Present paper summarizes the capabilities of the ocean retracking model developed at the Southampton Oceanography Centre to retrieve geophysical parameters (mainly, significant wave height, backscatter power and range), using the RA-2 Envisat 18-Hz averaged waveforms. This model is based on the use of the Maximum Likelihood Estimation. One of the most important characteristics of the model is that non-linear parameters can be added, in order to derive more information from the ocean waveforms. First results show that the linear model is able to retrieve accurate geophysical parameters from RA2, but the use of the non-linear model has to be considered with care. This work is part of the RAIES project, for the exploitation of the Envisat radar altimeter individual echoes and S-band data for ocean, coastal zone, land and ice/sea-ice altimetry.

An absolute sea-level monitoring and altimeter calibration permanent facility has been established on the isle of Gavdos, 50 km south of the island of Crete, Greece. This calibration/validation facility has been chosen because Gavdos is under a crossing point of the ground-tracks of Jason-1 satellite, and adjacent to an Envisat pass. Satellite altimeter missions are 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-vapour 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 have also been determined accurately. Comparison over the cycles 70 to 77 of the Jason-1 satellite indicate that its absolute mean bias for the sea-surface heights is 13 mm ± 20 mm. 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.

A Graphical User Interface (GUI) based software package has been designed to detect and statistically analyze illicit oil spills in European Seas. The first part of the tool allows for reading and processing of multiple formats of SAR satellite data for edge detection and shape analysis and stores the spill features in a database. The second part of the tool is used to display and perform statistical analysis on the previously established database.

An analysis of Synthetic Aperture Radar (SAR) images along with the analysis of velocity, salinity and temperature records taken at Camarinal Sill, the main sill of the Strait of Gibraltar, is intended to explain how the different hydrodynamic variables determine the wavelength of the internal waves generated in this location. The generation and subsequent propagation, toward the Mediterranean, of these waves produces an intense surface signature (surface slicks), which can be seen clearly in SAR images. The analysis procedure includes the application of wavelets analysis to determine the wavelength from the SAR images and an analytical model to compute the theoretical wavelengths as function of the hydrodynamic variables over the sill. Those results will be compared and discussed in this work.

A new method for simultaneous retrieval of aerosol properties and marine constituents in turbid waters is described. This method is an extension to turbid waters of an approach developed previously for simultaneous retrieval of aerosol properties and chlorophyll concentrations in clear waters. This extension is accomplished by employing near-infrared (NIR) channels not available on the SeaWiFS and MERIS instruments to help retrieve aerosol parameters over turbid waters. Optimal estimation theory is used to retrieve in-water parameters from multi- and hyperspectral information. Both forward and inverse modeling strategies will be discussed, as well as the uniqueness of the solutions, the information content available in multi- and hyperspectral data, and the error analysis approach. Our results indicate that it is important to use forward models that accurately treat the radiative transfer in the coupled (combined) atmosphere-ocean system, and to carefully select the most suitable bio-optical models for the in-water inherent optical properties (IOPs). Synthetic data, as well as multi- and hyperspectral images of data obtained over clear as well as turbid waters, are used to test the validity of the new retrieval approach.

Retrieval of surface properties of highly reflecting targets such as snow and ice is a challenging problem due to the influence of aerosols which varies considerably in space and time. Also, accounting for the bidirectional properties of a bright surface such as snow is very important for reliable retrievals. The main purpose of the work described in this paper is to explore the opportunities and possibilities offered by multi- and hyperspectral data such as those available provided by MODIS, GLI, the Advanced Land Imager (ALI), and Hyperion to retrieve reliable aerosol and surface properties. Over snow and ice surfaces these include aerosol optical depth and single scattering albedo, the mean size of snow grains and ice "particles" (inclusions), and the spectral and broadband snow/ice albedo. In particular the following question will be addressed: To what extent can multi- and hyperspectral data help improve our knowledge of snow and ice parameters that are important for understanding global climate change?

Conditions for primary production have been studied in Namibian waters during the period: October 1997-December 2003. The variables used have been: Sea Surface Temperature (SST) from the Advanced Very High Resolution Radiometer (AVHRR) and chlorophyll concentration from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery. Temporal, latitudinal analyses have been done for both variables in different spatial scales. Chlorophyll concentration presented a clear seasonality all along the Namibian coast. Summer and winter with maxima and minima respectively, these periods correspond to minimum and maximum upwelling intensity. These results indicate that primary production in this regions is not limited by nutrients, though it seems to be negatively affected by physical instability. Additionally north and south of 23°S a second peak of chlorphyll concentration is observed by at different seasons: autumn in the northern sector and spring in the souther one.

The development of algorithms for the production of reliable Sea Surface Temperature (SST) data sets from space borne infrared radiometers has been pursued by different agencies since late 1960's. The current state of the art in SST retrieval from space is limited by radiometer window placement, radiometer noise, quality of pre-launch characterization, in-flight calibration quality, viewing geometry and, mainly, atmospheric correction.The correction to eliminate the atmospheric effects is a critical and complicated step in the validation process, because although the satellite observations are approaching sufficient quality for routine use, unfortunately the thermal structure in the upper 10 m of the ocean is complex and highly variable, so SST may be significantly different depending on the vertical depth of the in situ measurement, the local time of day, local conditions at the air-sea interface and the instrument used; so in order to properly merge skin and bulk temperatures, daytime match-ups have been excluded from the validation process. In this context, the validation of the NOAA-AVHRR/3 and TERRA-MODIS atmospheric correction algorithms for the retrieval of sea surface temperature from the Canary Islands-Azores-Gibraltar area is performed by using more than 1500 in situ temperature measurements, derived from the ARGO Data Collection System and by the Oceanographic Service of the University of Las Palmas Gran Canaria, over the period from December 2000 to September 2003.

We present the results of recent experiments and analysis on the polarization discrimination technique developed by us to separate elastic reflectance and fluorescence components resulting from white light illumination of algae in seawater. The technique uses the polarized properties of elastically scattered light and unpolarized properties of fluorescence to separate the two. The approach was successfully applied to measurements on four types of algae of different sizes and shapes in the laboratory, with both polarized and unpolarized illumination sources. The procedure is shown to be effective for extraction of the chlorophyll fluorescence in the 685 nm region from reflectance of algae dominated by chlorophyll pigments with different angles of illumination for both polarized and unpolarized light sources, including sunlight. The results are compared with other methods for the estimation of chlorophyll concentrations, such as blue/green ratio, and the fluorescence line height above the baseline. We also report the results of experiments which examine the impact of surface roughness on the efficacy of the technique for measurements above the surface.

The Planetary Coral Reef Foundation is proposing to privately fund a Coral Reef Satellite Mission to perform a global mapping survey of shallow water coral reefs and monitor their health over a period of at least 5 years. Using available technology, but restricting the goals of the Mission to the limited objectives of finding and monitoring coral reefs, it is possible to design a coherent and cost effective flight system. We describe the general design of the mission and its components, giving particular emphasis to the science payload.

Satellite radiometers are widely used to detect oceanic structures which may allow for accumulations of pelagic fish. However, little information exists with respect to the possible use of spacecraft radar sensors in the detection and management of pelagic fisheries. This paper presents the satellite-derived ocenic events obtained from the Ekman Pumping (satellite wind scatterometer data derived), the Sea Level Anomaly, the Sea Surface Temperature and the Chlorophyll-a pigment images data sets, and how they relate to the albacore tuna fishing grounds distribution patterns in the North-East Atlantic. The statistical results show that catch per unit of effort (cpue) variability can be extensively explained by the satellite derived data base. The accumulation of CPUE records in specific zones is discussed too, in relation to the specific sensitivity of albacore due to the species' physiological thermo-conserving system. This paper emphasizes the importance of the combination of several satellite data sources in order to fully investigate mathematical relationships with the cpue.

Using 1.1 km resolution imagery from NOAA-12, -14, -16, and -17 recorded from April 2001 to May 2003 by "HAZO" HRTP mid-Atlantic satellite receiving station, 8-day average image are calculated to investigate AVHRR-derived SST distributions and associated dominant space and time scales around the Azores archipelago (34° to 42° N, 33° to 23° W). Eight-day average images together with zonal and meridional averages show a distinct seasonal cycle and typical gradi-ents, which emphasise the dual influence of the Gulf Stream and the Azores Current in this region. In late spring, iso-therms start moving to the north and retreat in early autumn. Low horizontal gradients are found during summertime, with warmer waters located to the south and west. Orientation of SST patterns changes with time from SW-NE (e.g. July 2001) to NNW-SSE (e.g. July 2002, August 2001 and 2002). The later orientation involves the sudden warming of the waters surrounding the northwestern group of islands of the Azores archipelago. This warming persists during 3 to 6 weeks with mean temperature differences of the order of 0.8° C. At a more local scale (2° x 2° in size) SST variability is also observed. In some cases, it is found that wind-driven coastal upwelling, a few km wide, occurs to the south of the islands during spring and summer months. Field data demonstrate that upwelling events increase local biomass. This result highlights the relevance of SST data to improve stock assessment and fishery management studies.

Cold and chlorophyll poor waters are used as a tracer of the cores where the deep waters touch the surface in upwelling areas of the Gulf of Cadiz. A very simple Lagrangian model of phytoplankton growth during the ascending of deep waters to the surface is implemented to diagnose vertical velocities in these cores. The diagnose combines daily images of chlorophyll and temperature to remotely sense upward velocities provided they have, in the Gulf of Cadiz, values above 9 m/d. The approach is valid for other areas subject to intense upwelling as far a local knowledge of nutrient and chlorophyll fields is implemented in the algorithms.

SST spatial variability in the Azores region is investigated using a method of least-square fit of a spatially averaged seasonal curve to monthly mean temperature variability curves at each pixel. The zero-order coefficient of the least-square fit is considered to represent a stationary anomaly field over the Azores region. The anomaly field reflects that the Mid-Atlantic Ridge (MAR) forms a barrier for heat exchange between the western and the eastern subtropical North Atlantic basins. Two SST frontal interfaces are identified to the east of MAR: the North Azores Flow (NAzF), which crosses MAR at 42-43oN, and the northern border of the Azores current. Several regions with significantly cooler surface waters are identified on stationary SST anomaly field. The temperature difference inside and outside of the cold-water pools sometimes exceeds 0.5oC. The most prominent pools are observed at the eastern flank of the MAR, between the Central and Eastern groups of the Azores islands and at a seamount chain south of the Azores. Those cooler water pools can be related to bottom-trapped advection, intensification of cyclones over bottom rises or enhanced tidal mixing near abrupt bottom topography.

Ocean Colour (OC) sensors have been primarily used in biological studies. More recently, OC information has been attracting the attention of oceanographers, as a potential method for revealing physical structures in the ocean. In this study, OC data obtained from SeaWiFS imagery is used, for the first time, to detect the weak Azores Current (AzC) and the associated Azores Front (AzF). Previous studies show that the frontal interface is well seen on SST imagery only during the cold season, while it is disguised during the warm season through the formation of a strong seasonal thermocline. With SeaWiFS imagery, the frontal interface is well identified around 34° N as an asymmetric zonally stretched band of higher near-surface chlorophyll a (CHL a) values north of the AzF, accompanied by a sharp decrease to the south. Quasi-stationary meanders, previously derived from SST fields for the same region, are also well observed in OC imagery. Monthly-averaged Chl a along a meridional cross-section shows that, from spring to autumn, the front is clearly visible. In winter, differences across the front are less pronounced, and the front is more easily identified on SST fields. OC gradients weaken to the east, corresponding to the general weakening of the AzC. In situ CTD data reveal a sharp and meandering thermohaline and dissolved oxygen front ocated at 33-34.5° N and 31° W. This study suggests that OC imagery, combined with other sensors, provide an important tool to investigate ocean dynamic variability, by helping to detect frontal zones with great precision.

Remote sensing techniques are a powerful tool for monitoring littoral zones. Optical sensors can be used to quantify water quality parameters such as suspended sediments. It is possible to estimate the Total Suspended Matter (TSM) concentration using multi-spectral satellite images. In order to extract meaningful information, the satellite data needs to be validated with in situ measurements. The main objective of this work was to quantify the TSM in sea breaking zone, using multi-spectral satellite images. A part of the northwest coast of Portugal, centered around Aveiro, was chosen as a test area. Several methodologies have been used to establish a relationship between the above sea water reflectance and the TSM concentration. Various field trips were done in order to simultaneously obtain water samples and reflectance measurements. A relationship between TSM concentration and reflectance was established for the range 400 - 900 nm. Data from Landsat TM, SPOT HRVIR and ASTER were calibrated and geometric corrected. The reflectance values were used to estimate the TSM concentration using the relationships established using the field measurements. The model coefficients and correlation factors, for identical bands on different sensors, presented a high similarity. The results have been incorporated in a Geographical Information System (GIS).

This paper addresses a particular detection problem related to the largest freshwater lake of Central and Western Europe, namely the Lake Balaton. The bed-silt of this shallow water lake (its average depth is 3.3 meters) contains several type of objects: industrial debris, historical vestiges, and in particular, an unknown quantity of unexploded ordnance from the second World War. It is important to localize and classify these objects for precise risk assessment and eventual later removal (not addressed in the paper). The bed-silt of the lake can be characterized as a mud having a light and constantly changing structure. It follows that the shallow water is almost always mixed with the mud. This admixture is constantly maintained by winds and navigating boats, hence the underwater visibility is close to zero during the most part of the year, especially in the depth range close to the bottom. Since the climate makes it possible, the authors propose a special way to explore the bed-silt of the lake, namely the use an autonomous vehicle on the frozen lake. Note that the ice prevents the wind and navigating boats to generate water movement and thus the mud is sedimented. This autonomous vehicle is equipped with a GPS based onboard localization system, with multiple sensor and recording equipment, and with a radio link to its command post. More details about the nature of objects to be detected as well as about the architecture of the detection and localization system are presented in the paper.

Development of robust protocols for use in mapping shallow water habitats using hyperspectral imagery requires knowledge of absorbing and scattering features present in the environment. These include, but are not limited to, water quality parameters, phytoplankton concentrations and species, submerged aquatic vegetation (SAV) species and densities, epiphytic growth on SAV, benthic microalgae and substrate reflectance characteristics. In the Indian River Lagoon, Fl. USA we conceptualize the system as having three possible basic layers, water column and SAV bed above the bottom. Each layer is occupied by plants with their associated light absorbing pigments that occur in varying proportions and concentrations. Phytoplankton communities are composed primarily of diatoms, dinoflagellates, and picoplanktonic cyanobacteria. SAV beds, including flowering plants and green, red, and brown macro-algae exist along density gradients ranging in coverage from 0-100%. SAV beds may be monotypic, or more typically, mixtures of the several species that may or may not be covered in epiphytes. Shallow water benthic substrates are colonized by periphyton communities that include diatoms, dinoflagellates, chlorophytes and cyanobacteria. Inflection spectra created form ASIA hyperspectral data display a combination of features related to water and select plant pigment absorption peaks.

Modeled hyperspectral reflectance signatures with water wave influences are simulated using an analytical-based, iterative radiative transport model applicable to shallow or deep waters. Light transport within the water body is simulated using a fast, accurate radiative transfer model that calculates the light distribution in any layered media and incorporates realistic water surfaces which are synthesized using empirically-based spectral models of the water surface to generate water surface wave facets. The model simulated synthetic images are displayed as 24 bit RGB images of the water surface using selected channels from the simulated synthetic hyperspectral image cube. We show selected channels centered at 490, 530 and 676 nm. We also demonstrate the use of the model to show the capability of the sensor and image modeling approach to detect or "recover" known features or targets submerged within or on the shallow water bottom in a tidal inlet area in Indian River Lagoon, Florida. Line targets are simulated in shallow water and indicate the influence of water waves in different water quality conditions. The technique demonstrates a methodology to help to develop remote sensing protocols for shallow water remote sensing as well as to develop information useful for future hyperspectral sensor system developments.

Sea surface temperature (SST) is an important parameter for the study of oceanic environment. In this study we used the SST data derived from the Advanced Very High Resolution Radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) series satellites to study the SST trends in the waters adjacent to Taiwan from 1982 to 2003. The Empirical Mode Decomposition (EMD) method was employed to retrieve the trend. Results show that the SST in the waters adjacent to Taiwan had a warming trend of about 0.50° C/decade and 0.47° C/decade in the Taiwan Strait and in the Kuroshio region east of Taiwan, respectively. The warming trend in winter is much higher than that in summer. This could be the reason why the people who live in Taiwan felt warm winter in recent years. The waters adjacent to Taiwan are also located at the high warming trend areas in the world. They are much higher than the mean trend of global ocean. Not only the waters around Taiwan are in the high warming areas, but also the oceans around China are. The high warming areas in the China oceans seem to be related to the distribution of atmospheric aerosols in the western Pacific Ocean.

The sea surface temperature (SST) front we considered here is the boundary separating the northern colder water and southern warm water in the Taiwan Strait (TS). It always coincides with the northern edge of the permanent warm current along the deep Peng-Hu Channel northward into the TS. The NOAA/AVHRR SST data during 1997-2000 is used to see the variability of this SST front. From gradient empirical orthogonal function (GEOF) analysis of the SST data we found that the SST front is weaker in summer and much stronger in winter. Meanwhile, the SST front was weaker in 1997 El Nino summer than 1998 La Nina summer, while stronger in 1997/1998 El Nino winter than 1998/1999 La Nina winter. The ERS-2 scatterometer wind stress data is also applied in this study, it is suggested that the wind variation seems to be the main factor to induce the above variation of the SST pattern in the TS.

It is becoming more important to understand the remote sensing systems and associated autonomous or semi-autonomous methodologies (robotic & mechatronics) that may be utilized in freshwater and marine aquatic environments. This need comes from several issues related not only to advances in our scientific understanding and technological capabilities, but also from the desire to insure that the risk associated with UXO (unexploded ordnance), related submerged mines, as well as submerged targets (such as submerged aquatic vegetation) and debris left from previous human activities are remotely sensed and identified followed by reduced risks through detection and removal. This paper will describe (a) remote sensing systems, (b) platforms (fixed and mobile, as well as to demonstrate (c) the value of thinking in terms of scalability as well as modularity in the design and application of new systems now being constructed within our laboratory and other laboratories, as well as future systems. New remote sensing systems - moving or fixed sensing systems, as well as autonomous or semi-autonomous robotic and mechatronic systems will be essential to secure domestic preparedness for humanitarian reasons. These remote sensing systems hold tremendous value, if thoughtfully designed for other applications which include environmental monitoring in ambient environments.

Operational oceanography requires availability of remotely sensed data, for example sea surface temperature (SST), in near realtime (NRT). A system is presented that makes use of a combination of state of the art NASA Pathfinder SST (PFSST) algorithm and cloud detection procedures both adapted to operate in NRT. A novel cloud detection algorithm that makes use of a reference image based upon recent SST fields recovers data over coastal areas affected by sharp SST fronts that are discarded by the standard PFSST quality flag. The resulting increased SST coverage is visually checked, to remove residual cloud contamination, by a trained analyst prior to input to the objective analysis package in turn adapted for satellite-derived SST observations. The output daily gridded data in which the gaps due to clouds have been filled by the optimal interpolation module are assimilated into the Mediterranean Forecasting System Toward Environmental prediction (MFSTEP) ocean forecasting system on a weekly basis.