This PDF file contains the front matter associated with SPIE Proceedings Volume 7473, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Measurements of particulate absorption, namely absorption by phytoplankton and non-algal particles (NAP) are important components in bio-optical models; only a few studies have been reported for the southeastern Bering Sea. This study analyzes variability in spectral particulate absorption (a_P(λ)) including phytoplankton (a_PHY(λ)) and NAP absorption (a_NAP(λ)) from in-situ data in conjunction with ocean color satellite data (MODIS - Moderate Resolution Imaging Spectroradiometer) along four transects in the southeastern Bering Sea shelf during a cruise in July 2008. Results obtained indicate that surface a_PHY(λ) at 443 nm is higher in middle shelf near the Pribilof Islands with a_NAP(λ) decreasing from north to south across the shelf. Greater than 90% of variability in a_P(λ) could be explained by a_PHY(λ) indicating biogenic matter dominates changes in particulate absorption. Good correlations were found between a_P(λ), a_PHY(λ) at 443 nm and chlorophyll-a (R² = 0.65 and 0.80, respectively). a_PHY(λ) spectra were highly variable, with larger variability in blue than red part of the spectrum, indicating change in pigment composition or package effect. MODIS satellite derived aPHY(λ) using quasi-analytical algorithms (QAA) revealed patterns similar to in-situ absorption data for a major part of the study area. Inconsistencies seen between in-situ absorption and QAA retrieved satellite absorption could probably be attributed to temporal differences between in-situ data collection and satellite overpass.

Subject of the paper is the presentation of the potential of use of multispectral remote sensing data for the investigation of water quality of large water basins on the example of the monitoring of the Baltic Sea with MERIS data. An interpretation and inversion scheme for optical satellite data over water has been developed to be used in several national and international projects to monitor different aspects of water quality. The resulting "Principal Component Interpretation" algorithm allows an optimized estimation of water constituents: chlorophyll pigment concentrations, suspended matter concentration and yellow substance concentration as well as optical properties of the water body. From these are derived secondary parameters like water transparency. In the frame of the international ESA MARCOAST project this interpretation scheme was developed for a regular (daily) monitoring of the Baltic Sea. Results are uniformly mapped images and concentration maps of the Baltic Sea area from which are additionally derived weekly, monthly and seasonal means. The Principal Component Interpretation belongs to the class of model based multivariate interpretation schemes and is closely related to Neural Networks techniques, but bases on a completely different training procedure. It makes use of an optimal information redistribution between the spectral bands and relates them to the water constituents. This kind of estimation allows an simultaneous estimation of expected global estimation accuracy. The regular monitoring is accompanied by the survey of in-situ ground measurements, which can be used for validation.The paper will present the bio-optical model which is used for the interpretation of Baltic Sea water. The basics of the interpretation scheme basing on principal component analysis will be explained and results of the monitoring of different products will be discussed on examples of a time series in 2008, showing the development and movement of algae blooms, together with other constituents. The obtained results are critically compared with available ground measurement.

Harmful Algal Blooms (HABs) can lead to severe economical and ecological impacts particularly in the coastal areas and can threaten human and marine health. About three-quarter of these toxic blooms are caused by dinoflagellates species which are well known to migrate vertically. During the day, they migrate up to the surface for photosynthesis, and consequently, their dense aggregations produce strong bio-optical signals that are detectable by space borne optical satellite sensors. In this study we use our recently developed low backscattering bloom detection technique, the Red Band Difference (RBD), to detect various dinoflagellates blooms using both MODIS (Moderate Resolution Imaging Spectroradiometer) and MERIS (Medium Resolution Imaging Spectrometer) data and present the results which confirm the potentials of the RBD technique. Here we present examples of bloom detection in waters off Gulf of Mexico, Monterey Bay, South Africa, and East China Sea.

QuikSCAT satellite based vector wind data were used to examine wind influence on SeaWiFS derived chlorophyll a (chlorophyll) surface distribution in the northern Gulf of Mexico waters influenced by the Mississippi and Atchafalaya Rivers, the largest in North America. Short-term satellite derived wind field revealed a systematic shift in direction and amplitude of the winds during a cold front passage in March 2002 that strongly influenced the surface chlorophyll distribution. Both the offshore extent and westward transport of enhanced surface chlorophyll biomass increased following the frontal passage. Monthly surface wind stress derived from the 12.5 km high resolution QuikSCAT winds mapped along with SeaWiFS derived surface chlorophyll during a low flow and a normal river discharge year in 2000 and 2001 indicated the dominant role of river discharge in influencing the concentration and extent of chlorophyll in the plume and inner shelf waters. However the magnitude and direction of wind stress strongly influenced the plume orientation and the cross-shelf extent of a coastal band of elevated chlorophyll. Wind stress also influenced the offshore cross-shelf variability in surface chlorophyll distribution.

The focus of this work is on the dependence of in situ hyperspectral and multiangular polarized data on the size distribution and refractive index of the suspended particles. Underwater polarization measurements were obtained using a polarimeter developed at the Optical Remote Sensing Laboratory of the City College of New York, NY. The degree of polarization (DOP) of the underwater light field in coastal environments was measured and the water-leaving polarized radiance was derived. In-water optical properties were also measured with an ac-9 (WET Labs). Absorption and attenuation spectra are then used to derive information on the dissolved and suspend components in the water medium which are used in a vector radiative transfer code which provides the upwelling radiance. The model was run for various values of the refractive index of mineral particles until the modeled DOP matched the measured one. The relationship between the intensity of the maximum of the DOP and both the refractive index of the mineral particles and the shapes of their size distributions is analyzed in detail.

Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth's climate and ecology. Typical ocean sensing is done with satellites or in situ buoys and research ships which are slow to reposition. Cloud cover inhibits study of localized transient phenomena such as Harmful Algal Blooms (HAB). A fleet of extended-deployment surface autonomous vehicles will enable in situ study of characteristics of HAB, coastal pollutants, and related phenomena. We have developed a multiplatform telesupervision architecture that supports adaptive reconfiguration based on environmental sensor inputs. Our system allows the autonomous repositioning of smart sensors for HAB study by networking a fleet of NOAA OASIS (Ocean Atmosphere Sensor Integration System) surface autonomous vehicles. In situ measurements intelligently modify the search for areas of high concentration. Inference Grid and complementary information-theoretic techniques support sensor fusion and analysis. Telesupervision supports sliding autonomy from high-level mission tasking, through vehicle and data monitoring, to teleoperation when direct human interaction is appropriate. This paper reports on experimental results from multi-platform tests conducted in the Chesapeake Bay and in Pittsburgh, Pennsylvania waters using OASIS platforms, autonomous kayaks, and multiple simulated platforms to conduct cooperative sensing of chlorophyll-a and water quality.

Our previous studies showed that the Fluorescence Line Height (FLH) product, which uses 3 NIR bands at 667, 678, and 746 nm on the MODerate-resolution Imaging Spectroradiometer (MODIS) sensor, and similar bands on MERIS sensor, is not reliable in coastal waters because of a peak in the elastic reflectance spectra which occurs due to the confluence of chlorophyll and water absorption spectra and which overlaps spectrally the chlorophyll fluorescence. This combination of two overlapping peaks makes fluorescence signal retrieval inaccurate. As a consequence, the present FLH algorithm significantly underestimates fluorescence magnitudes in coastal waters. To overcome this problem, we introduce a new and more accurate approach for the retrieval of FLH in turbid waters by the MODIS sensor, which exploits the correlation between the blue-green and red bands reflectance ratios. We show that by making use of the combined remote sensing reflectance's (Rrs) at 488nm, 547nm, 667nm and 678nm we can retrieve fluorescence accurately in case 2 waters even for low fluorescence quantum yield when fluorescence magnitudes are low. The derivation and validation of our algorithm was performed using extensive synthetic datasets which cover a large variability of parameters typical of coastal waters: with CDOM absorption at 400nm 0-2 m^-1, mineral concentration 0-5g/m³ and chlorophyll concentration of 0.5-100 mg/m³. In addition, we applied this proposed algorithm to MODIS satellite data and compared it with the traditional FLH algorithm.

Satellite altimetry has proved successful as a global tool for monitoring sea surface height, significant wave height and wind speed. Nevertheless, a global archive of 17 years of raw data from a series of missions is presently unexploited around the world coastline. This huge amount of unused data can be re-analyzed, improved and more intelligently exploited, possibly promoting coastal altimetry to the rank of operational service. Operational users interested in monitoring sea level change and wave conditions in the coastal zone (e.g. for coastal erosion, sediment/pollutant transport applications) still rely on sparse (and expensive) in situ monitoring stations or poor models. In this work we present a new approach in the exploitation of altimeter data in the coastal zone (currently impeded by unsuitable waveform retracking scheme and coarse along-track spatial sampling in the coastal zone, among others). The objective of this paper is to show how a new, robust, retracking algorithm is able to retrieve with high accuracy physical ocean parameters from altimeter waveforms in the coastal zone. The main focus lies on retrieving sea surface height in the coastal zone with the same precision as is achieved in the open ocean. In addition, the retrieval of more accurate altimeter-derived wave products in the coastal zone is also important as waves are more directly relevant to many operational applications in the coastal zone.

The main application of a scatterometer is the determination of the wind speed and direction at the sea surface. This is achieved by measuring the radar backscattering coefficient in three different directions and inverting these measurements using a geophysical model function (GMF). The scientific value of the data is directly related to the quality of the radiometric calibration. There are currently two european C-band scatterometers operating, one on-board the ERS-2 spacecraft launched in 1995 and the other on-board METOP-A, launched in 2006. The similarity of the two scatterometers is an opportunity to ensure the continuity of more than 15 years of global scatterometer measurements. To achieve the consistency of the backscattering coefficients data sets, required for long-term climate studies, an accurate cross-calibration is vital. The cross-calibration is made possible since the two spacecrafts operate simultaneously from 2006 up to now. As the backscattering coefficients measured by the scatterometers depend on acquisition time, location on the ground and on the geometry of the measurements (incidence and look angle), a direct comparison of measurements made by both instruments is practically impossible. In particular cases, models can be used to cope with measurement differences. On the rain forest, assumed to be time-invariant, homogeneous and isotropic, the backscattering coefficient depends only on the incidence angle, and the constant gamma model can be used to cope with the incidence angle effects. On some ice covered areas (e.g. Greenland and Antarctica), assuming that the ice surface is isotropic, the ice line model can be used. It is a function of incidence angle and ice age and depends on the location. On the ocean, which is inherently not stable in time, the CMOD5 GMF is used. CMOD5 relates the observed backscatter to the geophysical parameters which are the wind speed and wind direction. Using the last model, measurement biases can be assessed making simultaneous observations unnecessary.

The dedicated calibration site for satellite radar altimeters in Gavdos has been operational as of 2004. The small island of Gavdos is located along a repeating ground track of Jason satellites (crossover point No 109 ascending and No. 18 descending pass and adjacent to Envisat), and where the altimeter and radiometer footprints do not experience significant land intrusion. The purpose of such permanent Cal/Val facility is to calibrate the sea-surface height and ancillary measurements made by the satellite as it passes overhead, by using observations from tide gauges, GPS, DORIS and other sensors directly placed under the satellite ground tracks. The successful launch of Jason-2 satellite (20 June, 2008) initiated its calibration-validation phase. This was achieved having the two satellites flying with less than one minute difference and in the same orbit. Using the Gavdos calibration facility the following have been determined: (1) the absolute altimeter bias of Jason-1 satellite for the cycles 209-259; using GDR-C data; (2) the absolute altimeter bias of Jason-2 satellite for the cycles 2-28 using GDR-A data ; (3) the inter- mission bias for the period July 2008 - January 2009. The expansion of the Gavdos Cal/Val facilities with the deployment of a new site in the south of Crete and along pass No. 109 is also presented in this work.

The MIRAMER field campaign took place in the Mediterranean Sea during May 2008, both ground-based and on board an oceanographic ship. Radiometric datasets along with the associated environmental measurements have been collected in various environmental and observation conditions. It is dedicated to the validation of the sea surface optical properties model implemented in the MATISSE-v2.0 code. This analytical sea surface optical properties model in the infrared band is described. It allows the introduction of multiresolution in the simulated field-of-view answering the need in computed images including any observational configurations. It is valid for fully-developed seas, includes shadowing and hiding functions but not breaking and foam nor multiple reflections. First comparisons between simulations and measurements are presented in this paper.

This paper describes the results of modeling the water wave surface and underwater light field as influenced by water waves using a Monte Carlo model (MCHSIM). Model and sensor data related to water column properties and benthic properties that influence the light upwelled from below the water - as observed from a sensor looking from below or above the water surface is presented. Synthetic image results using Monte Carlo techniques show the influence of water waves upon subsurface shape factors and these factors can be used in shallow water remote sensing algorithms that are based on underlying analytical models. The upwelling angular distribution of light is calculated from the model and results shown for 490 nm. The upwelling and downwelling shape factors are shown from model runs which compare the results with solar zenith angle for nadir viewing geometry, and for realistic water surface wave facets. It is clearly shown that shape factors are strongly dependent upon not only viewing geometry and zenith angle of the sun, but also upon water waves that can focus and defocus radiance entering a wind roughened water column and influence the shape factors due to the scattering lobe effect. This paper presents results quantifying the magnitude of water effects upon the upwelling and downwelling shape factors in a systematic and quantifiable manner at 490 nm and demonstrates the utility of the model to assess the influence of water waves in a full 3-D Monte Carlo hyperspectral synthetic image cube model that accounts for adjacency effects.

Hyperspectral imagers tend to have lower spatial resolution than multispectral ones. This often results in a (sometimes difficult) trade-off between spectral and spatial resolution. We have developed a technique, called CRISP, that combines low-resolution hyperspectral data and high-resolution multispectral data to produce high quality, high-resolution hyperspectral data. This technique shows good quantitative performance when applied to realistic applications such as land cover estimation and anomaly detection. As a test of this technique, we have performed an experiment using HyMap hyperspectral data and multispectral instruments over the coast waters of Oahu, Hawaii. The accuracy of the CRISP sharpening approach when used for coastal applications such as depth mapping is assessed.

Optical remote sensing has been used to map and monitor water quality parameters such as the concentrations of hydrosols (chlorophyll and other pigments, total suspended material, and coloured dissolved organic matter). In the inversion / optimisation approach a forward model is used to simulate the water reflectance spectra from a set of parameters and the set that gives the closest match is selected as the solution. The accuracy of the hydrosol retrieval is dependent on an efficient search of the solution space and the reliability of the similarity measure. In this paper the Particle Swarm Optimisation (PSO) was used to search the solution space and seven similarity measures were trialled. The accuracy and precision of this method depends on the inherent noise in the spectral bands of the sensor being employed, as well as the radiometric corrections applied to images to calculate the subsurface reflectance. Using the Hydrolight® radiative transfer model and typical hydrosol concentrations from Lake Wivenhoe, Australia, MERIS reflectance spectra were simulated. The accuracy and precision of hydrosol concentrations derived from each similarity measure were evaluated after errors associated with the air-water interface correction, atmospheric correction and the IOP measurement were modelled and applied to the simulated reflectance spectra. The use of band specific empirically estimated values for the anisotropy value in the forward model improved the accuracy of hydrosol retrieval. The results of this study will be used to improve an algorithm for the remote sensing of water quality for freshwater impoundments.

Turbidity, as defined in the standard ISO7027, is a parameter that is routinely measured in many national and regional water quality monitoring programmes. The definition of turbidity according to ISO and as related to satellite data products is discussed. While satellite data products are beginning to become available for the closely related parameter, Total Suspended Matter (TSM), the direct estimation of turbidity as a satellite data product has not yet been addressed. In situ measurements of TSM and of turbidity, obtained in the Southern North Sea (SNS), show high correlation (correlation coefficient of 98.6%). A generic multisensor algorithm for TSM as function of reflectance has been previously developed. The methodology is extended here to the estimation of turbidity from water-leaving reflectance. A set of 49 seaborne measurements of reflectance in the spectral range 600-850nm and turbidity in the SNS are used to calibrate the algorithm. The algorithm is also calibrated for the specific bands of MERIS. Validation of these models is carried out using an independent set of seaborne measurements of turbidity and reflectance and shows low relative errors in turbidity retrieval at 681nm (less than 35%). This wavelength is recommended, provided no significant fluorescence affects this range.

Bioptical models are used jointly with hyperspectral imaging in inversion procedures for mapping of benthic habitats. Several algorithms have been described in the literature to remove the effects of the water column and extract information about the sea bottom that only take into consideration the measured hyperspectral image. However the availability of LIDAR derived bathymetry information opens the possibility of using this information for improved retrieval of the bottom properties. We present in this paper a study using simulated and hyperspectral imagery on the improvement in benthic habitat mapping that can be achieved by fusing bathymetry and hyperspectral imagery. Simulation results show that it is possible to obtain accurate bottom abundance estimates 5-10 meters beyond what can be obtained with hyperspectral imaging alone in clear waters. With real data we demonstrate increase in accuracy with respect to ground truth.

It is well known that synthetic aperture radars (SARs) can image oceanic internal waves (OIWs). The signatures of OIWs on SAR images result from the modulation of wind-generated surface waves by the surface currents associated with the OIWs. The role of surface winds in SAR signatures of OIWs in the northern South China Sea is examined using SAR images and BlendQscat wind data. A radar imaging model for simulating SAR signatures of OIWs is also used to estimate the dependence of the radar signatures associated with OIWs on wind conditions. The results show that the signatures of OIWs on SAR images in the northern South China Sea are highly dependent on the wind speed. The temporal variations of the OIWs observed by SAR are closely related with the temporal variations of the wind speed in the study area.

Using the polarization characteristics of a target and its underlying surface one can change the target contrast range. As the target one can use the compact and discrete structures with different characteristics to reflect electromagnetic waves. An important problem, solved by the adaptive polarization lidar, is to determine the availability and identification of different targets based on their polarization characteristics against the background of underlying surface, which polarization characteristics are unknown. Another important problem of the adaptive polarization lidar is a search for the objects, which polarization characteristics are unknown, against the background of underlying surface, which polarization characteristics are known. The adaptive polarization lidar makes it possible to determine the presence of impurities in sea water. The characteristics of the adaptive polarization lidar undergo variations, i.e., polarization characteristics of a sensing signal and polarization characteristics of the receiver are varied depending on the problem to be solved. One of the versions of construction of the adaptive polarization lidar is considered. The increase of the contrast in the adaptive lidar has been demonstrated by the numerical experiment when sensing hydrosols on the background of the Rayleigh scattering, caused by clear water. The numerical experiment has also demonstrated the increase of the contrast in the adaptive lidar when sensing at two wavelengths of dry haze and dense haze on the background of the Rayleigh scattering, caused by the clear atmosphere. The most effective wavelength was chosen.

Ocean primary productivity is the ability that the ocean primary producers convert inorganic matter into organic matter through the assimilation. It is an important parameter used to estimate ocean biological resources and reflect the characteristics and quality of the ocean ecological environment. With the development of ocean color remote sensing, it has become possible by using the satellite remote sensing to monitor the ocean primary productivity. So, this study selected China's coastal ocean (0°- 41°N, 105°- 130°E) as the main location, used NPP products of SeaWiFS estimated from VGPM (Vertically Generalized Production Model), Eppley-VGPM and CbPM (Carbon-based Production Model) from 1998-2007 to research the characteristics of space distribution and dynamic changes of NPP with time. The results showed that: these models result have many same aspects and have many differences; the mean NPP of VGPM in all ocean regions have two peaks, that of Eppley-VGPM and CbPM just have one peak; the NPP of China coastal ocean has obviously seasonal and apatial variation. In time, the lowest value of NPP was in winter and the highest was in spring and summer; in space, the Bohai and the Yellow Sea had relatively high NPP, relatively low value of the NPP was in South China Sea.

ESA's Envisat ASAR level 2 algorithm is used for retrieving ocean wave spectra (level 2 product) from synthetic aperture radar (SAR) single look complex (SLC) data. Our studies show that in addition to the contribution of wind wave part and swell part of the mixed waves, the cross spectra of mixed waves consist of an extra term. Just the extra term leads to an inherent error of this algorithm which has not been considered yet. This paper presents the error analysis of ESA's algorithm for ocean wave spectra retrieval in different significant wave height (SWH), wave length and wave component conditions based on simulation technique. To correct the inherent error of ESA's algorithm, a new method named unconstrained cross spectra method for directional ocean wave spectra retrieval from SAR SLC imagery is also presented. Case studies show that the new method can avoid the inherent error of ESA's algorithm very well.

Based on the in-situ data and ocean color remote sensing data of SeaWiFS, we found there was a black water region with the normalized water-leaving radiances less than 0.5 mW/(cm²•μm•sr) at the visible light wavelength. Yangtze River Estuary locates in the East China Sea shelf with shallow water. Affected by the tide mixing and the runoff of the Yangtze River and Qiantang River, the turbidity is very high. Generally, the water-leaving radiance is high in the turbid water because of the large particle scattering. The reason of the occurrence of this black water was analyzed by the inherent optical properties and the ocean color components. The results showed that black water was caused by the relative low values of the suspended particle matter concentration and the back scattering ratio.

Suspended sediment is an important parameter of water quality and a main factor to affect the lifetime of port use, which needs to be monitored on the spatial distribution and temporal changes. It also dominates the optical properties in the coastal ocean and makes it difficult to retrieve chlorophyll concentration and other water constituents from satellite remote sensing data. Many algorithms were developed to retrieve suspended sediment concentration (SSC) from satellite remote sensing data and most of them were tested to be used for the region of the East China Sea. The results show that relative errors are too large to be more than 100% under high concentration of sediments. This region, especially in the Yangtze estuary and Hangzhou Bay, is famous for large area distribution of high concentration of suspended sediment, as high as more than 1000 mg/l. A new algorithm is developed, based on a large amount of in-situ measurements of four big cruises, each of these cruises employ two big ships to take about two months to measure about 200 stations. First, the relationship between the water-leaving radiance at different wavelengths and SSC was analyzed and the results show that the radiance at green bands is sensible to SSC at low concentration and almost saturated at high concentration, while the radiance at red bands has a good relationship with SSC at high concentration, meanwhile the radiance at near-infrared bands has also a big value under high SSC. Then the accuracy of the algorithm is evaluated and shows that the algorithm has a nice performance both at low and high SSC. Finally, the algorithm is used to obtain SSC from SeaWiFS and MODIS data and the distribution of SSC show that the algorithm is suitable for retrieving SSC from satellite remote sensing data in the East China Sea.

This paper is concerned with the complex of optical devices for recording of sea waves characteristics in wide range of wavelength from centimeters to hundreds meter. The energy spectra of short waves are obtained in real time by spectral analysis of sea surface image with spectral analyzer operating under no coherent light. The spectral-kinematics characteristics of long energy waves are determined from optical RTI images (range-time-intensity images) constructed from optical profiles of sea surface. A model of imaging of the sea surface in diffuse sky light is developed using twoscale approach of sea roughness that permits to receive new expression for spectra of sea surface wave image. The principles of retrieval of spectralkinematics characteristics of surface waves from RTI images are developed and method for formation of RTI images permitted to remove influence of ships tossing is proposed. The preliminary model of sea wave elevation spectra for wavelength from centimeters to meter derived from spectra of sea surface images and its changing in wind front is presented. The appearance of group structure of long surface waves is registered on optical RTI images of sea surface. The complex of optical devices may be used from shore or ship for monitoring of sea surface roughness in real time.

The China Imaging ALTimeter (CIALT) is designed by the Center for Space Science and Applied Research of the Chinese Academy of Sciences. It is a new generation of altimeter which integrates the synthetic aperture technique and the interferometric technique into traditional altimeters. It operates in Ku-band with an incidence angle of less than 5°. These new characteristics bring us the expectative applications. The possible oceanic applications in marine geoid, ocean currents, mesoscale eddies, ocean surface winds, waves, and tides, etc. are presented.

Some missions have been carried out to measure wave directional spectrum based on airborne real aperture radar in a low incidence. For this study, the authors simulate the satellite-based real aperture radar image spectrum to validate the radar performance of measuring the directional wave spectrum based on the same principal as airborne one. In the processes of the simulation, the authors don't take into account the rotation of antenna and the disturbing of the noise in order that the simulation can exclude other factors to purely verify the measuring theory feasibility in essence. The authors use Wen's spectrum as the input spectrum of the simulation, which is a kind of wind-generated wave spectrum that can better describe the state of developing wave and the statuses of the Chinese sea fields. Following that, the simulated sea surface, backscattered radar signal, modulation spectrum and the one dimension wave spectrum (two dimension one can be obtained by synthesizing every directional one dimension spectrum) are obtained, which is compared with the input spectrum. To have a comprehensive realization to the performance of the radar, different cases including different developing degree, wind speed and angle between dominant waves propagation direction and radar look direction are considered. Presented results show that Satellite-based real aperture radar can mostly measure the wave spectrum, but the capacity is limited on the cases of low wind speed, developing waves and the big angles.

Simulated and airborne imagery demonstrate the ability to see manmade and natural objects below the water wave surface. Traditional photogrammetric imagery and airborne digital imagery both suffer from a loss in image clarity due to a number of factors, including the forward motion of the airborne platform. Blurring due to this effect can be calculated and an opto-mechanical system has been designed in order to help remove this effect. Forward motion blur can be shown to occur on the order of a several centimeters and calculation results are presented. The system is described and imagery is shown to demonstrate image blurring. Preliminary results obtained from an improved Monte Carlo model is also used to show expected results and to begin developing image correction methods in order to remove the blur due to water wave influences. Limitations to the hardware method suggest that the opto-mechanical system designed may lead to additional blur due to nonuniform focal plane focusing issues. The techniques have unique opportunities to help improve hyperspectral pushbroom sensors in addition to large frame mapping cameras that are in use today or being developed for future use.

We analyze here the intercorrelation between natural microwave radiation of the ocean-atmosphere system and its boundary heat and dynamic interaction and describe some approaches to an analysis of heat and dynamic processes in the ocean-atmosphere interface with satellite passive radiometric observations at microwaves. The feasibility of determining synoptic, seasonal and year-to-year variations of sensible, latent heat and momentum fluxes to a useful accuracy using the DMSP SSM/I data directly from the measured brightness temperatures is examined. The main results have been obtained by combining the data of the vessel experiments NEWFOUEX-88, ATLANTEX-90 and the data of microwave radiometric measurements from the meteorological satellites of the DMSP series. Especial part of our study is the elaboration of technologies for diagnosis of tropical hurricanes beginning in the oceans with the remote sensing methods.