This PDF file contains the front matter associated with SPIE Proceedings Volume 9240, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

This study presents an analysis of the sea-ice area time series for the East Greenland Sea for the period January 2003 – December 2013. The data used are a subset of the Arctic Sea Ice Concentration data set derived from the observations of the passive microwave sensors AMSR-E and AMSR-2 and produced, on a daily basis, by the Inst. of Environ. Physics of the University of Bremen. The area of interest goes, approximately, from 57◦N to 84◦N and from 53◦W to 15◦E. On the basis of previous studies, the parameter Sea Ice Area as the sum of all pixels whose sea ice concentration is above 70%, was introduced for measuring sea-ice extent. A first survey of the Greenland Sea data set showed a large anomaly in year 2012; this anomaly, clearly linked with the transition period from AMSR-E to AMSR-2 when re-sampled SSM/I data were used, was partially corrected with a linear regression procedure. The correlation between monthly mean Sea Ice Area and other geophysical parameters, like air temperature, surface wind and cloud cover, was further investigated. High anti-correlation coefficients between air temperature, at sea level and in five different tropospheric layers, and observed ice cover is confirmed. Our analysis shows that the strong decline of Arctic sea-ice area in the last 10 years is not observed in the East Greenland Sea; this implies that large reductions have occurred in the Canadian and Russian Arctic. This result confirms a hypothesis recently postulated to explain the different sea-ice decline in the Arctic and Antarctic regions.

At spring when solar irradiance and air temperature turn snow and ice into an array of surface scatterers, point scatterers become the main signature of ridged environments. This information is better retained in unfiltered T3 matrixes. On another hand a Lee filtered T3 matrix gives information about the diversity of a distributed target which is equally indicative of the higher variability within ridges. In order to keep both in a single set of data, we computed an hybrid matrix composed of the alpha parameter from a single look T3 matrix and the entropy of the same matrix from a Lee 3x3 matrix. As revealed running a Wishart classification algorithm, this approach increases greatly the contrast between ridged and flat areas. The statistics presented in the results section were computed from areas characterized as a) linear ridges, b) rubble fields, c) type 1 un-deformed ice and, d) type 2 un-deformed ice. Un-deformed type 1 ice dates back to the previous fall freeze-up period while un-deformed type 2 ice is a thinner ice formed later through the winter season when the ice pack open up under certain wind conditions and new ice can develop into a flat section. While this technique couldn’t be used during most of the winter season, this may present a great potential to extract narrow linear structures when snow wetness increase surface scattering and therefore the occurrence of single and double bounce scattering mechanisms.

Global Navigation Satellite System (GNSS) based scatterometry offers breakthrough opportunities for wave, wind, ice, and soil moisture remote sensing. Recent developments in electronics and nano-satellite technologies combined with modeling techniques developed over the past 20 years are enabling a new class of remote sensing capabilities that present more cost effective solutions to existing problems while opening new applications of Earth remote sensing. Key information about the ocean and global climate is hidden from existing space borne observatories because of the frequency band in which they operate. Using GNSS-based bi-static scatterometry performed by a constellation of microsatellites offers remote sensing of ocean wave, wind, and ice data with unprecedented temporal resolution and spatial coverage across the full dynamic range of ocean wind speeds in all precipitating conditions. The NASA Cyclone Global Navigation Satellite System (CYGNSS) is a space borne mission being developed to study tropical cyclone inner core processes. CYGNSS consists of 8 GPS bi-static radar receivers to be deployed on separate micro-satellites in October 2016. CYGNSS will provide data to address what are thought to be the principle deficiencies with current tropical cyclone intensity forecasts: inadequate observations and modeling of the inner core. The inadequacy in observations results from two causes: 1) Much of the inner core ocean surface is obscured from conventional remote sensing instruments by intense precipitation in the eye wall and inner rain bands. 2) The rapidly evolving (genesis and intensification) stages of the tropical cyclone life cycle are poorly sampled in time by conventional polar-orbiting, wide-swath surface wind imagers. It is anticipated that numerous additional Earth science applications can also benefit from the cost effective high spatial and temporal sampling capabilities of GNSS remote sensing. These applications include monitoring of rough and dangerous sea states, global observations of sea ice cover and extent, meso-scale ocean circulation studies, and near surface soil moisture observations. This presentation provides a primer for GNSS based scatterometry, an overview of NASA's CYGNSS mission and its expected performance, as well as a summary of possible other GNSS based remote sensing applications.

A scatterometer is a radar designed to measure the backscattering coefficient of distributed targets. In order to compute the backscatter from the received power, the scatterometer measures also the thermal noise power. This noise signal is composed of two components, the receiver thermal noise and the viewed ground radiance. The first component is instrument dependent and hence independent of the target and viewing geometry. The second component is target and viewing geometry dependent, it is proportional to the ground target brightness temperature. In this paper the noise signal measured by C-band scatterometers on-board ERS-2 and Metop-A satellites is analyzed. It was found that the noise signal carries valuable geophysical information, which is worth to be exploited. It is shown that the noise signal varies spatially, temporally and with viewing geometry. Thus, different targets (ocean, sea ice, land) could be easily identified. A comparison was carried out between the scatterometer noise and AMSR-E radiometer brightness temperature and high correlation was found. The noise signal processing (mainly noise subtraction) is discussed, including the assessment of the Noise Equivalent Sigma Zero and the Signal-to-noise ratio. This analysis leads to a better understanding of the noise signal and its impact on the backscatter processing.

Airborne remote sensing appears useful for monitoring oil spill accident or detecting illegal oil discharges. In that context, hyperspectral imagery in the SWIR range shows a high potential to describe oil spills. Indeed reflectance spectra of an oil emulsion layer show a wide variety of shapes according to its thickness or emulsion rate. Although based on laboratory measurements, it seems that these two parameters are insufficient to completely describe them. It appears that the way emulsion is performed leads to different reflectance spectra. Hence this paper will present a model which tends to simulate reflectance spectra of an oil emulsion layer over the sea water. To derive an analytical expression, some approximations and assumptions will be done. The result of this model shows high similarities with laboratory measurements and seems able to simulate most of the shapes of reflectance spectra. It also shows that a key parameter to define the shape of the reflectance spectra is the statistical distribution of water bubbles size in the emulsion. The description of this distribution function, if measurable, should be integrated into the methodology of elaboration of spectral libraries in the future.

The aim of the work presented in this paper focuses on the study and analysis of variations of the bistatic electromagnetic signature of the sea surface contaminated by pollutants. Therefore, we will start the numerical analyses of the pollutant effect on the geometrical and physical characteristics of sea surface. Then, we will evaluate the electromagnetic (EM) scattering coefficients of the clean and polluted sea surface observed in bistatic configuration by using the numerical Forward-Backward Method (FBM). The obtained numerical results of the electromagnetic scattering coefficients are studied and given as a function of various parameters: sea state, wind velocity, type of pollutant (sea surface polluted by oil emulsion, and sea surface covered by oil layer), incidence and scattering angles, frequencies bands (C, X and Ku) and radar polarization.

The Deepwater Horizon oil spill of the Gulf of Mexico in the spring of 2010 was the largest accidental marine oil spill in the history of the petroleum industry. An immediate request, after the accident, was to detect the oil slick and to measure its extent: SAR images were the obvious tool to be employed for the task. This paper presents a processing scheme based on Markov Random Fields (MRF) theory. MRF theory describes the global information by probability terms involving local neighborhood representations of the SAR backscatter data. The random degradation introduced by speckle noise is dealt with a pre-processing stage which applies a nonlinear diffusion filter. Spatial context attributes are structured by the Bayes equation derived from a Maximum-A-Posteriori (MAP) estimation. The probability terms define an objective function of a MRF model whose goal is to detect contours and fine structures. The markovian segmentation problem is solved with a numerical optimization method. The scheme was applied to an Envisat/ASAR image over the Gulf of Mexico of May 9, 2010, when the oil spill was already fully developed. The final result was obtained with 51 recursion cycles, where, at each step, the segmentation consists of a 3-class label field (open sea and two oil slick thicknesses). Both the MRF model and the parameters of the stochastic optimization procedure will be provided, together with the area measurement of the two kinds of oil slick.

For detecting accidental and illegal pollution by mineral oil, the German exclusive economic zone and surrounding waters have been monitored by aircraft operationally for more than 25 years. Aircraft surveillance uses predominantly Side-Looking-Airborne-Radar for visualization of the effect of oil to smoothen capillary waves. A set of near range sensors complements the remote sensing data available for the human operator to classify the detected features as "mineral oil", "natural phenomenon", "other substance" or "unknown" pollution. Today, as an add-on to aerial surveillance, the German Central Command of Maritime Emergencies uses the operational satellite service "CleanSeaNet" provided by the European Maritime Safety Agency: Radar satellite data is analyzed in near real time and alerts of potential pollution are sent out. Shortly after receiving the results, aircraft surveillance flights are started by the 3rd Naval Air Wing and the locations of the satellite alerts are checked. Thus, a combined system of satellite and aerial surveillance is in place. The German Federal Institute of Hydrology, BfG, has access to the data of the pollution events detected during these flights and the corresponding meta-data of flights and satellite images. In this work, a period of two years of this data is analyzed. The probability to detect pollutions is evaluated for (A) flight missions associated with satellite scenes, and (B) additional flights performed independently from satellite scenes. Thus, the influence of satellite alerts on the efficiency of aircraft monitoring is investigated. Coverage and coordination of the monitoring by aircraft and satellite are assessed and implications for the operational monitoring are discussed.

An automatic system called OSAD (Oil Spill Automatic Detector), able to discriminate oil spills (OS) from similar features (look-alikes – LA) in SAR images, was developed some years ago. Slick detection is based on a probabilistic method (tuned with a training dataset defined by an expert photointerpreter) evaluating radiometric and geometric characteristics of the areas of interest. OSAD also provides wind field by analyzing SAR images. With the aim to completely classify sea slicks, recently a new procedure has been added. Dark areas are identified on the image and the wind is computed inside and outside for every area: if outside wind value is less than a threshold of 2 m/s it is impossible to evaluate if damping is due to a slick. On the other hand, if outside wind is higher than the threshold and the difference between inside and outside the dark area is lower than 1 m/s we consider this reduction as wind fluctuation. Wind difference higher than 1 m/s is interpreted as damping effect due to a slick; therefore the remaining dark spots are split in OS and LA by OSAD. LA are then analyzed and separated in “biogenic” or “anthropogenic” slicks following an analogous procedure. The system performances has been tested on C-band SAR images, in particular on images having spatial resolution so high to examine details near the coastline; the obtained results confirm the efficiency of the algorithm in the classification of four types of signatures usually found on the sea surface.

The problem of excessive algae bloom in Volga River and adjacent reservoirs has long been acknowledged. Massive algae bloom causes serious economic damage and represents a threat to water inhabitants as well as man’s life and health. From ecological point of view, cyanobacteria are the most dangerous algae type. The detection of areas most affected by algae bloom using remote sensing instruments was performed on the basis of data obtained from the following sensors: TM Landsat-5; ETM+ Landsat-7; OLI Landsat-8; Envisat MERIS and ASAR. Landsat data were used to compile color composites and select bands, the combination of which provides the best detection results. Visible satellite data were found to better manifest eutrophication zones with predomination of cyanobacteria. Envisat MERIS was used to compile suspended matter concentration charts providing rough estimates of algae content. Envisat ASAR data were compared with quasi-simultaneous visible range data. In-situ measurements of algae properties in Rybinsk Reservoir have been performed for many years by researchers of the I.D. Papanin Inland Water Biology Institute located on its coast. They regularly perform cruises to collect water samples and determine phytoplankton content. Joint analysis of Landsat-7/8 and contact data resulted in good correlation of both bloom areas of diatoms, which predominated in June 2013, and those of cyanobacteria, the lifecycle peak of which was recorded in late August – early September.

We present a two-step algorithm for the detection of seafloor propeller seagrass scars in shallow water using panchromatic images. The first step is to classify image pixels into scar and non-scar categories based on a sparse coding algorithm. The first step produces an initial scar map in which false positive scar pixels may be present. In the second step, local orientation of each detected scar pixel is computed using the morphological directional profile, which is defined as outputs of a directional filter with a varying orientation parameter. The profile is then utilized to eliminate false positives and generate the final scar detection map. We applied the algorithm to a panchromatic image captured at the Deckle Beach, Florida using the WorldView2 orbiting satellite. Our results show that the proposed method can achieve <90% accuracy on the detection of seagrass scars.

The objective of this study is to investigate the relationship between spectral reflectance and Chla in the lake. The spectral reflectance and upper-layer water sampling was performed from onboard on May 30, August 8, 2013, and March 7, 2014 at the 10 to 11 points in the lake. MS720 (EKO Ltd.) was used for spectral reflectance measurement. The wavelength range of reflectance measurement is 400 to 900 nm. Chla was quantified by the UNESCO method after the filtering of upper-layer water and acetone extraction in the laboratory. The range of Chla is 6 to 145 μg L^-1. The spectralreflectance characteristic in the lake is the low reflectance near 670 nm (strong absorption), and the high reflectance near 700 nm (including fluorescence). Such the characteristic is the same as the eutrophic lakes such as Chesapeake Bay in the United States, or Lake District in Germany. A correlation analysis using the two band algorithm for Chla estimation was conducted using 32 obtained datasets. An optimal combination of two bands was the case of 648 nm and 700 nm (R2=0.81). However, the latest earth observation satellites are not observed at these bands. Then, the Chla estimation using Landsat-8 OLI bands which was launched in Feb., 2013 was examined. As a result, it became clear that the technique adapting OC2 and OC3 model of the operational algorithm was comparatively reasonable.

This study focused on determining the past changes and predicting the future trends in eutrophication of the Bolgoda North lake, Sri Lanka using in situ Chlorophyll-a (Chl-a) measurements and Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) satellite data. This Lake is located in a mixed land use area with industries, some agricultural lands, middle income and high income housing, tourist hotels and low income housing. From March to October 2013, water samples from five sampling sites were collected once a month parallel to ASTER overpass and Chl-a, nitrate and phosphate contents of each sample were measured using standard laboratory methods. Cloud-free ASTER scenes over the lake during the 2000-2013 periods were acquired for Chl-a estimation and trend analysis. All ASTER images were atmospherically corrected using FLAASH software and in-situ Chl-a data were regressed with atmospherically corrected three ASTER VNIR band ratios of the same date. The regression equation of the band ratio and Chl-a content with the highest correlation, which was the green/red band ratio was used to develop algorithm for generation of 15-m resolution Chl-a distribution maps. According to the ASTER based Chl-a distribution maps it was evident that eutrophication of this lake has gradually increased from 2008-2011. Results also indicated that there had been significantly high eutrophic conditions throughout the year 2013 in several regions, especially in water stagnant areas and adjacent to freshwater outlets. Field observations showed that this lake is receiving various discharges from factories. Unplanned urbanization and inadequacy of proper facilities in the nearby industries for waste management have resulted in the eutrophication of the water body. If the present trends of waste disposal and unplanned urbanization continue, enormous environmental problems would be resulted in future. Results of the present study showed that information from satellite remote sensing can play a useful role in the development of time series Chl-a distribution maps. Such information is important for the future predictions, development and management of this area as well as in the conservation of this water body.

We examined the applicability of Raman spectroscopy as a laser remote sensing tool for monitoring the gases dissolved in water and gas bubbles. A frequency doubled Q-switched Nd:YAG laser (532 nm) is irradiated to CO2 gas bubbles generated by an air pump. The Raman signals at 1383 cm-1 from CO2 and 1645 cm-1 from water were detected. It has been shown that the CO2/H2O Raman signal ratio is dependent on the CO2 bubble rate.

Imaging of shallow waters using high resolution video imagery is described. Common to mono, stereo and trinocular imaging approaches from ground and airborne platforms is the need to validate the surface water wave field measurements, particularly the amplitude and specular reflectance of water surface small gravity waves. A technique for calibration and validation of water surface gravity wave field energy spectra is described. Results demonstrate the value of video imagery where water level staff gauges with approximately with 0.5 cm wave height accuracy are easily sensed using high definition videography. Essentially, a staff gauge placed in shallow water constructed from PVC materials with custom colored line coding are imaged at 30 H or high frame rates, followed by frame by frame analyses in order to detect the water level measured at 0.5 cm height intervals. The image based time series allow the development of shallow water gravity wave energy spectra using standard FFT analysis procedures. Spectral models based upon peak frequency, for example, are then used in a two dimensional water surface wave simulation model that generates radiative transfer based hyperspectral images of the water surface wave field. The simulated and observed water surface wave patch fields are compared by extracting vertical or horizontal transects within observed and simulated imagery. The approach allows one to developed spectral energy model probability distributions at low cost. The novel noncontact video sensing and image analysis methodology used to calibrate and validate shallow water gravity wave models yield a means for ultimately calculating bottom boundary velocities under measured or simulated wave fields. These boundary layer velocities can cause migration and horizontal particle fluxes (g cm^-2 s^-1), resuspension, settling, and increased turbidity during dredging operations, but not necessarily due to waterway dredging operations and activities.

ERS-1/2 and Metop-A/B satellites carry a very similar radars operating at similar frequencies (5.3/5.255 GHz) and same polarization (VV). However, the radars on-board the satellites of these two missions differ in the pulse waveform, bandwidth and slightly in geometry. Moreover, the on-board and the on-ground processing is different. This paper investigates the spatial and radiometric resolution of these radars and the resolution enhancement between ERS (1991-2011) and Metop (2006- ) missions. The spatial resolution assessment implies the computation and the comparison of the Spatial Response Function (SRF) of both systems. The SRF involves mainly the antenna gain pattern, the pulse waveform and the different on-board filtering stages. The radiometric resolution depends mainly on the signal to noise ratio (SNR) and the number of averaged independent samples (N). Furthermore, the correlation of the measurement samples in a resolution cell is computed to assess the independence assumption. The metric used to quantify the radiometric accuracy in scatterometry is called K_p which is the relative standard deviation. A comparison of K_p parameter extracted from the nominal products of the two missions confirms the expected performance based on the SNR, N and correlation analysis.

Surface signatures of oceanic internal waves (IWs) are often observed in synthetic aperture radar (SAR) images since IWs change surface roughness through the interaction of small-scale ocean waves with varying currents induced by IWs. If we know the relationship between the vertical and horizontal parameters governing IWs, the mixed layer depth (MLD) can be estimated from SAR data since IWs propagate along a pycnocline where the water density changes rapidly. This study presents a method for estimating MLD from SAR data using IW images observed by RADARSAT-1 over the east waters of the Korean Peninsula. To interpret IWs using SAR data, the backscatter radar cross section is computed by applying the small perturbation model to the sea surface perturbed by varying surface currents. Wave height spectrum is computed by varying the upper layer depth of mixed layer from 5 m to 100 m with 1 m depth interval. The surface current field is assumed to move with the IWs, and is described by the KdV equation. The computed RCS is then compared with the RADARSAT-1 data, resulting in satisfactory agreement of the estimated depth of IWs with other data.

Ship wakes can be clearly seen in satellite radar and optical images of the sea surface, and understanding of physical mechanisms responsible for the wake signatures is very important to develop methods of ship detection/identification. The wake surface signatures at small and intermediate stages are characterized by a smooth centerline area where surface waves are depressed due to the vessel turbulence and by a pair of rough bands at the sides of the centerline wake. At large wake ages two slick bands (a “railroad track” wake) appear instead of the rough bands, while the smooth centerline band is practically absent. In this paper results of field studies of the mean flow structure near the wake are presented. It is shown that two mean circulating currents (“rolls”) rotating in the opposite directions are formed at two sides of the median vertical plane of the wake. Near the water surface the rolls result in diverging horizontal flows, decreasing near the wake edges. Wind waves propagating against the diverging currents are amplified due to a wave straining mechanism thus increasing the surface roughness. Film sampling was carried out when crossing the wakes and analysis of films collected within the “railroad” slick bands and outside the bands has revealed enhanced surface wave damping, obviously due to accumulation of surfactants in the slick bands; the surfactant compression is explained by the action of the diverging currents. The diverging currents as part of the rolls and the surfactant transport to the water surface are supposed to be associated with air bubbles generated by ship propellers.

The first Chinese Ku-band scatterometer (SCAT), carrying on the satellite HY-2, has provided the global ocean surface wind vector products since its successful launch in August 2011. The HY-2 SCAT wind products are estimated based on the geophysical model function (GMF), where only the wind vector, while no wave information is taken into consideration. Thus, it is still an open issue that the contribution to HY-2 SCAT wind product errors owing to the swell influence. In this paper, the swell impact on HY-2 SCAT wind speed and direction product quality is presented through the comparison of the one year HY-2 products with buoy data. The NDBC buoy wave spectra were reconstructed from measurements, partitioned using watershed algorithm, and categorized into 4 groups of pure swell, swell and wind sea dominated mixed sea, and pure wind sea. The wave dependency of wind residuals between the HY-2 and the buoy were investigated. The comparison results on different swell components indicate the significant influence of the swell present on HY-2 SCAT quality in terms of both wind speed and wind direction. It is recommended that the information on sea state should be integrated into the wind retrieval algorithm for Ku-band scatterometers (HY-2 SCAT and also the future scatterometer on CFOSAT), in order to improve the accuracy.

Satellite altimetry has proven to be a useful tool to study oceanic processes in the deep ocean; however, its use is still limited in shallow waters near the coast where two main issues still need a more detailed analysis. On one side, the local characteristics of each coastal region imply that certain corrections applied to the altimetry measurements need to be reanalysed. On the other side, the radar signal retracking algorithms need to be improved because the waveforms do not follow the Brown's model, which is designed for deep waters. The ESA mission Envisat was launched in March 2002 with a dual-frequency radar altimetry (RA-2). The satellite was operative until the end of the mission in May 2012. The ESA mission Cryosat-2 was launched in April 2010 being still in operation. The radar instrument on-board Cryosat-2 improves the capabilities of previous pulse-limited altimeters, such as Envisat RA-2. The Spanish-funded ALCOVA project aims at analyzing and improving the altimetry measurements obtained from these two altimetry missions. Regarding the RA-2 data a new prototype retracker -ALES- has been developed under the frame of the ESA-DUE eSurge project. Two pilot regions are proposed, namely, the Gulf of Cadiz and the Strait of Gibraltar in the Southwestern Iberian Peninsula. Cryosat-2 data (in SAR mode), the newly corrected RA-2 data (based on ALES) and the standard RA- 2 product (based on Brown's model) are being validated with available in-situ data (sea level height) to ensure their correct performance in the selected coastal areas.

Goal of this work is to present and validate an underwater object spectral recognition methodology for fluorescence LIDAR signals by using an underwater fluorescence LIDAR propagation model. The spectral recognition methodology is aimed at deciding if an underwater object detected in the water column can be identified as belonging to a data base of objects of interest characterized by known fluorescence spectral signatures. The methodology needs to compensate the received signal for the water column effects in order to derive an estimate of the underwater object fluorescence spectrum to be used for spectral recognition. By using an underwater fluorescence LIDAR propagation model developed ad hoc, the methodology may be validated in different system, geometric, and environmental conditions. Experimental results obtained in two different acquisition scenarios show that the underwater object recognition methodology is promising for recognizing objects submerged in the water column at different depths and highlight the utility of the developed LIDAR propagation model for assessing the object recognition performance that may be experienced in various different acquisition conditions.

The relationship between the degree of linear polarization (DoLP) and attenuation-to-absorption coefficients ratio (c/a) of the water from which the scattering coefficient is readily computed (b = c-a) for two main types of oceanic waters (Case I and II) was investigated using the vector radiative transfer simulation. It is found the for Case I waters that only the green channels of the spectrum can be used to retrieve the scattering coefficient of the water whereas blue and red channels are dominated by the pure water effects of either Rayleigh scattering or high water absorption showing no variability between DoLP and c/a. On the other hand, Case II waters showed a strong relationship between DoLP and c/a for all wavelength of light under study (440, 550, 665 nm). Those relationships have been parameterized for all possible viewing geometries (sensor zenith and azimuth relative to the Sun’s principle plane) and for varying Sun zenith angles. That relationship has been tested and validated against a dataset of in-situ measurements using a custom developed underwater polarimeter that measures the DoLP and an in-water package of instruments (WetLabs ac-s) that measure the absorption and the attenuation coefficients. Another polarimeter fixed on a platform in Long Island Sound at the LISCO station measures the DoLP of the light above water while a moored instrument package (WQM and C-star) that measures in-water optical properties have been used for a time serious validation.

Remote estimations of oceanic constituents from optical reflectance spectra in coastal waters are challenging because of the complexity of the water composition as well as difficulties in estimation of water leaving radiance in several bands possibly due to inadequacy of current atmospheric correction schemes. This work focuses on development of a multiband inversion algorithm that combines remote sensing reflectance measurements at several wavelengths in the blue, green and red for retrievals of the absorption coefficients of phytoplankton, color dissolved organic matter and nonalgal particulates at 443nm as well as the particulate backscatter coefficient at 443nm. The algorithm was developed, using neural networks (NN), and was designed to use as input measurements on ocean color bands matching those of the Visible Infrared Imaging Radiometer Suite (VIIRS). The NN is trained on a simulated data set generated through a biooptical model for a broad range of typical coastal water parameters. The NN was evaluated using several statistical indicators, initially on the simulated data-set, as well as on field data from the NASA bio-Optical Marine Algorithm Data set, NOMAD, and data from our own field campaigns in the Chesapeake Bay which represent well the range of water optical properties as well as chlorophyll concentrations in coastal regions. The algorithm was also finally applied on a satellite - in situ databases that were assembled for the Chesapeake Bay region using MODIS and VIIRS satellite data. These databases were created using in-situ chlorophyll concentrations routinely measured in different locations throughout Chesapeake Bay and satellite reflectance overpass data that coexist in time with these in-situ measurements. NN application on this data-sets suggests that the blue (412 and 443nm) satellite bands are erroneous. The NN which was assessed for retrievals from VIIRS using only the 486, 551 and 671 bands showed that retrievals that omitted the 671 nm band was the most effective, possibly indicating an inaccuracy in the VIIRS 671 band that needs to be further investigated.

Influence of breaking waves and whitecaps on characteristics of echo signal of airborne bathymetric lidar is investigated at strong winds. The model of echo signal, considering following factors is advanced: finite height of waves, random refraction of light by sea surface, free from foam and breaking waves, diffuse scattering of light on both sites of a surface with whitecaps on crests of waves. The account of finite height of waves is represented especially important at strong winds as in these conditions influence of whitecaps can appear essential. The relations are received, allowing estimating average delay and broadening of the signal. It is shown that whitecaps weak influence on average characteristics at wind speeds to 20 m/s. This influence appears essential in that case when measurement of a delay and, accordingly, definition of depth of a bottom or reflecting object is made by times of the first arrival of a backscattering signal from water.

Measuring accurately Sea Surface temperature is important for many marine applications and monitoring the global climate system. Many instruments are used for the measuring the SST. The SST delivered from satellite have the advantages that are a broad scope and consistent detection. But SST products show the different value because of different of retrieval algorithm and sensor. To reduce the uncertain, SST data ensemble is carried out using the Bayesian model averaging(BMA). BMA is method of the weighted average using the posterior probability distribution. And the means and variances of the posterior probabilities are estimated using Expectation-Maximization(EM) algorithm. The estimated mean of the posterior probability is used as the weight for the weighted average. SST data of Aqua/MODIS, Terra/MODIS and NOAA/AVHRR was used as ensemble member. SST data Envisat/AATSR was used as reference data for calculating the posterior probability and validation data. To make the monthly ensemble SST, their provided monthly SST data was used. one-leave-out-cross validation that is one of the statistical validation method is used for validating the ensemble SST. The 12 cases, except for the data of one month per the case, was made and excepted month was used validation period. And we compared with the ensemble mean and median. As the result, ensemble BMA showed the lowest RMSE.

The characterization of the marine environment plays an important role in the understanding of the dynamics affecting the transport, fate and persistence (TFP) of Persistent Organic Pollutants (POPs). This work is part of a project funded by the Ministero dell’Istruzione, dell’Università e della Ricerca. The aim of the project is the assessment of the TFP of POPs in the Mediterranean sea. The analysis will be carried out at regionalmesoscale (central Mediterranean), and at local spatial scale considering different Italian test sites (the Delta of the Po River, the Venice Lagoon and the estuary of the Rio Nocella). The first step of this work involves the implementation of GIS geodatabases for the definition of the input dataset. The geodatabases were populated with MERIS and MODIS level 2 and level 3 products of Chlorophyll-a (CHL-a), Chromophoric Dissolved Organic Matter (CDOM), Aerosol Optical Thickness (AOT), Diffuse Attenuation Coefficient (DAC), Particulate Inorganic Carbon (PIC), Particulate Organic Carbon (POC) and Sea Surface Temperature (SST). The spatial scale (central Mediterranean sea) and the reference system (Plate Carrée projection) have been imposed as a constraint for the geodatabases. Four geodatabases have been implemented, two for MODIS and two for MERIS products with a monthly, seasonal and climatological temporal scale (2002 -2013). Here, we present a first application of a methodology aimed to identify vulnerable areas to POPs accumulation and persistence. The methodology allowed to assess the spatial distribution of the CHL-a in the central Mediterranean sea. The chlorophyll concentration is related to the amount of nutrients in the water and therefore provides an indicator of the potential presence of POPs. A pilot area of 300 x 200 km located in the North Adriatic sea has been initially considered. The seasonal and climatological MODIS and MERIS CHL-a variability were retrieved and compared with in-situ forcing parameters, i.e. Po River discharge rates and wind data. Study outlooks include a better accuracy of the distribution of the vulnerable areas achieved through the use of additional parameters (CDOM, SST, POC), and an assessment of the contribution of the contaminants by atmospheric dry deposition to the marine environment.

At present time radar methods of the seas and oceans diagnostics are actively developing. Using of the radar stations based on satellites and planes allows to receive information on a sea surface and a atmosphere near-surface layer with coverage of big water surface areas independently of day time. The developed methods of satellite radio images processing can be applied to marine radar stations. In Institute of Applied Physics RAS works on sea surface diagnostics systems development on the basis of standard marine radar are actively conducted. Despite smaller coverage of the territory in comparison with satellite data, marine radar have possibility to record spatially temporary radar images and to receive information on a surrounding situation quickly. This work deals with results of the researches which were conducted within the international expedition in the Atlantic Ocean in the autumn of 2012 on a route Rotterdam (Netherlands) – Ushuaya (Argentina) – Antarctica — Ushuaya. During this expedition a complex measurements of a sea surface, a atmosphere near-surface layer parameters and subsurface currents in the wide range of hydroweather conditions, including the storm were carried out. The system developed in IAP RAS on the basis of a marine radar ICOM MR-1200RII and the ADC (Analog Digital Converter) block for data recording on the personal computer was used. Display of a non-uniform near-surface current on sea surface radar images in storm conditions is shown. By means of the high-speed anemometer and meteorological station the measurements of the atmosphere parameters were carried out. Comparison of the anemometer data with calculated from radar images is carried out. Dependence of radar cross section from wind speed in the wide range of wind speeds, including storm conditions is investigated. Possibility of marine radar using for surface waves intensity and ice situation estimates also as icebergs detection is shown.

This paper compares the wind speed retrieval methods on C-band multi-polarization SAR measurements to find out the most appropriate one for each polarization data. The RADARSAT-2 SAR quad-polarization (VV+HH+VH+HV) data and NDBC buoy wind data were collocated. For VVpolarization, the retrieved wind speed are compared among four geophysical model function (GMF). For HH polarization, the retrieved wind speed are compared among four polarization ratio model (PR) based on CMOD5 GMF. For VH polarization, the retrieved wind speed are compared between two linear models. Comparisons show all of three polarimetric SAR data have the ability of retrieving wind speed. Based on the error analysis, the commendatory methods are proposed for each polarization.

Satellite radar (SAR) and visible band data from Envisat ASAR, ERS-2 SAR, Lansat-5,7,8 sensors were used to investigate internal waves (IWs) in the Black Sea. The three main areas of the Black Sea where surface manifestations of internal waves (SMIWs) were mostly observed are: the Danube Delta, Crimea Peninsula and the northeastern region near Novorossiysk. The main goal of our investigation was to define the mechanisms of IW generation in the non-tidal sea. In the first area, IWs are observed rather often due to surface intrusions of fresh waters of the Danube River. In contrast to usual soliton-like IW trains caused by river plumes, soliton trains near the Danuba Delta propagate in different directions and often subject to nonlinear interactions. The interrelation between location and orientation of IW trains and fresh water fronts is discussed. In the area off Crimea, in our opinion, IWs are generated mainly by upwelling relaxation and interaction between internal inertial waves and bottom topography features. SMIW in the northeastern part of the Black Sea are scarce, though IWs are regularly revealed by in-situ measurements. Field measurements were conducted in the northeastern part of the Black Sea from a small boat and from scientific sea platform near Crimea employing CTD probes, thermistor chain and Acoustic Doppler Current Profilers (ADCP). ADCP measurements allowed us to detect a number of IW trains. Their amplitudes were estimated to reach 5-8 m. Joint analysis of satellite SAR and subsatellite data gave an assessment of their typical wavelength at 90-100 m.

Radar manifestations of ship wakes in zones of phytoplankton bloom are discussed. It is shown that these signatures can be regarded as indicators of biogenic activity. The main data are satellite radar images. Satellite visible (VIS) and infrared (IR) satellite data are also analyzed. The large amount of the available data allowed us to make some generalizations and obtain statistically reliable results concerning spatial and temporal variability of certain type of ship wake manifestations in synthetic aperture radar (SAR) images of the sea surface. Traditional classification of surface ship wakes manifestations in satellite SAR images specifies distinct features such as a dark trailing centreline region (turbulent wake), narrow V-wakes aligned at some angle to the ship’s path (the Kelvin wake), and, sometimes, internal wave wakes generated under conditions of shallow stratification. Their characteristic lengths are reported to be up to tens of kilometers and they can last from tens of minutes up to one hour. Instances of radar signatures of the ship wakes dissimilar to the previously described were detected in radar images obtained in the course of a satellite monitoring campaign of the central and south-eastern Baltic. These ship wakes can be seen in satellite radar images as long bright strips of enhanced backscatter with characteristic length of up to several hundred kilometres lasting more than 5 hours. A hypothesis is put forward of the coherence of this type of ship wakes detected in sea surface radar imagery and areas of intensive biogenic activity under conditions of low near-surface winds. Statistics on their seasonal, spatial and year-to-year distribution are drawn. These results are compared with temporal and spatial variations in chlorophyll a concentration and intensity of phytoplankton bloom in the area of interest. Chlorophyll a concentration maps derived from satellite data are used, as well as those based on in situ measurements. The relation between occurrences of this type of ship wake manifestations and areas of algae blooms is established.

Recent studies have suggested the length of the satellite records is too short to separate interannual and multidecadal cycles from climate trends. Therefore, the traditional method to assume trend being a straight line over the whole length of a time series is not suitable to reveal the actual trend of satellite Chlorophyll a concentration (Chla) records which length is less than 20 years. From the monotonic trend analysis, the significant increasing trend (P<0.05) in the central and southern South China Sea (SCS) and significant decreasing trend (P<0.05) in the Bay of Bengal (BoB) were detected. However, a time-varying trend in the surface chlorophyll between the SCS and BoB was obtained by exploring an Ensemble Empirical Mode Decomposition (EEMD) method in our study. Our analysis of the long term merged Chla time series from GlobColour over the time period from September 1997 to December 2011 revealed a change of trend for the central BoB before and after 2003; Chla was indeed increasing till 2003 but began to be declining since then. For the southern SCS, Chla was increasing till 2004 and appeared to decrease since then. In the southern BoB and the central SCS, the trends seemed to be almost linear and always decreased or increased during the study period. The results indicate that the warming SST makes a contribution to the decrease of the chlorophyll while the cooling SST leads to the increase of the chlorophyll in both the southern BoB and southern SCS. However, the wind may contribute a little to the trend of chlorophyll.

A comparison among three Compact-Polarimetry (CP) Synthetic Aperture Radar (SAR) architectures is followed to analyze some polarimetric features sensitivity with respect to the ocean background variation, which is achieved as situational awareness about the environment influence on detection algorithms performance. Thus, architectures are emulated from Radarsat-2 full-polarimetric actual SAR data, according to wave polarimetry concepts. In this analysis, the entropy of the wave scattered off the observed scene is used as polarimetric feature, considering as reference the conventional target entropy evaluated from full-polarimetric SAR data. Then, actual RISAT-1 Hybrid-Polarity (HP) data are analyzed extracting other polarimetric features to investigate their capabilities to discriminate metallic targets from the ocean background. Relative ocean background sensitivity analysis is addressed using an objective metric named Relative Sensitivity of Polarimetric Features (RSPolF), whose characterizes the polarimetric feature sensitivity for the sea state found in each SAR scene. Additionally, on further works, it can objectively support target detection algorithms for threshold definition.

The functionality, the goals and the current state of the distributed information system “See the Sea” (STS) are presented and discussed. This system is designed for investigating various processes and phenomena in the ocean and marine atmosphere using different types of satellite remotely sensed data. The STS system provides researchers with the possibilities to deal with the satellite remote sensing data as well as with the result of its analysis. The key feature of STS is the ability to work simultaneously with satellite information of different types. STS provides tools for joint analysis of different types of satellite data, as well as data of ground meteorological stations, cartographic data etc. This paper gives an overview of the system and data processing use cases. Some example cases are described including processing and joint analysis of various satellite data. The data from different sensors (obtained by Envisat ASAR, Landsat-8 OLI, Landsat-7 ETM+, Landsat-5 TM, Terra/Aqua MODIS as well as Hyperion and HICO hyperspectral data) was analyzed jointly for differentiation between different types of coastal waters, and for reconstruction of suspended matter distribution in the test areas of the Azov and Black Seas.

The method of retrieval of wind speed from sea surface image under diffuse sky illumination is developed. The method consists of two stages: firstly the rms slope is determined by fitting modeled radiance with sought rms slope to measured sea surface radiance and secondly wind speed is determined using the Cox and Munk relation between mean square slope and wind speed. An analytical model of sea surface radiance for visible light is developed taking into account shadowing of surface waves for grazing view geometry. The method was applied to investigation of the structure of near surface wind fields in сatabatic wind flows for ranges from hundreds meters to ten kilometers.

In order to obtain the indicator types which must be introduced in marine water quality evaluation as well as the suitable evaluation methodology, GB3097-1997 National Marine Water Quality Standards is, in the first place, analyzed to establish a hypothetical sample which is consisting of 2000 stances, each stance containing the information of 21 indicators. And then a stepwise discriminant method is utilized to filter the 21 indicators in accordance with their water quality classification discriminant abilities. And finally, 6 indicators with significant discriminant ability, biochemical oxygen demand(BOD5), oil type(Oil), total phosphorus(P), cadmium(Cd), cyanide(HH) and chemical oxygen demand(COD), are selected and the water quality evaluation chart of the corresponding six indicators is also established. Theoretically, the water quality indicator types and the suitable evaluation methodology, which must be introduced when the water quality evaluation is done in all the waters under the jurisdiction of China, are discussed in this paper, providing theoretical basis for the subsequent marine water quality evaluation based on field observation.

The principal component analysis (PCA) method is a popular fusion method used for its efficiency and high spatial resolution improvement. However, the spectral distortion is often found in PCA. In this paper, we propose an adaptive PCA method to enhance the spectral quality of the fused image. The amount of spatial details of the panchromatic (PAN) image injected into each band of the multi-spectral (MS) image is appropriately determined by a weighting matrix, which is defined by the edges of the PAN image, the edges of the MS image and the proportions between MS bands. In order to prove the effectiveness of the proposed method, the qualitative visual and quantitative analyses are introduced. The correlation coefficient (CC), the spectral discrepancy (SPD), and the spectral angle mapper (SAM) are used to measure the spectral quality of each fused band image. Q index is calculated to evaluate the global spectral quality of all the fused bands as a whole. The spatial quality is evaluated by the average gradient (AG) and the standard deviation (STD). Experimental results show that the proposed method improves the spectral quality very much comparing to the original PCA method while maintaining the high spatial quality of the original PCA.