Saverio Mori

Discrimination of Water Surfaces, Heavy Rainfall, and Wet Snow Using COSMO-SkyMed Observations of Severe Weather Events

An automatic method to distinguish water surfaces (either flooded or permanent water bodies) from artifacts caused by heavy precipitation and wet snow is designed to improve flood detection accuracy in X-band synthetic aperture radar (SAR) images. The algorithm implementing the proposed method, mainly based on image segmentation techniques and on the fuzzy logic, consists of two principal steps: 1) detection of regions (or segments) of low-radar backscatter that appear dark in a SAR image, and 2) classification of each detected segment. Ancillary data, such as a local incidence angle map, a land cover map, and an optical image (helpful to detect wet snow), are also used. Through the fuzzy logic, the algorithm integrates different rules for the detection of dark areas, as well as for their classification based on radiometric, geometrical and shape features extracted from the segmented SAR image and on the ancillary data. The algorithm is tested on the COSMO-SkyMed imagery of the severe weather event that hit Northwest Italy on November 2011. A comparison with measured data, provided by the weather radars belonging to the Italian radar national network, and with the ground precipitation, forecasted by a numerical weather prediction model routinely used within the framework of the EUMETSAT Hydrology Satellite Application Facility project, indicates that the algorithm produces reliable classification maps, being able to distinguish the rainfall signature on X-band SAR images from that of flooded areas.

Modeling Polarimetric Response of Spaceborne Synthetic Aperture Radar Due to Precipitating Clouds From X- to Ka-Band

Spaceborne synthetic aperture radars (SARs) exhibit the appealing imaging feature of very high spatial resolution (on the order of meters). At frequency above C-band, the atmospheric effects, and particularly the signature of precipitating clouds, cannot be neglected on both amplitude and phase received signal. The impact of precipitation on SAR slant-view imagery is due to a combination of surface and volumetric backscattering, coupled with path attenuation and with a significant dependence on frequency, polarization, and spatial distribution of hydrometeors. The actual spatial resolution (on the order of hundreds of meters) of these effects is larger than the SAR nominal one due to the random nature of the moving distributed atmospheric target. This paper is devoted to the numerical forward modeling of SAR response at X-, Ku-, and Ka-bands due to precipitating clouds in order to better understand the physical correlation between SAR echo and precipitation. To this aim, a high-resolution mesoscale atmospheric numerical model is used to extract the 3-D distribution of liquid and ice hydrometeors. A detailed sensitivity analysis of SAR backscattering is carried out with respect to hydrometeor columnar and slant water contents, relative contribution of volumetric and surface scattering, incidence angle and ground inhomogeneity, polarimetric observables, and frequency scaling signatures. The numerical results show that the slant-view of SAR observations plays a determinant role and the use of a multifrequency polarimetric SAR may be very useful to characterize precipitation effects and, to a certain extent, retrieve its content at very high spatial resolution.

Detection of floods and heavy rain using Cosmo-SkyMed data: The event in Northwestern Italy of November 2011

In this work, an automatic method to distinguish, in X-band SAR images such as those supplied by Cosmo-SkyMed, water surfaces (either flooded, or permanent water bodies) from artifacts due to heavy precipitation, is designed to improve flood detection accuracy. The method, mainly based on the fuzzy logic, consists of two main steps, i.e., the detection of low backscatter areas and the classification of each dark object present in the considered SAR image. The algorithm uses ancillary data, such as a local incidence angle map and a Land Cover map. Through the fuzzy logic, it integrates different rules for the detection of low backscatter areas (based on the standard deviation of the backscattering coefficient and on a well-established radar backscattering model), as well as different rules for the classification of the low backscatter (dark) areas (i.e., to distinguish water surfaces from artifacts) based on their geometrical and shape features and on both land cover and local incidence angle.

Model analysis of hydrometeor scattering effects on free space near-infrared links

A promising technology for peer-to-peer connections and urban area networks is represented by wireless communications through free space using optical carrier (Free Space Optics, FSO). This technology ensures high data rates, with relatively low error rates, low power consumption and inherent security. Nevertheless FSO links are quite sensitive to atmospheric condition. Fog droplets, but also raindrops and snowflakes, may introduce severe path attenuation which drastically reduces the channel availability. A parametric model to simulate droplets scattering effects over the FSO link in terms of extinction coefficient, albedo factor and asymmetry coefficient as function of the particle water content will be presented. Both single and multiple scattering effects will be shown.

Microphysical characterization of free space optical link due to hydrometeor and fog effects.

Free space optics (FSO) channel availability is affected by atmospheric water particles, which may introduce severe path attenuation. A unified microphysically oriented atmospheric particle scattering (MAPS) model is proposed and described to simulate particle scattering effects on FSO links. Atmospheric particles, such as raindrops, graupel particles, and snowflakes, together with fog droplets, are considered. Input data to characterize liquid and frozen water particle size distribution, density, and refractivity are derived from available literature data and measurements. Scattering, absorption, and extinction coefficients as well as the asymmetry factor are numerically simulated for each particle class and then parametrized with respect to particle water content, fall rate, and visibility, spanning from visible to infrared wavelengths. Both single- and multiple-scattering effects are discussed and quantified by using a radiative transfer model for small-angle approximation. MAPS simulations confirm that fog layers are those causing the largest power extinction on FSO links, but also several decibels of attenuation can be attributed to snow and rain conditions. Multiple-scattering effects, especially due to fog droplets, heavy rain, and dry snowflakes, typically tend to reduce the total attenuation by increasing the received power. An estimate of these effects, parameterized to single-scattering extinction, is proposed for near-infrared FSO link design.

Hydrometeor scattering and stochastic modeling for free-space optical channel characterization

Free space communications, using optical carriers (Free Space Optics, FSO) technology, ensure high data rates, with relatively low error rates, low power consumption and inherent security. However, FSO links are quite sensitive to atmospheric conditions. Fog droplets, but also raindrops and snowflakes, may introduce severe path attenuation which drastically reduces the channel availability. A parametric model to simulate droplets scattering effects on FSO links (from visible to near infrared wavelengths) is proposed in terms of scattering coefficients, albedo factor and asymmetry coefficient as function of the particle water content. Both single and multiple scattering effects are shown and discussed. A prototype of a stochastic time series generator of FSO rain attenuation is also presented.

Modeling scintillation effects on free space optical links using radiosounding profile data

Wireless communications using free space optics (FSO) are sensitive to atmospheric conditions. Hydrometeors, but also clear-air turbulence, may introduce severe impairments reducing FSO channel availability. Yearly radiosounding profiles, available near Rome (Italy), are used to estimate the power scintillation index through a new physical turbulence structure constant model and to estimate scintillation fade statistics for near-infrared FSO.

Analysis of rainfall signatures on COSMO-SkyMed X-Band Synthetic Aperture Radar observations

This paper presents an investigation on the rainfall signature for two COSMO-SkyMed (CSK) satellite case studies. Both of them are relative to a severe precipitation weather event, occurred in northwestern Italy (close to Liguria region) on November 3-8, 2011. This event was monitored by using a number of CSK images provided by the Italian Space Agency (ASI). In this case CSK X-SAR data have been compared with the weather radar (WR) Italian Radar National Mosaic. A third case study is relative to Hurricane “Irene” event, occurred in Eastern United States (close to Delaware) on late August 2011. CSK X-SAR images are compared with respect to concurrent ground-based S-band NEXRAD weather radar reflectivities. The correlation of the precipitating cloud fields between CSK X-SAR and WR images is significant in all case studies. An application of a refined XSAR-based precipitation retrieval method is presented. The X-SAR surface response is estimated using ancillary data, such as land cover maps and a digital elevation model (DEM).

Atmospheric precipitation impact on synthetic aperture radar imagery: Numerical model at X and KA bands

Recent spaceborne polarimetric Synthetic Aperture Radars (SARs) enable the complete characterization of target scattering and extinction properties. Several missions are operating at X band while there are plans and analyses for systems operating at higher frequencies, such as Ka band. Systems operating at these frequencies have interesting and distinctive applications in the field of geosciences such as Cartography, Surface deformation detection, Forest cover mapping and many others. However, the detected ground surface response can be affected by atmospheric effects in both signal amplitude and phase, especially in presence of atmospheric precipitations. In this work we will introduce a simulation framework developed to characterize how precipitating clouds affect spaceborne X- and Ka-band SARs systems. The proposed framework is able to simulate the polarimetric SAR ground responses in terms of Normalized Radar Cross Sections (NRCS) and complex correlation coefficient, both for realistic atmosphere-ground scenarios and for synthetic canonical ones. Some preliminary results will be shown and discussed.

Clear-air turbulence effects modeling on terrestrial and satellite free-space optical channels

Wireless communications using free space optics (FSO) are sensitive to atmospheric conditions. Clear-air turbulence can introduce severe impairments reducing FSO channel availability. Radiosounding profiles, available near Rome (Italy) and Munich (Germany), are used to estimate the power scintillation index through a new physical refractive index structure constant model and to estimate scintillation fade statistics for near-infrared FSO. Preliminary qualitative validation is performed using FSO campaign near Munich for both terrestrial and slant links.