The scatterometer on-board of the ERS spacecraft is range-gated, in opposition to Seasat/Nscat scatterometers that are Doppler filtered. It can thus admit some Doppler frequency shift in the returned echo. However, the bandwidth of the filter on-board of the ERS satellite limits the Doppler shift that can be tolerated on the returned echo data. For these reasons, the ERS spacecraft needs to be yaw-steered in order to minimize the residual Doppler shift. Due to a malfunction of several of the on-board gyroscopes used to govern the attitude of the ERS-2 spacecraft, precise yaw steering of the spacecraft cannot be guaranteed anymore. This paper reviews modifications to the existing processing chain that are needed to be able to process the data acquired by the ERS-2 spacecraft in degraded attitude mode, so called zero-gyro mode (ZGM). The main modification is the introduction of the on the fly estimation of the yaw angle as input to a model of the acquisition geometry. This paper also details how the yaw angle is estimated from the received raw data by measuring the residual Doppler frequency shift. Finally, several improvements such as the impact of an increased spatial resolution of the backscattering coefficients are also discussed.

Due to gyroscopes malfunctions, the ERS-2 spacecraft cannot accurately be yaw steered. Moreover, the actual yaw angle of the spacecraft is unknown. Since the yaw angle is not known in advance and not periodic, the look-up tables-based original scatterometer processor is not able to compute accurate values for the backscattering coefficients from the measurements made. This implies the need for an upgraded wind scatterometer ground processor in order to obtain accurate backscattering coefficients. Moreover, the upgraded processor includes several other enhancements. This paper presents the results of the validation of the upgraded processor. The validation of the geometrical model is performed by comparing geometric parameters such as the incidence angle and the sub-satellite track heading. The radiometric performance of the upgraded processor is first evaluated with data acquired in nominal attitude, by comparing the backscattering coefficients. The radiometric performance of the upgraded processor is then further assessed with data acquired in degraded attitude. This is only possible over the calibration test site and over other selected land areas.

The spaceborne scatterometer is a microwave radar that provides high precision radiometric measures of the normalized radar cross section σ⁰ of the ocean surface. The backscatter is affected by the superficial roughness that is in turn related to the local wind. Since microwave wavelengths are used the scatterometer, at first order, can be meant as an instrument which provides measurements independent of clouds and sun illumination therefore it is able to observe the internal structure of a Tropical Cyclone (TC). The relationship between the σ⁰ and the surface wind filed is described by a geophysical model function (GMF). The model used in the ERS scatterometer processing is the well-known semi-empirical model CMOD4. Unfortunately this model is not tailored for high wind speeds, such as the case of TCs. This fact causes a poor quality in the wind field estimated through the scatterometer data acquired over a TC. In this paper we describe a study in view of a possible extension of the CMOD4 for high wind speeds. The study has been based on the ERS-2 σ⁰ measurements relevant to six selected TCs and the corresponding wind speeds obtained by employing the Holland model. We have selected six TCs and for each one we have developed a 3D wind speed pattern making use of the wind speed available through the NHC (National Hurricane Center) warnings. The obtained wind speeds are then correlated to the σ⁰’s acquired over these six TCs. The results obtained in this work support the need to extend the CMOD4 model.

A new inversion procedure to estimate the near-surface wind field from scatterometer measurements is hereafter presented. It is an evolution of the point-wise inversion scheme actually employed by the ASI (Italian Space Agency) at the I-PAF (Italian Processing and Archiving Facility). A set of experiments are illustrated.

An absolute sea level monitoring and altimeter calibration permanent facility is being established on the isle of Gavdos, south of the island of Crete, Greece. This calibration facility has been chosen because Gavdos is under a crossing point of the ground-tracks of TOPEX/Poseidon and Jason-1, and adjacent to an ENVISAT pass. Satellite altimeter missions will be evaluated at that site using external measurements from tide gauges, GPS, a DORIS beacon, meteorological sensors, wave height sensors, airborne campaigns for gravity and sea surface topography, water vapor radiometry, solar atmospheric spectrometry, GPS buoys, altimeter transponder, Satellite Laser Ranging, etc. The mean sea level and the earth's tectonic deformation field in the region will be also determined accurately. The GAVDOS project has started in December 2001 and has been in the context of an international calibration/validation effort of the Jason-1 Science Working Team. This paper describes the objectives, current status and future plans for the establishment of the GAVDOS calibration facility for satellite altimeter missions.

We have used the first three years of ERS-2 altimeter data (May 1995 - June 1998) in order to analyse the space-temporal ocean response to atmospheric pressure variations in the three main ocean world basins: Atlantic, Indian and Pacific. We have also quantified the magnitude of the departures of this response from the hypothetical barometric factor (-0.995 cm/mbar), commonly applied to altimeter data records to eliminate the effect of the atmospheric pressure variations in the ocean (Inverse Barometer Correction). From the results obtained, we have found a different behaviour in the Atlantic Ocean with respect to the other two basins, as far as the magnitude of the barometric factor is concerned. Considering that we have estimated the meridional response to atmospheric pressure variations by applying the collinear track and the crossover track methods, the Atlantic Ocean response is quite similar to the one deduced from the isostatic assumption at all latitudinal bands. Nonetheless, Indian and Pacific Oceans show important departures from the hypothetical value at low latitudes. In order to understand why the Atlantic Ocean response is different from the one obtained in the others two, we can infer some explanations but it seems that the different climatology in the basins could be explaining the results obtained, especially the effect of winds.

The use of image segmentation and object feature extraction in order to classify SAR image objects into oil spill or other features (oil slick look-alikes), it is widely acceptable in oil spill detection research. For this purpose, a number of features (geometric, surrounding, backscattering, etc.) are usually calculated and introduced in a decision support procedure. The aim of the present study is presentation, analysis and evaluation of the above features in order to produce general rules adequate to identify oil spills in any SAR image. SAR image processing is based on a new multi-segmentation technique. As a first step, image objects in different scales are extracted using the multi-segmentation procedure. Following segmentation, a hierarchical network of image objects is developed, which simultaneously presents object information and fuzzy rules for classification. In experiments implemented in SAR images, the method developed has successfully detected oil spills and look alikes. Texture behavior most contributes to detection (texture characteristics 80%), followed by physical behavior (actual backscatter characteristics 53%, spot surroundings 26 %) and finally geometry behavior (geometrical characteristics 2%).

The Laser Induced Fluorescence (LIF) technique has been widely employed for the study and the monitoring of the phytoplanktonic population in the marine environment. Herein a method for the characterization of different phytoplanktonic species by means of a high spectral resolution lidar fluorosensor is presented. The method is based on the detection of the changes in the peak position of the fluorescence of the chlorophyll a that is contained in all phytoplanktonic species. These changes are probably due to the proteic compounds that are present together with the chlorophyll in the thylakoid membranes within the chloroplasts and that vary with the phytoplanktonic species. The main advantage is that this method does not require the presence of characteristic fluorescence features of other light harvesting pigments, such as carotenoids or phycobilines, so that it can be used also with species where only chlorophyll fluorescence is present. Moreover, the light harvesting pigments usually show a weak fluorescence because of the strong resonant coupling between them.

This paper describes an ocean lidar system and measurements. The lidar transmitters include a tunable visible laser and IR lasers. The tunable laser transmitter operates between 470 nm and 540 nm. The IR lasers operate at 904 nm and 1064 nm wavelengths. This lidar uses receivers that detect both elastic and in-elastic scattering signals from the atmosphere and water columns. For elastic scattering measurements, the receivers are photo-detectors that couple to multi-channel waveform digitizers. For in-elastic scattering measurements, this lidar uses two different receiver configurations. The first receiver configuration uses a line scan spectrometer that couples to a boxcar integrator. This receiver configuration collects laser-induced spectra as a function of laser transmitter wavelengths by scanning the spectrometer wavelengths during the lidar measurements. The second receiver configuration uses an imaging spectrometer to collect laser-induced spectra in spatial and spectral dimensions. During lidar measurement of the water columns, a PC controls the spectrometers, the waveform digitizer, and the boxcar integrator, using commercially available and custom designed computer interface circuits. This paper describes these lidar transmitters, lidar receivers and data acquisition hardware. The lidar measurements of the ocean water described in this paper use various platforms. These platforms include airborne, shipboard, shore-based and pier-based platforms. These lidar measurements include atmospheric, ocean surface and water column measurements. This paper describes the results of these measurements and the potential applications for marine and coastal environments.

The paper is devoted to study the seasonal behavior of the sea surface pigments concentration in the area of the West Indian Ocean. The analysis is based on the SeaWiFS images acquired at the Broglio Space Centre (BSC, Kenya coast, 40° E, 3° S) since June 2000. The L-band system used for acquiring SeaWiFS images is also used for the acquisition of NOAA images that allow the estimate of Sea Surface Temperature (SST) and the retrieval of other physical parameters (ATOVS) useful for a better understanding of the phytoplankton cycles. SST estimate from AVHRR data is based on an algorithm developed at CRPSM. Information on atmosphere conditions in the region of interest are obtained from ATOVS data using a processing scheme of the AAPP-ICI tool adapted to the Malindi station. The accuracy of these data is checked and improved using “in situ” periodic balloon-based atmospheric profiles. The combination of ocean color data from SeaWIFS with the oceanographic satellite-derived available data allows a better description of the phytoplankton cycle and, possibly of the ocean productivity.

In this paper, we examined the spatial dynamics of chlorophyll-α and SST of a bay in the south-western Scottish coast through analysis of a series of Airborne Thematic Mapper images that were acquired on two dates throughout an ebb tide. Changes in patterns of chlorophyll-α and SST were determined through two complimentary statistical procedures: firstly, by geostatistics (variogram analysis), which provided information on changes in the scale-dependency of the variation; and secondly, by maximum cross correlation, which provided information on the displacement of pattern at a local scale. Geostatistics and maximum cross correlation were effective for quantifying spatial dynamics, but qualitative interpretation was also necessary. Complex spatial dynamics were found over a wide range of spatial and temporal scales, associated with the creation and dissipation of eddies, the convergence and divergence of fronts, and the creation of geostrophic boundary currents. All these dynamics were superimposed on the synoptic tidal flow. Patterns of chlorophyll-α differed markedly from those of SST, indicating the non-conservative aspect of algal populations and the 3-dimensional aspect of the velocity field.

In this paper, a neural network model, realizing a function assigning an estimate of the phytoplankton content in the ocean to several remote sensing acquisitions, is presented. This inverse problem is first shown to be a family of inverse subproblems, all of the same kind and continuously parameterized by the geometrical parameters defining the viewing geometry, thus allowing a two-steps modeling process. The central point of the method is that reflectances and geometrical parameters are processed in a different way. The first ones are considered as random variables while the seconds play the role of deterministic parameters. First, a set of local regression phytoplankton concentration estimators, i.e. small size neural networks, is constructed, locality being defined in the geometrical parameters space. Under some non restrictive hypotheses, each of those local models is shown to be optimal. Further, a lower bound on the expected accuracy is given. Secondly, a global model is constructed from a set of local models which in fact amounts to be a neural network, the parameters of which are continuous functions of the geometrical parameters. The model has been tested on a wide simulated data set of about 7 million points for different geometrical configurations, different atmospheric conditions and several wind speed and direction values. It has shown very good results for a large set of geometrical configurations. Moreover, many much results have been obtained with this model than with global approaches based on multilayer perceptrons and radial basis functions neural networks. The presented methodology is also a promising direction for the elaboration of complex models from a set of simpler ones.

Sea ice in Canadian waters is monitored through an operational program conducted by Environment Canada. The program uses several remote sensing data sources and outputs a daily ice chart which is disseminated to marine users. The chart contains information on operational sea ice parameters; namely ice type, thickness, mechanical strength and surface roughness and topography. Data fusion techniques are being developed to assist ice information retrieval from remote sensing data, particularly radar imagery data. This paper presents a new data fusion method to combine co-located and co-incident data from radar, optical and passive microwave sensors into an ice parameter retrieval scheme. Examples are presented to show how ice surface temperature (derived from infrared sensors), microwave brightness temperature (observed from microwave radiometer) and radar imagery (from RADARSAT) can be combined to improve retrieval of ice types and thickness. In addition to ice parameter retrieval, the method facilitates analysis of sub-pixel information from a coarse-resolution data (e.g. SSM/I) using a background of fine-resolution data (e.g. RADARSAT). The method allows combining multi-sensors data in physical models to retrieve surface parameters that cannot otherwise be retrieved from a single sensor observations

In this paper we show the results related with the possibility of measure the electrophysical properties of Oceans with foam by using the passive remote sensing system. To solve the problems of remote sensing of different surfaces based in the use of the radiometers, it is necessary to establish multiparametric measurements. By using of multichanel radiometers, we can receive signs of different frequency, polarizations, directions. The algorithms of processing of thermal radiation used in terrestrial surfaces are also shown. These algorithms have been synthesized base on the maximum verisimilitude criteria. The algorithms include the operations of statistical processing of characteristic thermal radiation in order to receive the statistical characteristics of the electrophysical parameters of the Ocean. To reach it regressive model of the Ocean with foam, is analyzed in an temperature interval of 273-310 K, with different percent of salts and to different wind velocities. We analyzed the polarization type, monitoring angles, height of the antenna in order to the errors of measurements be minimum. These recommendations can be useful for planning aerospace experiments for studding the Ocean. This information can be obtained by using the inverse elements of the Fisher matrix.

Many studies indicate that the atmosphere is a significant and in some cases the dominant pathway by which specific elements are transported from the land to the open sea. The Mediterranean Sea is a semi-enclosed basin, that continuously receives anthropogenic substances from the industrialized European country, and sporadically, from the arid region of the Sahara desert, nearly the 90% of the total amount of aerosols that reach the sea surface. The Mediterranean is a predominantly oligotrophic basin with areas of high productivity limited to areas influenced by runoff, rivers or upwelling. In situ biogeochemical measurements indicate that atmospheric deposition can induce significant productivity changes. The present work aims to use SeaWiFS satellite data and the SKIRON atmospheric model to provide an estimate of the temporal and spatial variability in the atmospheric forcing (dust events) and in the marine biological response (blooms), and to evaluate the overall contribution of these Saharan dust events to the fertility of the Mediterranean Sea. Although biological dynamic is meanly driven by the circulation features of the basin, results show that the atmospheric nutrient deposition gives some evident response in the biological activity.

Modeled hyperspectral reflectance signatures just above the water surface are obtained from radiative transfer models to create synthetic images of the water surface. Images are displayed as 24 bit RGB images of the water surface using selected channel. Comparisons are made in this paper between a hyperspectral Monte Carlo and a hyperspectral layered analytical model of radiative transport applicable to shallow water types. Images at the selected wavelengths or channels centered at 490, 530 and 680 nm suggest the two models provide the same results when displayed as RGB images. The most sensitive parameters for generating realistic images are water depth and bottom reflectance in clean natural, optically shallow waters. The images clearly demonstrate the need importance of detailed and accurate water depths.

The purpose of this paper is to present simulation results of a thermal sub-model developed for the Florida Tech UTC-M sea-breeze model. The insertion of this thermal radiative model into the atmospheric planetary boundary layer model, allows calculation of time dependant heat flux boundary conditions at the air-land boundary that are derived from satellite data such as AVHRR and MODIS. The improved UTC-M planetary boundary layer model with this thermal sub-model is used to demonstrate the use of thermal inertia to help estimate heat fluxes at the land-air interface which in turn influences convergence and vertical fluxes, which then affects mesoscale meteorological wind and convergence predictions. We present thermal radiative model simulations and associated results due to the influence of the parameterization of the net surface radiation and thermal inertia using wavelength or channel specific data from MODIS and AVHRR satellite sensors. Results are presented for cloudless sky conditions.

In this study we analyse thermal satellite images relative to years 1997-2000, to infer cold filaments and surface jets dynamics in the Mediterranean Sea. The main zones in which these phenomena are seen to occur are characterised by upwelling and/or the funnelling of strong cold winds by somewhat irregular coastal topography. Indeed, intense air-sea interaction in the coastal zone are known to generate a particularly strong input of potential vorticity into marine water, and this in turn gives origin to upwellings, cold filaments and jets. In the Mediterranean Sea, the geographical zones more "rich" in these jets are the two lobes of the southern Sicilian coast, the sea off Olbia in Sardinia, that South of the island of Crete, where a particularly intense large scale turbulence field is evident, and the Balkanic coast of the Adriatic sea. In addition, the theoretical analysis of these jets' evolution using a modern version of the potential vorticity conservation, valid even if friction and entrainment are to be considered , gives some insight into these systems' dynamics.

This paper describes the radiative transfer of the sun’s electromagnetic energy utilizing a solution to the two-flow irradiance equations that generates fast and accurate estimates of light distributions in any layered media, such as water with depth dependent concentrations of water column constituents. The layered model is designed to generate synthetic water surface reflectance signatures and associated synthetic images, in the presence of depth dependent water constituents, various bottom types, and variable water depths. The layered model accounts for specular (collimated) irradiance below the water’s surface and utilizes boundary conditions that allow the absorption, backscatter, beam attenuation, and conversion (from specular irradiance to diffuse irradiance) coefficients to vary as a function of depth. In addition, the model allows one to compute the influences of submerged targets, bottom types or unique submerged targets or water column layers with defined by their reflectance signatures of unique absorption and backscatter characteristics. Model simulations are presented to demonstrate the utility of the model for development of remote sensing algorithms for use in coastal and marine water types.