Search Results (5)

Spaceborne Synthetic Aperture Radar (SAR) can be applied for monitoring tropical cyclones (TCs), but co-polarized C-band SAR suffers from signal saturation such that it is improper for high wind-speed conditions. In contrast, cross-polarized SAR data does not suffer from this issue, but the retrieval algorithm needs more deliberation. Previously, many geophysical model functions (GMFs) have been developed using cross-polarized data, which obtain wind speeds using the complex relationships described by radar backscatter, incidence angle, wind direction, and radar look direction. In this regard, the rapid development of artificial intelligence technology has provided versatile machine learning methods for such a nonlinear inversion problem. In this study, we comprehensively compare the wind-speed retrieval performance of several models including Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Network (DNN), which were developed based on spatio-temporal matching and correlation analysis of stepped frequency microwave radiometer (SFMR) and dual-polarized Sentinel-1 SAR data after noise removal. A data set with ~2800 samples is generated during TCs for training and validating the inversion model. The generalization ability of different models is tested by the reserved independent data. When using similar parameters with GMFs, RF inversion has the highest accuracy with a Root Mean Square Error (RMSE) of 3.40 m/s and correlation coefficient of 0.94. Furthermore, considering that the sea surface temperature is a crucial factor for generating TCs and influencing ocean backscattering, its effects on the proposed RF model are also explored, the results of which show improved wind-speed retrieval performances. Full article

The risk of oil spills in the Arctic is growing rapidly as anthropogenic activities increase due to climate-driven sea ice loss. Detecting and monitoring fuel spills in the marine environment is imperative for enacting an efficient response to mitigate the risk. Microwave radar systems can be used to address this issue; therefore, we examined the potential of C-band polarimetric radar for detecting diesel fuel in freezing seawater under windy environmental conditions. We present results from a mesocosm experiment, where we introduced diesel fuel to a seawater-filled cylindrical tub at the Sea-ice Environmental Research Facility (SERF), University of Manitoba. We characterized the temporal evolution of the diesel-contaminated seawater and sea ice by monitoring the normalized radar cross section (NRCS) and polarimetric parameters (i.e., copolarization ratio (R_co), cross-polarization ratio (R_xo), entropy (H), mean-alpha (α), conformity coefficient (μ), and copolarization correlation coefficient (ρ_co)) at 20° and 25° incidence angles. Three stages were identified, with notably different NRCS and polarimetric results, related to the thermophysical conditions. The transition from calm conditions to windy conditions was detected by the 25° incidence angle, whereas the transition from open water to sea ice was more apparent at 20°. The polarimetric analysis demonstrated that the conformity coefficient can have distinctive sensitivities to the presence of wind and sea ice at different incidence angles. The H versus α scatterplot showed that the range of distribution is dependent upon wind speed, incidence angle, and oil product. The findings of this study can be used to further improve the capability of existing and future C-band dual-polarization radar satellites or drone systems to detect and monitor potential diesel spills in the Arctic, particularly during the freeze-up season. Full article

Similar to light detection and ranging (lidar), profile radar can detect forest vertical structure directly. Recently, the first Ku-band profile radar system designed for forest applications, called Tomoradar, has been developed and evaluated in boreal forest. However, the physical relationships between the waveform and forest structure parameters such as height, leaf area index (LAI), and aboveground biomass are still unclear, which limits later forestry applications. Therefore, it is necessary to develop a theoretical model to simulate the relationship and interpret the mechanism behind. In this study, we extend the Radiosity Applicable to Porous IndiviDual objects (RAPID2) model to simulate the profile radar waveform of forest stands. The basic assumption is that the scattering functions of major components within forest canopy are similar between profile radar and the side-looking radar implemented in RAPID2, except several modifications. These modifications of RAPID2 mainly include: (a) changing the observation angle from side-looking to nadir-looking; (b) enhancing the ground specular scattering in normal direction using Fresnel coefficient; (c) increasing the timing resolution and recording waveform. The simulated waveforms were evaluated using two plots of Tomoradar waveforms at co- and cross- polarizations, which are collected in thin and dense forest stands respectively. There is a good agreement (R² ≥ 0.80) between the model results and experimental waveforms in HH and HV polarization modes and two forest scenes. After validation, the extended RAPID2 model was used to explore the sensitivity of the stem density, single tree LAI, crown shape, and twig density on the penetration depth in the Ku-band. Results indicate that the backscattering of the profile radar penetrates deeper than previous studies of synthetic aperture radar (SAR), and the penetration depth tends to be several meters in Ku-band. With the increasing of the needle and twig density in the microwave propagation path, the penetration depth decreases gradually. It is worth noting that variation of stem density seems to have the least effect on the penetration depth, when there is no overlapping between the single tree crowns. Full article

Investigation of microwave scattering mechanisms is extremely important for developing methods for ocean remote sensing. Recent studies have shown that a common two-scale scattering model accounting for resonance (Bragg) scattering has some drawbacks, in particular it often overestimates the vertical-to-horizontal polarization radar return ratio and underestimates the radar Doppler shifts if the latter are assumed as associated with quasi linear resonance surface waves. It is supposed nowadays that radar backscattering at moderate incidence angles is determined not only by resonance Bragg mechanism but also contains non polarized (non Bragg) component which is associated supposedly with wave breaking but which is still insufficiently studied. Better understanding of the scattering mechanisms can be achieved when studying variations of radar return due to long wind waves. In this paper, results of experiments from an Oceanographic Platform on the Black Sea using dual co-polarized X-band scatterometers working at moderate incidence are presented and variations of Bragg and non-Bragg components (BC and NBC, respectively) and radar Doppler shifts are analysed. It is established that BC and NBC are non-uniformly distributed over profile of dominant (decametre-scale) wind waves (DWW). Variations of BC are characterized by some “background” return weakly modulated with the dominant wind wave periods, while NBC is determined mostly by rare and strong spikes occurred near the crests of the most intense individual waves in groups of DWW. We hypothesize that the spikes are due to intensification of nonlinear structures on the profile of short, decimetre-scale wind waves when the latter are amplified by intense DWW. Bragg scattering in slicks under the experimental conditions was suppressed stronger than NBC and spikes dominated in total radar return. It is obtained that radar Doppler shifts at HH-polarization are larger than at VV-polarization, particularly in slicks, the same relation is for NBC and BC Doppler shifts, thus indicating different scattering mechanisms for these components. Full article

Microwave radar is a well-established tool for all-weather monitoring of film slicks which appear in radar imagery of the surface of water bodies as areas of reduced backscatter due to suppression of short wind waves. Information about slicks obtained with single-band/one-polarized radar seems to be insufficient for film characterization; hence, new capabilities of multi-polarization radars for monitoring of film slicks have been actively discussed in the literature. In this paper the results of new experiments on remote sensing of film slicks using dual co-polarized radars—a satellite TerraSAR-X and a ship-based X-/C-/S-band radar—are presented. Radar backscattering is assumed to contain Bragg and non-Bragg components (BC and NBC, respectively). BC is due to backscattering from resonant cm-scale wind waves, while NBC is supposed to be associated with wave breaking. Each of the components can be eliminated from the total radar backscatter measured at two co-polarizations, and contrasts of Bragg and non-Bragg components in slicks can be analyzed separately. New data on a damping ratio (contrast) characterizing reduction of radar returns in slicks are obtained for the two components of radar backscatter in various radar bands. The contrast values for Bragg and non-Bragg components are comparable to each other and demonstrate similar dependence on radar wave number; BC and NBC contrasts grow monotonically for the cases of upwind and downwind observations and weakly decrease with wave number for the cross-wind direction. Reduction of BC in slicks can be explained by enhanced viscous damping of cm-scale Bragg waves due to an elastic film. Physical mechanisms of NBC reduction in slicks are discussed. It is hypothesized that strong breaking (e.g., white-capping) weakly contributes to the NBC contrast because of “cleaning” of the water surface due to turbulent surfactant mixing associated with wave crest overturning. An effective mechanism of NBC reduction due to film can be associated with modification of micro-breaking wave features, such as parasitic ripples, bulge, and toe, in slicks. Full article