This PDF file contains the front matter associated with SPIE Proceedings Volume 8724, including the Title Page, Copyright Information, Table of Contents, and the Conference Committee listing.

The detection and identification of underwater threats in coastal areas is of interest to the Navy. Conventional optical imaging systems are limited to scenarios where the number of attenuation lengths between the system and the object are less than 4. With a desire to operate at extended ranges and threats becoming smaller and better camouflaged, new approaches are needed. In response to these challenges, new transmitters and receivers are being developed to support the next-generation of underwater optical imaging systems. One of these systems is based on the modulated pulse concept where a pulsed laser source is encoded with a radar signal, and a range-gated, high-speed optical receiver recovers the radar modulation envelope. Subsequent processing of the radar signal provides a way to discriminate against multiply scattered light and to enhance image contrast and resolution. The challenge is developing transmitter and receiver hardware that meets the requirements of the modulated pulse technique. We report recent progress that has been made in developing modulated pulse transmitter and receiver hardware. A working prototype was demonstrated and tested in a controlled laboratory environment. The results of these initial experiments are presented.

Underwater imaging is challenging because of the significant attenuation of light due to absorption and scattering of light in water. Using polarization properties of light is one of the options for improving image quality. We present results of imaging of a polarized target in open ocean (Curacao) and coastal (NY Bight) waters. The target in the shape of a square is divided into several smaller squares, each of which is covered with a polarizing film with different polarization orientations or transmission coefficients was placed on a mirror and imaged under water by a green-band full-Stokes polarimetric video camera at the full range of azimuth angles against the Sun. The values of the Stokes vector components from the images are compared with the modeled image of the target using radiative transfer code for the atmosphere-ocean system combined with the simple imaging model. It is shown that even in clear water the impact of the water body on the polarized underwater image is very significant and retrieval of target polarization characteristics from the image is extremely challenging.

Mobile, high throughput mid-range data communications and robust real-time data networking in the subsea environment that can accommodate high bandwidth sensors such as optical imagers have a potentially high impact as enabling technologies for a variety of future subsea operations in the areas of distributed sensing and real-time wireless feedback and control of unmanned undersea vehicles. Although much work has been done recently in the field of undersea optical free space communications and networking, to date there has yet to be an implementation of a complete multi-node undersea wireless optical data communications network. The deployment and testing of optical wireless network equipment in the undersea environment is expensive and time-consuming, and there is a clear need for a network simulation framework that will allow researchers to evaluate the performances of different networking concepts/configurations under realistic operational and environmental constraints. This paper describes a network simulation approach that uses an accurate time dependent Monte Carlo channel model to simulate the networking physical layer, which can be used in conjunction with higher network layer protocols to simulate larger scale network performance and to help determine hardware requirements for overall network system design in a variety of undersea channel conditions.

The Bahamas Optical Turbulence Experiment (BOTEX) was conducted in the summer of 2011 to investigate the impact of turbulence on underwater optical imaging. Underwater optical properties can be affected by turbulence in the water, due to localized changes in the index of refraction. We discuss measurements of current velocity and temperature, made with a Nortek Vector Acoustic Doppler Velocimeter (ADV) and PME Conductivity- Temperature (CT) probe, as well as observations made with a Rockland Oceanographic Vertical Microstructure Profiler (VMP). The instruments were deployed in close proximity in the field and in the context of measurements of optical target clarity. Turbulent kinetic energy dissipation (TKED) and temperature dissipation (TD) rates are calculated from the ADV/CT measurements and compared to TKED and TD estimated from the data collected with the VMP. The results show reasonable agreement between the two methods; differences are attributed to turbulence patchiness and intermittence, as well as sampling challenges. The study also highlights the importance of collecting concurrent data on temperature, current velocity, and current shear to assess the turbulence impact on underwater optical properties.

As part of the research to development an optical communication design of a leader-follower formation between unmanned underwater vehicles (UUVs), this paper presents light field characterization and design configuration of the hardware required to allow the use of distance detection between UUVs. The study specifically is targeting communication between remotely operated vehicles (ROVs). As an initial step in this study, the light field produced from a light source mounted on the leader UUV was empirically characterized and modeled. Based on the light field measurements, a photo-detector array for the follower UUV was designed. Evaluation of the communication algorithms to monitor the UUV’s motion was conducted through underwater experiments in the Ocean Engineering Laboratory at the University of New Hampshire. The optimal spectral range was determined based on the calculation of the diffuse attenuation coefficients by using two different light sources and a spectrometer. The range between the leader and the follower vehicles for a specific water type was determined. In addition, the array design and the communication algorithms were modified according to the results from the light field.

Nowadays there is a significant interest in the study of the ocean´s mapping. This research goal is to find a way through computer vision to automate image analysis obtained underwater, skip handwork; people may have the aptitude to do it on paper, however it might not be as precise, trustful and quick. The basis of this case study is the shades present in pictures. There are several techniques that can be used to approach this purpose. In order to develop this idea, there will be used Fourier transform, Wavelet transform and computer vision filters, among other methods. Underwater mapping is difficult because of the noise and lack of high resolution marine technologies; there is needed more than one procedure to obtain a sharp map.

Sonar watermarking is the practice of embedding low-power, secure digital signatures in the time frequency space of a waveform. The algorithm is designed for a single source/receiver configuration. However, in a multiuser environment, multiple sources broadcast sonar waveforms that overlap in both time and frequency. The receiver can be configured as a filter bank where each bank is dedicated to detecting a specific watermark. However, a filter bank is prone to mutual interference as multiple sonar waveforms are simultaneously present at the detector input. To mitigate mutual interference, a multiuser watermark detector is formulated as a decorrelating detector that decouples detection amongst the watermark signatures. The acoustic channel is simulated in software and modeled by an FIR filter. This model is used to compensate for the degradation of spreading sequences used for watermark embedding. The test statistic generated at the output of the decorrelating detector is used in a joint maximum likelihood ratio detector to establish the presence or absence of the watermark in each sonar waveform. ROC curves are produced for multiple sources positioned at varying ranges subject to ambient ocean noise controlled by varying sea states.

The lidar overlap function is defined as the fraction of the transmitted beam that is within the receiver field of view. For the case of bistatic oceanographic lidar from the deck of a ship, the overlap function can vary from pulse to pulse under the influence of the rough sea surface. This paper considers the overlap function as a function of depth for a bistatic lidar operating from the deck of a ship. The effect is calculated using a Monte-Carlo approach, with a Pierson–Moskowitz spectrum of surface roughness and optical ray tracing through that surface. The results show that a significant decrease in the overlap can result, even at low wind speeds.

CZMIL is an integrated lidar-imagery system and software suite designed for highly automated generation of physical and environmental information products for coastal zone mapping in the framework of the US Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP). This paper presents the results of CZMIL system validation in turbid water conditions along the Gulf Coast of Mississippi and in relatively clear water conditions in Florida in late spring 2012. Results of the USACE May-October 2012 mission in Green Bay, WI and Lake Erie are presented. The system performance tests show that CZMIL successfully achieved 7-8m depth in Mississippi with K_d =0.46m^-1 (Kd is the diffuse attenuation coefficient) and up to 41m in Florida when Kd=0.11m^-1. Bathymetric accuracy of CZMIL was measured by comparing CZMIL depths with multi-beam sonar data from Cat Island, MS and from off the coast of Fort. Lauderdale, FL. Validation demonstrated that CZMIL meets USACE specifications (two standard deviation, 2σ, ~30 cm). To measure topographic accuracy we made direct comparisons of CZMIL elevations to GPS-surveyed ground control points and vehicle-based lidar scans of topographic surfaces. Results confirmed that CZMIL meets the USACE topographic requirements (2σ, ~15 cm). Upon completion of the Green Bay and Lake Erie mission there were 89 flights with 2231 flightlines. The general hours of aircraft engine time (which doesn't include all transit/ferry flights) was 441 hours with 173 hours of time on survey flightlines. The 4.8 billion (!) laser shots and 38.6 billion digitized waveforms covered over 1025 miles of shoreline.

While land maps of vegetation cover and substrate types exist, similar underwater maps are rare or almost non-existing. We developed the use of airborne bathymetric lidar mapping and high resolution satellite data to a combined method for shallow sea floor classification. A classification accuracy of about 80% is possible for six classes of substrate and vegetation, when validated against field data taken from underwater video recordings. The method utilizes lidar data directly (topography, slopes) and as means for correction of image data for water depth and turbidity. In this paper we present results using WorldView-2 imagery and data from the HawkEye II lidar system in a Swedish archipelago area.

The University of Southern Mississippi’s Central Gulf of Mexico Ocean Observing System (CenGOOS) operates three long-range (~200 km) 5 MHz CODAR high frequency radar (HFR) stations at Singing River Island in Pascagoula, Mississippi, Gulf State Park in Orange Beach, Alabama, and Henderson Beach State Park in Destin, Florida. Each station broadcasts electromagnetic (EM) waves that follow the conducting sea surface and are Bragg-scattered preferentially by surface gravity waves with a wavelength of one half the wavelength of the EM waves moving towards or away from the antenna. The back-scattered waves are Doppler shifted by the sum of the speed of the waves through the water and the component of the surface velocity in the radial direction to the receive antenna. If the water depth is sufficient for the deep-water approximation to hold (in this case deeper than 20 m), the wave speed is a function of only the wavelength, so it is known from the Bragg-scattering condition. Thus, the component of the surface velocity radial to the receive antenna can be computed from the amount of Doppler shift, and these components are known as “radials”. Where there is overlapping coverage of radials, the total surface current vectors are estimated. The HFR stations cover much of the Mississippi Bight (MSB) seaward of the 20 m isobath. The surface current fields have been analyzed for annual and seasonal climatology.

This paper will discuss and compare some recent oceanic test results from the Bahamas Optical Turbulence Exercise (BOTEX) cruise, where vertical profiling was conducted with both time-resolved laser backscatter measurements being acquired via a subsurface light detection and ranging (lidar) profiling instrument, and laser beam forward deflection measurements were acquired from a matrix of continuous wave (cw) laser beams (i.e. structured lighting) being imaged in the forward direction with a high speed camera over a one-way path, with both transmitter and camera firmly fixed on a rigid frame. From the latter, it was observed that when within a natural turbulent layer, the laser beams were being deflected from their still water location at the image plane, which was 8.8 meters distance from the laser dot matrix transmitter. As well as suggesting that the turbulent structures being encountered were predominately larger than the beam diameter, the magnitude of the deflection has been confirmed to correlate with the temperature dissipation rate. The profiling lidar measurements which were conducted in similar conditions, also used a narrow collimated laser beam in order to resolve small-scale spatial structure, but with the added attribute that sub-nanosecond short pulse temporal profile could potentially resolve small-scale vertical structure. In the clear waters of the Tongue of the Ocean in the Bahamas, it was hypothesized that the backscatter anomalies due to the effect of refractive index discontinuities (i.e. mixed layer turbulence) would be observable. The processed lidar data presented herein indicates that higher backscatter levels were observed in the regions of the water column which corresponded to higher turbulent mixing which occurs at the first and second themoclines. At the same test stations that the laser beam matrix and lidar measurements were conducted, turbulence measurements were made with two non-optical instruments, the Vertical Microstructure Profiler (VMP) and a 3D acoustical Doppler velocimeter with fast conductivity and temperature probes. The turbulence kinetic energy dissipation rate and the temperature dissipation rates were calculated from both these setups in order to characterize the physical environments and corroborate with the laser measurements. To further investigate the utility of elastic lidar in detecting small-scale turbulent structures, controlled laboratory experiments were also conducted, with the objective of concurrently acquiring both the laser beam spatial characteristics in the forward direction and the laser backscatter temporal profile from each transmitted sub-nanosecond pulse. An artificial refractive index discontinuity was generated in clear test tank conditions by placing a clean ice-filled carboy above the laser beam propagation path. The results from both field and laboratory experiments confirm our hypothesis that turbulent layers are detectable by lidar sensors, and motivates that more research and lidar instrumentation development is needed to better quantify turbulence, especially for mitigating associated performance degrading effects for the U.S. Navy’s next generation electro-optic (EO) systems, including active laser imaging and laser communications.

Data assimilation experiments with the coupled physical, bio-optical model of Monterey Bay are presented. The approach is based on the representation of the error covariances in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from the model run. Estimated coupled bio-optical, physical error covariances are used in the Kalman gain update providing updates of coupled bio-optical properties in accord with the model dynamics and available observations. With the assimilation of satellite-derived bio-optical properties (chlorophyll-a and absorption due to phytoplankton), the model was able to reproduce intensity and tendencies in subsurface chlorophyll distributions observed at water samples locations in the Monterey Bay, CA. Data assimilation also improved agreement between the observed and model-predicted ratios between diatoms and small phytoplankton populations.

In the conventional SAR (Synthetic Aperture Radar) polarimetry, fully polarimetric HH-HV-VH-VV quad polarization data are used. The advantage of using quad-polarization data is more information on the scattering objects than the single- and quad-polarization data; while the disadvantages are narrower swath and less frequent data takes. To fill the gap in-between, the present study examines the polarimetric analysis using HH-VV dual polarization. The model-based three- and four-component scattering power decomposition analyses are not possible with dual-polarization data, and thus, the study is focused on the eigenvalue decomposition analysis by comparing the entropy and mean alpha angle derived from dual-polarization data with those derived from quad polarization data, acquired by ALOS-PALSAR (Advanced Land Observing Satellite Phased Array L-band SAR) PLR (PoLaRimetric mode) and TerraSAR-X dual-polarization SpotLight mode over the Tokyo Bay, Japan. The preliminary results indicate that the values of dual-polarization entropy and alpha angle are almost the same as the quad-polarization values, indicating that dual-polarization data are as capable as quad-polarization data in the eigenvalue decomposition. The technique is then applied to estimating the underwater laver cultivation fields and ship detection.

Crude oil spills in the marine environment result in spatially variable slicks, with up to 90% of the oil contained in less than 10% of the slick area. Rapid slick containment and cleanup is in the interest of all stakeholders and can be best accomplished by focusing efforts on the thickest regions of the slick. An instrument for estimating oil slick thickness would expedite the cleanup process and offers the potential to minimize a spills’ environmental impact. In this work, we have experimented using infrared (IR) spectroscopy and pattern recognition algorithms to discriminate thin and thick regions of an oil slick. Fourier transform-IR (FT-IR) spectra of five crude oils and one refined oil at varying thicknesses on water were collected at short standoff in a laboratory setting. The strong C-H stretching absorbances near 3000 cm^-1 and 1500 cm^-1 proved most useful for discriminating oil thickness. Several techniques for signal representation and discrimination were explored in attempt to classify spectra as thin or thick, where “thick” was defined as greater than a predetermined thickness threshold. Although a discrimination approach using Principal Component Analysis and artificial neural networks was most efficient, a template matching approach provided slightly better performance. Thick oil slicks were determined with 95% probability of detection (P_d) and 5% probability of false alarm (P_fa) when the oil was contained in the template matching database (88% P_d with 15% P_fa when the oil was not in the database). The system’s overall performance varied with the predetermined thickness threshold, with 100 μm producing the best results.

Modeling the ocean bottom and surface of both Atlantic and Pacific Oceans near the Colombian coast is a subject of increasing attention due to the possibility of finding oil deposits that haven’t been discovered, and as a way of monitoring the ocean limits of Colombia with other countries not only covering the possibility of naval intrusion but as a chance to detect submarine devices that are used by illegal groups for different unwished purposes. In the development of this topic it would be necessary to use Standard Hydrodynamic Equations to model the mathematical shape of ocean waves that will take differential equations forms. Those differential equations will be solved using computer algebra software and methods. The mentioned solutions will involve the use of Special Functions such as Bessel Functions, Whittaker, Heun, and so on. Using the Special Functions mentioned above, the obtained results will be simulated by numerical methods obtaining the typical patterns around the Colombian coasts (both surface and bottom). Using this simulation as a non-perturbed state, any change in the patter could be taken as an external perturbation caused by a strange body or device in an specific area or region modeled, building this simulation as an ocean radar or an unusual object finder. It’s worth mentioning that the use of stronger or more rigorous methods and more advanced Special Functions would generate better theoretical results, building a more accurate simulation model that would lead to a finest detection.

Automated match ups allow us to maintain and improve the ocean color products of current satellite instruments MODIS, and since February 2012 the Visible Infrared Imaging Radiometer Suite (VIIRS). As part of the VIIRS mission Ocean Calibration and Validation Team, we have created a web-based automated match up tool that provides access to searchable fields for date, site, and products, and creates matchups between satellites (MODIS, VIIRS), and in-situ measurements (HyperPRO and SeaPRISM). The goal is to evaluate the standard VIIRS ocean color products produced by the IDPS and available through NOAA’s CLASS data system. Comparisons are made with MODIS data for the same location, and VIIRS data processed using the NRL Automated Processing System (APS) used to produce operational products for the Navy. Results are shown for the first year of VIIRS data matching the satellite data with the data from Platform Eureka SeaPRISM off L. A. Harbor in the Southern California Bight, and HyperPRO data from Station ALOHA near Hawaii.

Over the decades, ocean color imaging sensors placed in Low Earth Orbits (LEO) have enabled nearly daily measurements of ocean water properties. Such observations, however, are restricted by cloud/atmospheric conditions. More importantly, such systems could not provide sufficient number of measurements to study the diurnal dynamics of coastal/oceanic ecosystems. One way to surmount such limitations is to leverage geo-stationary orbits to significantly improve temporal observations over such dynamical coastal/oceanic environments. In this study, it is desired to examine whether 50% changes in chlorophyll-a concentration (< 1.5 ug⁄l) on a semi-diurnal basis are above the noise level. To do so, the top-of-atmosphere radiance (L_t) is modeled for the planned GEO-CAPE mission intended for monitoring coastal ecosystem and river plumes. The input to the simulations includes diurnal remote sensing reflectances (R_rs), which are propagated through a moderately clear atmospheric conditions using a radiative transfer code. The simulations are carried out for two footprints to investigate two extremely different sun-sensor geometries. From these simulations, the temporal change in spectral reflectances between the hours relative to an average noise is examined. Based on the preliminary results, it was found that while the signal change is, on average, 13x the average noise for near-nadir footprints, the change in signal, on average, is only 1.5x the average noise level for near-edge footprints at top of the atmosphere. Such a contrast suggests difficulties in retrieving diurnal variability for locations near the edge of the field of regard (FOR).

As an integral part of the VIIRS sensor calibration and validation efforts, our group has been continuously monitoring the validity of the Visible Infrared Imager Radiometer Suite (VIIRS)’s Ocean Color (OC) and atmospheric data stream through time series in-situ data acquired at the observatory sites which are part of the AERONET – OC network. This paper addresses the preliminary evaluations of the VIIRS sensor’s performance for retrieving OC data of typical coastal water environments, by carrying out time-series, as well as qualitative and quantitative match-up comparisons analysis between in-situ and satellite retrieved OC data. Initial time-series match-up comparisons carried out for almost a year period (January to December, 2012) show that VIIRS data exhibits strong temporal and statistical agreements with AERONET-OC data demonstrating a potential for enhanced coastal water monitoring from space. VIIRS data processing schemes which apply different vicarious calibration gains are compared and analyzed based on AERONET-OC data as well as OC retrievals of the Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Aqua satellite. The underlying cause of the discrepancies observed in VIIRS retrieved normalized water-leaving radiances is also investigated.

The Hyperspectral Imager for the Coastal Ocean (HICO) is a prototype sensor installed on the International Space Station (ISS) designed to explore the management and capability of a space-borne hyperspectral sensor. The Office of Naval Research (ONR) funded the development and management of HICO. The Naval Research Laboratory (NRL) built and is involved in management of the HICO sensor. Bathymetry information is essential for naval operations in coastal regions. However, bathymetry may not be available in denied areas. HICO has a 100 meter spatial resolution, which makes it more capable for providing information within bays and estuaries than other sensors with coarser resolutions. Furthermore, its contiguous hyperspectral range is well suited to be used as input to the Hyperspectral Optimization Process Exemplar (HOPE) algorithm, which along with other absorption and backscattering values, estimates bottom albedo and water depth. Vicarious calibration uses in situ data to generate new gains and offsets that when applied to the top-of-atmosphere radiance values improves atmospheric correction results and the measurement of normalized water-leaving radiances. In situ remote sensing reflectance data collected in St. Andrews Bay were used to vicariously calibrate a coincident HICO scene. NRL’s Automated Processing System (APS) was used to perform atmospheric correction and estimation of remote sensing reflectance (Rrs). The HOPE algorithm used the vicariously calibrated HICO Rrs values to estimate water depth. The results were validated with bathymetry maps from the NOAA National Ocean Service (NOS).

The dynamic and small-scale spatial variability of bio-optical processes that occurs in coastal regions and inland waters requires high resolution satellite ocean color feature detection. The Visual Infrared Imaging Radiometer Suite (VIIRS) currently utilizes five ocean color M-bands (410,443,486,551,671 nm) and two atmospheric correction M-bands in the near infrared (NIR; 745,862 nm) to produce ocean color products at a resolution of 750-m. VIIRS also has several high resolution (375-m) Imaging (I)-bands, including two bands centered at 640 nm and 865 nm. In this study, a spatially improved ocean color product is demonstrated by combining the 750-meter (M- channels) with the 375-m (I1-channel) to produce an image at a pseudo-resolution of 375-m. The new approach applies a dynamic wavelength-specific spatial ratio that is weighted as a function of the relationship between proximate I- and M-band variance at each pixel. This technique reduces sharpening artifacts by incorporating the native variability of the M-bands. In addition, this work examines the viability of replacing the M7-band (862 nm) with the I2-band (865 nm) to determine the atmospheric correction and aerosol optical depth at a higher resolution. These true (I-band) and pseudo (M-band) high resolution radiance values can subsequently be utilized as input parameters into various algorithms to yield high resolution optical products. The results show new capability for the VIIRS sensor for monitoring bio-optical processes in coastal waters.

Using a dataset consisting of 9000 reflectance spectra simulated using HYDROLIGHT 5 for a broad range of observable natural water conditions, we have developed three neural networks (NNs) working in parallel to model the inverse problem for both oceanic and coastal waters. These NNs are used to relate the water leaving remote sensing reflectance (Rrs) at available MODIS visible wavelengths (412, 443, 488, 531, 547 and 667nm) to the phytoplankton (a_ph), non-phytoplankton particulate (a_dm), dissolved (a_g) absorption and particulate backscattering (b_bp) coefficients at 443nm. These reflectance derived parameters (a_ph(443), a_dm(443), a_g(443), b_bp(443)) are then combined with the measured reflectance values and used as input to a fourth NN, (IOP NN [Chl]), to derive chlorophyll concentration ([Chl]). Unlike NNs previously developed by us that were trained on a synthetic dataset and then tested on the NASA Bio-Optical Marine Algorithm Dataset (NOMAD), the (IOP NN [Chl]) network was both trained and tested solely on NOMAD. Although the inherent optical properties (IOP) can be derived from the optical signal through their direct relation to the Rrs, the relationship of [Chl] to IOP varies with location and season, and is therefore difficult to model globally. In order to demonstrate that the inclusion of derived IOP estimates along with radiance measurements can improve the retrieval of [Chl], we construct a neural network that is trained to derive [Chl] from reflectance measurements only We also compare our [Chl] product to that obtained from the current OC3 algorithm implemented by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). Finally, we apply our algorithm to MODIS data and present and analyze the global seasonal variability for all three parameters.

Same day ocean color products from the S-NPP and MODIS provide for a new capability to monitor changes in the bio-optical processes occurring in coastal waters. The combined use of multiple looks per day from several sensors can be used to follow the water mass changes of bio-optical properties. Observing the dynamic changes in coastal waters in response to tides, re-suspension and river plume dispersion, requires sequential ocean products per day to resolve bio-optical processes. We examine how these changes in bio-optical properties can be monitored using the NPP and MODIS ocean color products. Additionally, when linked to ocean circulation, we examine the changes resulting from current advection compared to bio-optical processes. The inter-comparison of NPP and MODIS ocean products are in agreement so that diurnal changes surface bio-optical processes can be characterized.

The ultimate goal of the prediction of Sea Surface Temperature (SST) from satellite data is to attain an accuracy of 0.3°K or better when compared to floating or drifting buoys located around the globe. Current daytime SST algorithms are able to routinely achieve an accuracy of 0.5°K for satellite zenith angles up to 53°. The full scan swath of VIIRS (Visible Infrared Imaging Radiometer Suite) results in satellite zenith angles up to 70°, so that successful retrieval of SST from VIIRS at these higher angles would greatly increase global coverage. However, the accuracy of present SST algorithms steadily degrades to nearly 0.7°K as the satellite zenith angle reaches 70°, due mostly to the effects of increased atmospheric path length. We investigated the use of T_field, a gap-free first guess temperature field used in NLSST, as a separate predictor to the MCSST algorithm in order to clearly evaluate its effects. Results of this new algorithm, TfieldSST, showed how its rms error is heavily dependent on the aggressiveness of the pre-filtering of buoy matchup data with respect to Tfield. It also illustrated the importance of fully exploiting the a priori satellite-only information contained in T_field, presently tamed in the NLSST algorithm due to the fact that it shows up as a multiplier to another predictor. Preliminary results show that SST retrievals using TfieldSST could be obtained using the full satellite swath with a 30% improvement in accuracy at large satellite zenith angles and that a fairly aggressive pre-filtering scheme could help attain the desired accuracy of 0.3°K or better using over 75% of the buoy matchup data.

The Naval Oceanographic Office (NAVOCEANO) produces Sea Surface Temperature (SST) retrievals from satellite data. NAVOCEANO also obtains satellite-derived SST data sets from other groups. To provide consistency for assimilation into analyses and models, all the SST data sets are evaluated for their accuracy with the same methodology. In this paper, the focus is SST derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on board the Suomi National Polar-orbiting Partnership (NPP) satellite. Of particular interest is the evaluation of NAVOCEANO produced SST with its NAVOCEANO Cloud mask, the VIIRS cloud mask, and VIIRS Environmental Data Record SST. The evaluation results show that these products are in some ways comparable, with similar strengths and weaknesses, although they target different customers. For comparison, the reliability results for the Meteorological Operational (METOP-A) satellite-derived SST, which is a NAVOCEANO operational product, are presented. As a by-product of the NAVOCEANO VIIRS SST evaluation, the non-linear SST (NLSST) equations used to derive the SST values were found to be less than optimal, depending on the unit of the field temperature term. NAVOCEANO VIIRS SST employs an expanded NLSST equation, which in effect refines the approximation of the gamma term by adding an offset. In view of the evaluation results, NAVOCEANO VIIRS SST became operational at the end of January 2013.

Data of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi National Polar-orbiting Partnership (NPP) have been acquired at Centre de Météorologie Spatiale (CMS) in Lannion (Brittany) in direct readout mode since April 2012. CMS is committed to produce sea surface temperature (SST) products from VIIRS data twice a day over an area covering North-East Atlantic and the Mediterranean Sea in the framework of the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF). A cloud mask has been developed and cloud mask control techniques have been implemented. SST algorithms have been defined, as well as quality level attribution rules. Since mid October 2012 a VIIRS SST chain, similar to that used for processing METOP AVHRR has been run in a preoperational mode. The corresponding bias and standard deviation against drifting buoy measurements (mid October 2012 to mid March 2013) are -0.05 and 0.37 K for nighttime and -0.13 and 0.46 K for daytime, respectively. VIIRS derived SST production is expected operational by mid 2013. The OSI-SAF VIIRS derived SST products are compliant with the Group for High Resolution SST (GHRSST) GDS V2.0 format.

Currently, two global Level 2 SST products are generated at NOAA from S-NPP VIIRS Sensor Data Records with two independent systems, JPSS Interface Data Processing Segment (IDPS) and Advanced Clear Sky Processor for Oceans (ACSPO) using different retrieval algorithms. The two products differently correlate with in situ SST and L4 analyses, and the performance of IDPS SST is suboptimal. In this context, evaluation of existing operational SST algorithms was undertaken to select the optimal algorithm for VIIRS. This paper describes methodology and results of the evaluation. For all tested algorithms, SST accuracy and precision are estimated from matchups of VIIRS brightness temperatures with in situ SST, and sensitivity of retrieved SST to true SST is calculated using the Community Radiative Transfer Model. These three retrieval characteristics are dependent on observational conditions and show significant spatial variability. Therefore, we evaluate the SST algorithms by quantifying favorability of spatial distributions of retrieval characteristics for global SST product. We define for this purpose Quality Retrieval Domain (QRD) as a part of the World Ocean, within which SST accuracy, precision and sensitivity meet predefined specifications on retrieval characteristics. We show that, given a set of specifications, the QRD significantly varies between the algorithms. This makes QRD an informative measure of the algorithms’ performance. Based on QRD estimates for a variety of specifications, we recommend for VIIRS the algorithms developed at the EUMETSAT Ocean and Sea Ice Satellite Application Facility as ones providing the maximum QRD under reasonable specifications on retrieval characteristics.

Errors in the radiometric calibration of detectors introduce stripe noise in the images captured by multidetector spectroradiometers. Consequently, native resolution sea surface temperature (SST) maps derived from these instruments often display pronounced striping which reduces the accuracy of the data and its usefulness for low-level processing tasks such as thermal front detection. An algorithm has been designed to reduce the effect of striping and improve the imagery quality of the National Environmental Satellite, Data and Information Service (NESDIS) Advanced Clear-Sky Processor for Ocean (ACSPO) SST products. Using three days of Terra/Aqua MODIS and NPP VIIRS top-of-atmosphere clear-sky calibrated radiances, the performance of the proposed method was tested via quantitative and qualitative analysis. Preliminary results reported in this paper demonstrate substantial improvement in image quality without any impact on the geometrical features or global statistics of SST data.

This paper evaluates the performance of MODIS (Terra and Aqua) thermal emissive bands using current Collection 5 (C5) and newly released Collection 6 (C6) Level 1B products with a focus on relative differences between the two instruments. Data from the Infrared Atmospheric Sounding Interferometer (IASI) serves as a transfer reference. Comparison was conducted using observations from simultaneous nadir overpasses (SNO) of the Metop-A satellite and Terra/Aqua satellites. SNO times and locations were determined based on satellite orbital two-line element sets and the SNO time difference was limited to within 30 seconds. Each IASI instantaneous field of view of 12 km is co-located with multiple MODIS pixels. The corresponding IASI simulated MODIS radiances are derived by convolutions of IASI hyperspectral data and MODIS relative spectral response functions. Data analysis results show that correlations of MODIS aggregated brightness temperature (BT) and IASI simulated BT are greater than 0.9. Differences between Aqua and Terra MODIS C5 are ranging between 2 and 6 K at lower BT and are within ±1 K at higher BT for photovoltaic bands 20-25 and 27-30. Corresponding differences from C6 products are significantly reduced to less than 2 K (except band 20). For photoconductive bands 31-36, measurements from MODIS C5 and C6 are nearly within ±1 K between Aqua and Terra.

The MODerate resolution Imaging Spectroradiometers (MODIS) onboard the NASA EOS Terra and Aqua spacecraft were launched on December 18, 1999 and May 4, 2002 respectively. They have both successfully operated on-orbit for more than a decade. The spectral characteristics of the MODIS instruments were calibrated pre-launch using a ground calibration device called the Spectral Measurement Assembly (SpMA). The ground spectral characterization was transferred to an on-board device called the Spectro-Radiometric Calibration Assembly (SRCA) for the Reflective Solar Bands (RSB) by measuring the sensor spectral responses near simultaneously with both SRCA and SpMA. After transferring the calibration reference from the SpMA, the SRCA was able to track the on-orbit spectral changes by performing periodic spectral mode operations. This paper provides brief descriptions of MODIS on-orbit spectral characterization via its on-board SRCA. In the algorithm description section, functional steps and spectral calibration methodologies are presented. This study will focus on MODIS SWIR bands (bands 5, 6, 7 and 26) as their center wavelengths are longer than 1μm, which is beyond the specified SRCA spectral calibration range. In addition to the SWIR bands, band 2 results are also included. Because of the pre-launch and on-orbit configuration differences, band 2 spectral characterization is referenced to the first onorbit results. A summary of Terra and Aqua MODIS on-orbit relative spectral response changes, such as center wavelength and bandwidth changes, is provided in this paper for all the RSB bands.

Pressure and temperature are fundamental properties of the oceanic water. They have varying effects on the processes that take place in oceans be they biological, physical or chemical while pressure always increases with respect to surface when you go down, temperature has a more complex variation with respect to the depth. Various tools and techniques are available to measure these properties. A combination sensor with high accuracy and response time would enable better measurements of these two parameters. This paper presents a novel structure based on simultaneous measurement of temperature and pressure sensing using Fiber Bragg grating (FBG) sensors. For this, proposed sensor heads for both temperature and pressure. Temperature measurement, two different types of sensor heads has been designed for this implementation. The first sensor head consists of a FBG which is fixed between ceramic block on one side and a bimetallic strip made up of aluminum and copper on the other. The second sensor head consists of the FBG which is fixed between two bimetallic strips. For pressure, in first type the FBG is fixed between silicon rubber foil and sensor head wall. In second method the FBG is fixed between two silicone rubber foils. The pressure on walls of silicon rubber foils elongates FBG, which results in shift of wavelength. Theoretical studies carried out on these proposed sensor heads resulted in an increase in temperature sensitivity of about six times greater than that of bare FBG sensor and pressure sensitivity of about eight times greater than that of bare FBG. Further, the proposed sensors have shown good linearity and stability.

To assess the on-orbit radiometric stability of imaging sensors, pseudo-invariant calibration sites (PICS) have been utilized and recommended by the Committee on Earth Observation Satellites (CEOS). In the African continent, the Libya 4 test site has been frequently used to detect long-term changes because of its spatial uniformity, temporal stability, and low atmospheric aerosol loading. The nominal location of the Libya 4 test site is centered at the latitude and longitude of +28.55° and +23.99° with a suggested usable area of 75 x 75 km. Previous cross-calibration studies have used subset areas of the test site around the CEOS suggested center coordinate regardless of the spectral characteristic of the site. In this study, yearly hyper-spectral collections from 2004 to 2012 around day of the year 170 were used from Earth Observing One (EO-1) Hyperion sensor over the Libya 4 site. To evaluate the spectral stability over a broad range over the Libya 4 site, a series of Region of Interest (ROI) covering approximate areas of 3 by 3 km were selected in the along track direction from +28.07° to 29.55° of latitude (about 170 km long), which is also a subset of the CEOS reference site. The reflectance variations in other ROIs are initially estimated by average deviation and compared with the spectral angle mapper (SAM) method using ROI number ‘0’ in year 2004 collection as a reference spectrum. To consider a practical application, SAM and average deviation metrics are limited by the wavelength ranges of Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) Relative Spectral Response (RSR), instead of using the entire range of the Hyperion spectrum. These ETM+ RSR’s focused SAM values are considered to be the sensor specific spectral stability of the Libya 4 site. The Libya 4 CEOS test site is shown to be a spectrally stable target where SAM angles are less than 1.6 degrees and average deviations are less than 5% reflectance level based on the reference spectrum in 2004 within ETM+ RSR Full- Width at Half-Maximum (FWHM) ranges.

When we talk about for the ship detection, identification and its classification, we need to go for the wide area of monitoring and it may be possible only through satellite based monitoring approach which monitors and covers coastal as well as the oceanic zone. Synthetic aperture radar (SAR) has been widely used to detect targets of interest with the advantage of the operating capability in all weather and luminance free condition (Margarit and Tabasco, 2011). In EU waters, EMSA(European Maritime Safety Agency) is operating the SafeSeaNet and CleanSeaNet systems which provide the current positions of all ships and oil spill monitoring information in and around EU waters in a single picture to Member States using AIS, LRIT and SAR images. In many countries, a similar system has been developed and the key of the matter is to integrate all available data. This abstract describes the preliminary design concept for an integration system of RADAR, AIS and SAR data for vessel traffic monitoring. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should be also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Land-based RADAR can provide ships positions detected and tracked in near real time. In general, SAR are used to acquire image data over large coverage area, AIS reports are obtained from ship based transmitter, and RADAR can monitor continuously ships for a limited area. In this study, we developed individual ship monitoring algorithms using RADAR(FMCW and Pulse X-band), AIS and SAR(RADARSAT-2 Full-pol Mode). We conducted field experiments two times for displaying the RADAR, AIS and SAR integration over the Pyeongtaek Port, South Korea.

The Terra and Aqua MODIS instruments have operated continuously for over 12 and 10 years respectively and are key contributors to the NASA Earth Observing System mission. The calibration for the 16 thermal emissive bands (TEB) is maintained on-orbit through scan-by-scan observations of a temperature controlled blackbody and deep space. Recently a potential calibration issue with Terra Band 29 (8.55 μm) was identified resulting in a possible long-term drift in Band 29 detector response. The long-term performance of Band 31 (11 μm) is considered stable and is used as a reference to track the relative stability of other TEB. Multiple observations of different Earth targets with a range of scene temperatures as a function of time are analyzed to assess MODIS TEB band-to-band calibration stability for Band 29.

Measuring the sea surface during tropical cyclones (TC) is challenging due to severe weather conditions that prevent shipboard measurements and clouds which mask the sea surface for visible satellite sensors. However, sea surface emission in the microwave L-band can penetrate rain and clouds and be measured from space. The European Space Agency (ESA) MIRAS L-band radiometer on the Soil Moisture and Ocean Salinity (SMOS) satellite enables a view of the sea surface from which the effects of tropical cyclones on sea surface emissivity can be measured. The emissivity at these frequencies is a function of sea surface salinity (SSS), sea surface temperature (SST), sea surface roughness, polarization, and angle of emission. If the latter four variables can be estimated, then models of the sea surface emissivity can be used to invert SSS from measured brightness temperature (T_B). Actual measured T_B from space also has affects due to the ionosphere and troposphere, which have to be compensated for, and components due to the galactic and cosmic background radiation those have to be removed. In this research, we study the relationships between retrieved SSS from MIRAS, and SST and precipitation collected by the NASA TMI sensor from the Tropical Rainfall Measuring Mission (TRMM) satellite during Hurricane Isaac, in August 2012. During the slower movement of the storm, just before landfall on the vicinity of the Louisiana Shelf, higher precipitation amounts were associated with lower SSS and slightly increased SST. This increased trend of SST and lower SSS under regions of high precipitation are indicative of inhibited vertical mixing. The SMOS Level 2 SSS were filtered by a stepwise process with removal of high uncertainty in T_B under conditions of strong surface roughness which are known to create noise. The signature of increased SST associated with increasing precipitation was associated with decreased SSS during the storm. Although further research is required, this study shows that there is a T_B signal from the sea surface beneath a tropical cyclone that provides information on roughness and salinity.