Dual-polarized microwave radars are of particular interest nowadays as perspective tool of ocean remote sensing. Microwave radar backscattering at moderate and large incidence angles according to conventional models is determined by resonance (Bragg) surface waves typically of cm-scale wavelength range. Some recent experiments have indicated, however, that an additional, non Bragg component (NBC) contributes to the radar return. The latter is considered to occur due to wave breaking. At present our understanding of the nature of different components of radar return is still poor. This paper presents results of field experiment using an X-/C-/S-band Doppler radar operating at HH- and VVpolarizations. The intensity and radar Doppler shifts for Bragg and non Bragg components are retrieved from measurements of VV and HH radar returns. Analysis of a ratio of VV and HH radar backscatter – polarization ratio (PR) has demonstrated a significant role of a non Bragg component. NBC contributes significantly to the total radar backscatter, in particular, at moderate incidence angles (about 50-70 deg.) it is 2-3 times smaller than VV Bragg component and several times larger that HH Bragg component. Both NBC and BC depend on azimuth angle, being minimal for cross wind direction, but NBC is more isotropic than BC. It is obtained that velocities of scatterers retrieved from radar Doppler shifts are different for Bragg waves and for non Bragg component; NBC structures are “faster” than Bragg waves particularly for upwind radar observations. Bragg components propagate approximately with phase velocities of linear gravity-capillary waves (when accounting for wind drift). Velocities of NBC scatterers depend on radar band, being the largest for S-band and the smallest at X-band, this means that different structures on the water surface are responsible for non Bragg scattering in a given radar band.
Investigation of the Doppler shift of radar return from the sea surface is very important for better understanding of capabilities of exploitation of microwave radar for measuring velocities of marine currents. Here new field experiments carried out from a Platform on the Black Sea with a coherent X-band scatterometer, and a Doppler multifrequency (X- /C-/S-band) dual-polarized radar recently designed at IAP RAS are discussed. It is shown that the radar return contains both Bragg (polarized) and non polarized scattering components, presumably giving different contributions to radar Doppler shifts. Radar Doppler shifts were estimated using two different definitions as a) a frequency of the “centre of gravity” of an instantaneous radar return spectrum (ASIS) averaged over periods of dominant wind waves and b) the “centre of gravity” of the averaged over dominant wave periods spectrum (SAS). The ASIS and SAS values for both VV and HH-polarizations are shown to be different due to effects of radar backscatter modulation by dominant (long) wind waves. The radar Modulation Transfer Function (MTF) has been analyzed from experimental data and difference between SAS- and ASIS-values has been satisfactory explained using the measured MTF-values. It is obtained that experimental values of ASIS can be satisfactory described by the Bragg model despite the significant contribution of NP component to the radar backscatter. A physical explanation of the effect is given.
At present a sufficient amount of methods is offered for determining the characteristics of sea roughness in accordance with optical images of wavy water surface obtained from different near-shore constructions, sea platforms, vessels, aircraft and satellites. The most informative elements in this case are solar path and peripheral areas of the image free from sun glitters. However, underwater images of the surface obtained with the help of optical receiver located at a certain depth contain apart from the mentioned elements one more informative element– Snell’s window. It is an underwater sky image which distortions of border contain information on roughness characteristics and serve as the indicator of its variability. The research offers the method for determining energy spectra of wind waves in accordance with the second statistical moment of Snell’s window image. The results of testing of the offered method are provided based on natural images registered in the course of trip to the Black Sea under conditions of different wind and wave environment for clear surface and surface covered by surfactant films. For both cases frequency spectra of surface slopes are recovered and their good coincidence to the spectra received by processing of signals from a string wave recorder is established. Efficiency of application of the offered method for tasks of remote monitoring and environmental control of natural reservoirs is shown.
Retrieving the water-leaving reflectance from airborne hyperspectral data implies to deal with three steps. Firstly, the radiance recorded by an airborne sensor comes from several sources: the real radiance of the object, the atmospheric scattering, sky and sun glint and the dark current of the sensor. Secondly, the dispersive element inside the sensor (usually a diffraction grating or a prism) could move during the flight, thus shifting the observed spectra on the wavelengths axis. Thirdly, to compute the reflectance, it is necessary to estimate, for each band, what value of irradiance corresponds to a 100% reflectance. We present here our calibration method, relying on the absorption features of the atmosphere and the near-infrared properties of common materials. By choosing proper flight height and flight lines angle, we can ignore atmospheric and sun glint contributions. Autocorrelation plots allow to identify and reduce the noise in our signals. Then, we compute a signal that represents the high frequencies of the spectrum, to localize the atmospheric absorption peaks (mainly the dioxygen peak around 760 nm). Matching these peaks removes the shift induced by the moving dispersive element. Finally, we use the signal collected over a Lambertian, unit-reflectance surface to estimate the ratio of the system's transmittances to its near-infrared transmittance. This transmittance is computed assuming an average 50% reflectance of the vegetation and nearly 0% for water in the near-infrared. Results show great correlation between the output spectra and ground measurements from a TriOS Ramses and the water-insight WISP-3.