This PDF file contains the front matter associated with SPIE Proceedings Volume 8888, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

The assimilation of Synthetic Aperture Radar (SAR) data in an operational data assimilation system for the purpose of estimating sea ice properties is a relatively unexplored area. One of the areas where SAR data can provide key information regarding the details of the ice cover is in the marginal ice zone. However, automatic interpretation of the images in this area is challenging due to sensitivity of the backscattered signal to changing surface and environmental conditions and speckle noise. In this paper the impact of denoising on the assimilation of SAR texture features is examined. Two cases have been considered; one assimilating texture features without denoising and the other one having a denoising step prior to the assimilation of texture features. The contribution of the denoising to the analysis is evaluated.

The environment of Arctic is very important for the global environment and human society because it is sensitive as sea ice changes and keeps the Earth’s cool or warm climate. So we need continuous monitoring of Arctic sea ice to understand and predict the process of climate changes. Satellite remote sensing is a useful tool for monitoring sea ice. Thus, this study analyzed the time-series of Arctic sea ice changes using satellite remote sensing data with a time-series statistical method for last ten years from 2003 and predicted the sea ice extent in the near future. Especially, we used the Multivariate SARIMA(Seasonal Autoregressive Integrated Moving Average) model that reflects multiple meteorological variables and seasonality. It was carried out to convert daily to monthly data of sea ice products because optical sensors have high spatial and temporal resolution than passive microwave sensors, but have difficulty observing the sea ice because of clouds. The result showed that minimum area of sea ice was a decrease trend during the study period and the explanatory power of the constructed Multivariate SARIMA model was about 0.71. It is thought of as a remarkable outcome because there are no studies for the Multivariate SARIMA analysis showing high explanatory power for the changes of sea ice extent. To improve the explanatory power of our model, it will be necessary as a future work to set the optimal thresholds of algorithm for estimating monthly sea ice extent and to increase the accuracy of climate factors data.

The capabilities of evolving satellite remote sensing technology, combined with conventional data collection techniques, provide a powerful tool for efficient and cost effective management of living marine resources. Fishes are the valuable living marine resources producing food, profit and pleasure to the human community. Variations in oceanic condition play a role in natural fluctuations of fish stocks. The Satellite Altimeter derived Merged Sea Level Anomaly(MSLA) results in the better understanding of ocean variability and mesosclae oceanography and provides good possibility to reveal the zones of high dynamic activity. This study comprised the synergistic analysis of signatures of SEAWIFS derived chlorophyll concentration, National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer(NOAA-AVHRR) derived Sea Surface Temperature and the monthly Merged Sea Level Anomaly data derived from Topex/Poseidon, Jason-1 and ERS-1 Altimeters for the past 7 years during the period from 1998 to 2004. The overlapping Chlorophyll, SST and MSLA were suggested for delineating Potential Fishing Zones (PFZs). The Chlorophyll and SST data set were found to have influenced by short term persistence from days to week while MSLA signatures of respective features persisted for longer duration. Hence, the study used Altimeter derived MSLA as an index for long term variability detection of fish catches along with Chlorophyll and SST images and the maps showing PFZs of the study area were generated. The real time Fishing statistics of the same duration were procured from FSI Mumbai. The catch contours were generated with respect to peak spectra of chlorophyll variation and trough spectra of MSLA and SST variation. The vice- a- versa patterns were observed in the poor catch contours. The Catch Per Unit Effort (CPUE) for each fishing trail was calculated to normalize the fish catch. Based on the statistical analysis the actual CPUEs were classified at each probable MSLA depth zones and plotted on the same images.

We recently developed a method for inter-calibrating spaceborne scatterometers. This method was successfully applied to ERS-1/ERS-2 and Metop-A/ERS-2 C-band scatterometers. The method is based on combining different natural targets (ocean, sea ice and rainforest) and associated geophysical models. In this paper, the inter-calibration method is applied to Metop-A and Metop-B scatterometers data with a focus on the ocean measurements. Additionally, the correction coefficients obtained from the ocean are compared to and validated on other independent targets i.e., rainforest and sea ice. Calibration of the scatterometer over ocean is widely used for monitoring and correction of the backscattering coefficients. The method is based on the assessment of the difference between the measured and the simulated backscatter using NWP winds and Geophysical Model Functions (GMF’s) such as CMOD5. The method provides the instrument bias against the GMF. It was found that this bias varies spatially and temporally. This temporal and spatial variation of the bias could lead to discrepancies of up to 0.1 dB, which is significant compared to the calibration accuracy (0.2 dB). This adds to the actual bias (instrument drift) an artificial error which is due to the misfit of the input wind distribution. It is shown that this discrepancy is due to the sensitivity of the GMF to the wind speed distribution and this consequently yields the calibration over ocean to be sensitive to the wind speed distribution. The wind speed distribution variation in time and space is analyzed. The sensitivity of the calibration over the ocean to the wind speed distribution variation is assessed. Finally, a method is proposed to mitigate this variation and thus reduces the misfit error.

A simplified algorithm for SAR-based bathymetry is presented able to measure surface current variations generated by the bottom topography from SAR intensity images and to reduce the need for both a-priori information and human-inthe- loop operations. The algorithm is first analyzed from a theoretical point of view and an error budget model is developed to estimate the achievable depth accuracy as a function of the uncertainty in the input parameters. Preliminary experimental results are also presented in which the algorithm is applied to both COSMO-SkyMed and ALOS images of the Gulf of Naples. The results show that the technique has the potential to generate depth measures that are significantly denser than those commonly reported in the nautical charts.

Both the modulation of short wind wave breaking in the long surface wave field and the occurrence of breaking in the presence of a long wave were investigated in wind-wave tank. Short wind waves were generated by the air flow at various speeds, the long surface wave at various frequency and amplitude were generated by wave maker. Data of X- and Ka-band scatterometers, string wave recorder placed in the probing area, and web camera making video records of the probing area were synchronously recorded in the experiment. Also precision measurements using laser-optics system based on the high-speed video recording, laser illumination, and special algorithms of video processing allowed us to obtain a large ensemble of the wave profiles. It is shown that at relatively weak wind long surface wave causes short wind wave breaking, and at high wind speeds – breaking intensification. Wind wave breaking is mainly observed on the front slope of the long wave, the breaking observation area extends with increasing wind speed.

We studied the changes of total suspended matter (TSM) distribution in Estonian coastal sea with special focus onPaldiskiharbor at the Pakri Bay (SW Gulf Of Finland). The purpose of current study was to examine the suitability of remote sensing data for detection of turbidity differences caused by dredged sediments on monthly mean surface TSM concentration, retrieved from satellite images. The MERIS (FSG) products with 300m resolution and MODIS band 1 data with 250m resolution from years 2006-2010 were used in theanalysis. MERIS images were processed using the Case-2 water processors available in BEAM software. Validation of the two processors (C2R and FUB) with in situ measurements of TSM gave reliable correlation between satellite data and in situ TSM measurements: r² was 0.43 for FUB processor and 0.47 for C2R processor. An empirical algorithm was established for conversion of MODIS band 1 reflectance (620-670 nm) data to TSM concentration. We found reliable (r²=0.43) relationship between MODIS reflectance at band 1and TSM concentration measured fromwater samples. The monthly average TSM maps in the harbor region were calculated from MERIS and MODIS data using validated conversion algorithms in order to describe TSM variability and to analyzeenvironmental impact of dredging.

Remote sensing results of land and water surfaces from airborne and satellite platforms are dependent upon the illumination geometry and the sensor viewing geometry. Correction of pushbroom hyperspectral imagery can be achieved using bidirectional reflectance factors (BRF’s) image features based upon their multi-angle hyperspectral signatures. Ground validation of features and targets utilize non-imaging sensors such as hemispherical goniometers. In this paper, a new linear translation based hyperspectral imaging goniometer system is described. Imagery and hyperspectral signatures obtained from a rotation stage platform and the new linear non-hemispherical goniometer system shows applications and a multi-angle correction approach for multi-angle hyperspectral pushbroom imagery corrections. Results are presented in a manner in order to describe how ground, vessel and airborne based multi-angle hyperspectral signatures can be applied to operational hyperspectral image acquisition by the calculation of hyperspectral anisotropic signature imagery. The results demonstrate the analysis framework from the systems to water and coastal vegetation for exploitation of surface and subsurface feature or target detection based using the multi-angle radiative transfer based BRF’s. The hyperspectral pushbroom multi-angle analysis methodology forms a basis for future multi-sensor based multi-angle change detection algorithms.

In this paper we present the spectral behavior of the Solar Induced Fluorescence (SIF) of a crude oil, retrieved from its radiance spectrum acquired in eight selected spectral windows of the visible spectrum from about 389 nm to 659 nm. Each spectral window was chosen to cover one or more solar Fraunhofer Lines (FL) so as to retrieve the in-filling due to the oil fluorescence contribution induced by the solar irradiance. The selected Fraunhofer lines were chosen within the solar lines rather than the telluric ones since the former ones offer several advantages for the application from air- or space-borne platform. Solar FL, compared with telluric ones, require a simpler atmospheric model to evaluate ground solar irradiance. Besides, the signal measured at the sensor is not affected by re-absorption effects. For each spectral window, oil fluorescence contribution and reflectance were evaluated by comparing the measured total radiance of the oil with the incident sun irradiance spectrum measured in the same conditions. Fluorescence and reflectance spectral shapes were evaluated within each measured spectral window by applying a spectral fitting method (SFM) and polynomial modeling. Solar-induced fluorescence data were then used to evaluate the fluorescence spectrum of the oil. The SIF spectrum of the same oil was also simulated by using emission-excitation fluorescence data and a simulated solar irradiance. The measured and simulated spectra were then compared.

The knowledge about mesoscale and sub-mesoscale sea surface current fields is of high interdisciplinary interest, since it results in a better understanding of ocean-atmosphere interactions. However, many available numerical model results are of resolutions, which are too coarse to investigate mesoscale and sub-mesoscale turbulent features like eddies, particularly in coastal waters. In this work we present the results of tracking biogenic and anthropogenic surface film signatures on multi-sensor satellite images (SAR and multispectral images) to estimate the local sea surface current field. The main advantage of this approach is that the resolution of the derived current fields depends mainly on the resolution of the images, which have been used for tracking. Due to the large temporal distance between two acquisitions of a scene and the high variability of the tracked sea surface films, classical tracking methods, e.g. feature based or Optical Flow methods may not be applicable to successfully track the imaged signatures of the surface films. In this work, we use our former developed generic framework, which ensures the applicability and increases the stability of the results for wellknown tracking and Optical Flow algorithms. With this framework, it is e.g. possible to compute the sea surface current field using Optical Flow approaches even for large spatiotemporal distances and with partial scene coverage. We present and compare the results of different tracking algorithms by means of tracking biogenic sea surface films. The investigated areas are the Baltic Sea and the Black Sea. We present the use of Landsat TM, SeaWiFS, ERS-2, TerraSARX and RADARSAT-2 data for the derivation of sea surface currents. The resolution of the images used varies from moderate to fine resolution, which allows the derivation sea surface current fields of moderate to fine resolutions.

Measurements of the upwelling polarized radiance in relatively shallow waters of varying depths and benthic conditions are compared to simulationsrevealing the depolarizing nature of the seafloor. Significant correlations between simulations and measurements are attained when the appropriate unpolarized, Lambertian bottoms are included in the radiative transfer model. The bottoms used in this study produce realistic upwelling radiance distributions as well as ranges of the degree of linear polarization (DoLP) that peak between 10 and 30%. This study specifically finds that polarization in upwelling radiance is best preserved at long wavelengths in clear waters and also at short wavelengths in phytoplankton- and CDOM-rich waters. These results can thus facilitate the detection of benthic materials as well as future studies of camouflage by benthic biota.The DoLPwas found to be highly sensitive to benthic reflectance, but the angle of polarization (AoLP), which quantifies the orientation of polarization, is independent of it. The AoLP could therefore be used to communicate and sense direction underwater.

In the processing of Ocean Color (OC) data from sensor data recorded by Visible Infrared Imaging Radiometer Suite (VIIRS) aboard JPSS-Suomi satellite, NASA Ocean Biology Processing Group (OBPG) is deriving a continuous temporal calibration based on the on-board calibration measurements for the visible bands, and then reprocessing the full mission to produce a continuously calibrated sensor data record (SDR) product. In addition, a vicarious calibration during SDR to OC Level-2 processing is applied. In the latest processing the vicarious calibration is derived from the Marine Optical Buoy (MOBY) data, whereas in the initial processing it was derived from a sea surface reflectance model and a climatology of chlorophyll-a concentration. Furthermore, NASA has recently reprocessed the OC data for the entire VIIRS mission with lunar-based temporal calibration and updated vicarious gains. On the other hand, in fulfilling the mission of the U.S. National Oceanic and Atmospheric Administration (NOAA), the Interface Data Processing Segment (IDPS) developed by Raytheon Intelligence and Information Systems, for the processing of the environmental data products from sensor data records, has gained beta status for evaluation. As these processing schemes continue to evolve, monitoring the validity and assessments of the related VIIRS ocean color products are necessary, especially for coastal waters, to evaluate the consistency of these processing and calibration schemes. The ocean color component of the Aerosol Robotic Network (AERONET-OC) has been designed to support long-term satellite ocean color investigations through cross-site measurements collected by autonomous multispectral radiometer systems deployed above water. As part of this network, the Long Island Sound Coastal Observatory (LISCO) near New York City and WaveCIS in the Gulf of Mexico expand those observational capabilities with continuous monitoring as well as (for the LISCO site) additional assessment of the hyper-spectral properties of coastal waters. In the investigations carried out over a one and half year period dataset of VIIRS, based on the data from two coastal AERONET-OC sites, it has been observed that the VIIRS sensor captures well the seasonal and temporal variations in the nLw data, exhibiting significant correlation with in-situ data (R = 0.929 and 0.985 for LISCO and WaveCIS respectively). For the WaveCIS site, VIIRS nLw data retrievals are seen to be enhanced with each incremental adjustments of vicarious and calibration procedures. However, that is not the case for the LISCO site which exhibits more frequent occurrences of negative water-leaving radiances, while underestimation in VIIRS nLw data is further exacerbated. Strong consistency between the time-series nLw data retrieved from the VIIRS and MODIS sensors was also observed.

As it can strongly influence the availability of light and thus primary production, coloured dissolved organic matter (CDOM) affects the function of lake ecosystems. Therefore reliable methods are required for the monitoring of CDOM concentration. A new method using downwelling irradiance was tested for applicability in four selected lakes of the Bavarian Osterseen Lake District, which consists of 19 naturally connected freshwater lakes of different trophic level. The method separates between the direct and diffuse part of the incident light in order to handle the strong variability of the underwater light field. It is implemented in the software WASI, which is capable to retrieve water constituents by inverse modeling. During field campaigns downwelling irradiance measurements using RAMSES sensors were made in different depths. Simultaneously, water samples were taken in three depths (0.5 m, 2 m and Secchi disk depth), from which the absorption coefficient of CDOM, a_Y, was derived in the range from 190 to 900 nm using photometric absorption measurements. Concentration (defined as a_Y at 440 nm) ranged from 0.33 to 1.55 m^-1 with a mean of 0.71 m^-1 ± 0.04 m^-1, the spectral slope at 440 nm from 0.0120 to 0.0184 nm-1 with a mean of 0.0145 ± 0.0008 nm^-1. These laboratory measurements from water samples were compared to CDOM concentration obtained by inverse modeling of downwelling irradiance measurements using WASI. For sensor depths lower than 1 to 1.5 m large uncertainties were observed. The measurements in 2 m depth and at Secchi disk depth yielded good correlation between water sample and WASI derived data (R² = 0.87) with a mean standard deviation of 0.06 m^-1 for the determined CDOM concentrations. This new method is an alternative to laboratory analysis of water samples from in situ measurements of CDOM concentration.

It is known that development of new remote sensing technique for investigation of sea surface features is an important oceanographic problem. This paper is focused on a new method of analysis of optical range – time – intensity images (RTI images) of sea surface [1-3]. The RTI image constructed from optical profiles of sea surface is an optical analog of a side-looking radar image of sea surface but having higher spatial resolution and some possibility for remote sensing of sea roughness. It is possible to form RTI images with range from some tens meters to tens kilometers depending on spatial resolution needed. A set of original optical devices for recoding RTI images using linear arrays of CCD-photodiodes was created [4-6]. The long surface wave fields, breaking of waves, near surface wind field features, eddies, wind fronts, catabatic winds, ship wakes, oil slicks, manifestations of internal waves on sea surface were recorded and investigated by this apparatus in inland waters and in the ocean [5-7]. Description of optical system, some new examples of RTI images of sea surface and its analysis are presented in this work. The principles of remote sensing of near surface winds by its manifestations on the water surface under grazing angles were developed. The model of RTI imagery of the water surface based on the expansion of image intensity on wave slopes and taking into account wave shadowing has been developed. The analytical dependence of intensity of water surface on wave slope dispersion permitting to restore velocity of near surface wind was received.

Oceans play a significant role in the global carbon cycle and climate change, and the most importantly it is a reservoir for plenty of protein supply, and at the center of many economic activities. Ocean health is important and can be monitored by observing different parameters, but the main element is the phytoplankton concentration (chlorophyll–a concentration) because it is the indicator of ocean productivity. Many methods can be used to estimate chlorophyll–a (Chl-a) concentration, among them, remote sensing technique is one of the most suitable methods for monitoring the ocean health locally, regionally and globally with very high temporal resolution. In this research, long term ocean health monitoring was carried out at the Bay of Bengal considering three facts i.e. i) very dynamic local weather (monsoon), ii) large number of population in the vicinity of the Bay of Bengal, and iii) the frequent natural calamities (cyclone and flooding) in and around the Bay of Bengal. Data (ten years: from 2001 to 2010) from SeaWiFS and MODIS were used. Monthly Chl–a concentration was estimated from the SeaWiFS data using OC4 algorithm, and the monthly sea surface temperature was obtained from the MODIS sea surface temperature (SST) data. Information about cyclones and floods were obtained from the necessary sources and in-situ Chl–a data was collected from the published research papers for the validation of Chl-a from the OC4 algorithm. Systematic random sampling was used to select 70 locations all over the Bay of Bengal for extracting data from the monthly Chl-a and SST maps. Finally the relationships between different aspects i.e. i) Chl-a and SST, ii) Chl-a and monsoon, iii) Chl-a and cyclones, and iv) Chl-a and floods were investigated monthly, yearly and for long term (i.e 10 years). Results indicate that SST, monsoon, cyclone, and flooding can affect Chl-a concentration but the effect of monsoon, cyclone, and flooding is temporal, and normally reduces over time. However, the effect of SST on Chl-a concentration can't be minimized very quickly although the change of temperature over this period is not very large.

New principles of design of imaging system through the rough surface are offered. These principles allow to lower negative influence of surface wavy and multiple scattering in water on the spatial resolution. The system model in which the image of underwater objects is formed at by means of angular scanning by an illumination beam is considered. Image distortions in such system are caused basically by random changes of a refraction angle of a laser beam on a surface and can be eliminated, if the true direction of an input of a beam in water is known. We suggest taking the information on refraction angle of a beam from angular distribution of backscattering signal of water layer. Such information can be received by means of receivers with sensitivity linearly vary across the field of view. The knowledge of true position of a beam of illumination on object allows receiving the image not deformed by wavy. We suggest reducing influence of multiplayer scattering in water by means of application of high-frequency modulation of beam power and the matched processing in reception system. Use of a complex signal modulation allows keeping the good resolution on depth and the resolution in a horizontal plane to rise. Thus, the combination of a method of definition of a refraction angle of a beam and modulation of a beam by a high-frequency complex signal gives an essential gain in the resolution of airborne imaging system.

A new method is proposed to extract the directional ocean wave spectra from the dual-polarization SAR imagery. Firstly, a new SAR - ocean transform is constructed by combining the quasi-linear transforms of the dual-polarization image spectra and cross spectra. The modulation transfer function (MTF) of the transform depends only on the tilt MTF. The uncertainty of MTFs in hydrodynamic and velocity bunching modulation can’t bring extra errors. Secondly, the 180° ambiguity of wave spectra is removed by the imaginary part of dual-polarization cross spectra. Finally, Radarsat-2 quad-polarization SAR imagery was collected to validate the performance. The extracted wave parameters are compared with the ones from buoy. Comparisons preliminarily show the potential of wave spectra extraction from dual-polarization SAR imagery. More cases will be studied.

Acousto-optical imaging spectrometer based on double AOTF for World Ocean monitoring with suitable characteristics and high quality spectral imaging for ecological monitoring applications is described.

Small footprint airborne laser scanning (ALS) is widely used to collect topographic data over large areas. ALS point clouds provide high resolution datasets for variety of scientific and engineering applications, e.g. geomorphology, geodynamics and forestry. ALS can also be used for monitoring coastal processes. For many marine applications, however, the sea surface heights (SSH) are often requested. Satellite altimetry (SA) has been used to monitor SSH globally. But in regional scale, especially in the coastal areas and enclosed water bodies, the usability of SA is limited due to poor accuracy. Alternatively, our experiments have demonstrated that the water surface in the nadir range can be registered using small footprint ALS. Therefore, a special case study was carried out to analyze SSH determination from ALS measurements. Three profile-wise ALS measurements were carried out in the eastern shores of the Baltic Sea. Along flight trajectories 100 m wide corridors of ALS points were formed. Shorter wavelength signals, like sea wave oscillation, were removed by a low-pass averaging filter. The achieved SSH were verified against a high resolution regional geoid model and also with high-frequency tide gauge observations. Comparisons revealed that the ALS-based sea level-corrected SSH agree with the regional geoid model with standard deviation as of ±1…±2 cm. Thus, small footprint ALS measurements could be applied to determine SSH in regions where SA has limited quality, e.g. in coastal areas and enclosed water bodies.