflections and determine their position in
an azimuth-slant range plane; the used method takes into account the geometric and electromagnetic characteristics of
man-made structures.
Our method is conceived to model and work with a single high-resolution SAR image of an extended area.
The integrated management of water resources is a crucial problem for improving the quality of life in Sub-Saharian
Africa. Several satellites everyday acquire a huge amount of physical information that could be employed as a support
for solving agriculture and water problems. In this paper we present a project devoted to exploit the use of high
resolution synthetic aperture radar (SAR) images for water resource management at no cost for the users. A case study is
developed in the Yatenga region, in the northern Burkina Faso, integrating hydrologic and remote sensing models in
order to improve the capacity of predicting flood and drought events. Main attention is posed here on the innovative
fractal techniques developed for the extraction of geometrical and physical parameters that can be used for calibrating
hydro-geological models.
In this paper a fractal based processing for the analysis of SAR images of natural surfaces is presented. Its definition is
based on a complete direct imaging model developed by the authors. The application of this innovative algorithm to
SAR images makes possible to obtain complete maps of the two key parameters of a fractal scene: the fractal dimension
and the increment standard deviation. The fractal parameters extraction is based on the estimation of the power spectral
density of the SAR amplitude image. From a theoretic point of view, the attention is focused on the retrieving procedure
of the increment standard deviation, here presented for the first time. In the last section of the paper, the application of
the introduced processing to high resolution SAR images is presented, with the relevant maps of the fractal dimension
and of the increment standard deviation.
Recently we proposed a Polarimetric Two-Scale Model (PTSM) [1-3], able to retrieve surface roughness, ground
permittivity and soil moisture content by processing polarimetric Synthetic Aperture Radar (SAR) data.
In our model we consider a bare soil surface as composed of large-scale variations on which a small-scale roughness is
superimposed. In particular, the large-scale roughness is locally treated by replacing the surface with a slightly rough
tilted facet, whose slope is the same of the smoothed surface at the center of the pertinent facet. The facet slopes along
azimuth and range directions are modeled as independent Gaussian variables. Unlike what is described in [1-3], here the
facet slope means are not forced to be equal to zero and then our retrieval algorithm can be applied even on not flat areas,
just considering information provided by Digital Elevation Models (DEM). The facet's tilt causes the rotation of the local
incidence plane around the line of sight and the variation of the local incidence angle around the radar look angle. We
accounted for both these effects to evaluate analytically the normalized radar cross sections (NRCS), employed to
retrieve the roughness and the soil moisture content using the co-pol/cross-pol method.
The response of natural stratification to electromagnetic wave has received much attention in last decades, due to its
crucial role played in the remote sensing arena. In this context, when the superficial structure of the Earth, whose
formation is inherently layered, is concerned, the most general scheme that can be adopted includes the characterization
of layered random media. Moreover, a key issue in remote sensing of Earth and other Planets is to reveal the content
under the surface illuminated by the sensors. For such a purpose, a quantitative mathematical analysis of wave
propagation in three-dimensional layered rough media is fundamental in understanding intriguing scattering phenomena
in such structures, especially in the perspective of remote sensing applications. Recently, a systematic formulation has
been introduced to deal with the analysis of a layered structure with an arbitrary number of rough interfaces. Specifically,
the results of the Boundary Perturbation Theory (BPT) lead to polarimetric, formally symmetric and physical revealing
closed form analytical solutions. The comprehensive scattering model based on the BPT methodologically permits to
analyze the bi-static scattering patterns of 3D multilayered rough media. The aim of this paper is to systematically show
how polarimetric models obtainable in powerful BPT framework can be successfully applied to several situations of
interest, emphasizing its wide relevance in the remote sensing applications scenario. In particular, a proper
characterization of the relevant interfacial roughness is adopted resorting to the fractal geometry; numerical examples are
then presented with reference to representative of several situations of interest.
In this paper we present a technique for the analysis of low intensity patches on SAR oceanic amplitude images. The
proposed technique, which is based on multifractal analysis of the edges of dark areas (here called regions of interest,
ROIs), can be used to identify oil slicks generated by moving ships. The core idea is that different physical-chemical
interactions of oil slicks and look-alikes with the sea surface imply different multifractal features for the edges of the
ROIs on the acquired images. Accordingly, we propose to perform a multifractal analysis on ROIs' edges, which consists
in the estimation of their multifractal spectrum and in the evaluation of the "dispersion area" of this spectrum. The
proposed procedure is tested on simulated SAR images and methods and results are extensively discussed. First results
seem to indicate that the observation of multifractal spectra is useful in order to distinguish between oil slicks generated
by moving ships from other kinds of slicks, even when these phenomena have the same degree of irregularity and an
estimation of the classical fractal dimension is not suitable for discrimination purposes.
In this paper we present the rationale and the preliminary results of a research project devoted to the appropriate and
innovative use of remotely sensed data for water management in semi-arid regions. The study area is the district of
Yatenga, northern Burkina Faso in the sub- Saharan belt of West Africa, where extreme climate conditions cause several
problems: drought, floods, soil erosion. The data comes from the Italian Space Agency (ASI) Cosmo-Skymed program,
which provides high resolution (1 meter) Synthetic Aperture Radar (SAR) images. Crucial peculiarity of the project is
the use of open source software for data processing and hydrological modeling. Two different hydrological models have
been selected. The Soil and Water Assessment Tool (SWAT) to be employed for the design of appropriate water
management plans and soil erosion mitigation measures. The Width Function Instantaneous Unit Hydrograph (WFIUHD)
model can to employed for the prevision of flood events and therefore for the planning of risk mitigation. The paper
shows the preliminary results of the project obtained by the processing of the first available high resolution SAR data. In
particular, the first step is the realization of a Digital Elevation Model (DEM). GIS tools have been set up for the DEMprocessing
in order to derive the needed hydro-morphological basin attributes to support the geo-morphological rainfall-
runoff (WFIUHD) modeling.
Fractal geometry provides the correct scientific approach to model natural environments. The altimeter of the Cassini
mission is acquiring profiles of the Titan surfaces. In this paper the rationale for a fractal analysis of the profiles acquired
by the Cassini altimeter is presented. The quantitative analysis proves that the fractal models provide meaningful
information on the Titan surface. It is also shown that the classical (non-fractal) analysis leads to erroneous results.
An innovative perspective to analyze the quality of digital elevation models (DEM) it is presented here. It is based on the fractal Brownian model which is suitable for the description of natural surfaces. Applications to across- track interferometric synthetic aperture radar (SAR) DEM and classical photogrammetric DEM is here accomplished showing the viability and usefulness of the proposed method.
An innovative IFSAR simulator is presented. It is based on an electromagnetic backscattering model of the scene and an accurate description of the IFSAR system impulse response function. A set of meaningful examples are also presented.
The operational and applicative contribute of Synthetic Aperture Radar (SAR) imagery is heavily affected by the possibility to extract some desired features. In this paper we consider such a problem on a new perspective based on the fractal approach. The fractal approach to SAR imagery classification seems to be very promising tool but still needs further clarifications. Different procedures are here discussed an compared, showing limits and potentials of such an intriguing mathematical tool.
In this paper we examine the SAR raw signal simulation of extended mountainous natural terrain. In order to cope with this goal we need to consider some problems relative to the evaluation of the backscattering pattern and of the efficient and correct inclusion of the SAR system unit response. In particular, and with regard to the first issue inclusion of the third dimension requires accommodation of its coarse description. Subjective and objective norms in order to judge the simulation results are presented and discussed, together with a number of examples.
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