Sea surface salinity
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The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
All fields of satellite, airborne and ground remote sensing.
OCEANS 2020 - SINGAPORE
An OCEANS conference is a major forum for scientists, engineers, and end-users throughout the world to present and discuss the latest research results, ideas, developments, and applications in all areas of oceanic science and engineering. Each conference has a specific theme chosen by the conference technical program committee. All papers presented at the conference are subsequently archived in the IEEE Xplore online database. The OCEANS conference comprises a scientific program with oral and poster presentations, and a state of the art exhibition in the field of ocean engineering and marine technology. In addition, each conference can have tutorials, workshops, panel discussions, technical tours, awards ceremonies, receptions, and other professional and social activities.
To promote awareness, understanding, advancement and application of ocean engineering and marine technology. This includes all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.
Theory and Applications of Microwave Radiometry
Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.
Physics, medicine, astronomy—these and other hard sciences share a common need for efficient algorithms, system software, and computer architecture to address large computational problems. And yet, useful advances in computational techniques that could benefit many researchers are rarely shared. To meet that need, Computing in Science & Engineering (CiSE) presents scientific and computational contributions in a clear and accessible format. ...
It is expected that GRS Letters will apply to a wide range of remote sensing activities looking to publish shorter, high-impact papers. Topics covered will remain within the IEEE Geoscience and Remote Sensing Societys field of interest: the theory, concepts, and techniques of science and engineering as they apply to the sensing of the earth, oceans, atmosphere, and space; and ...
Theory, concepts, and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.
Microwave theory, techniques, and applications as they relate to components, devices, circuits, and systems involving the generation, transmission, and detection of microwaves.
IEEE Power Engineering Review, 1992
Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492), 2003
To identify and quantify spatial patterns in cetacean density in the eastern Pacific Ocean, we have built generalized additive models (GAMs) of encounter rate (number of sightings per km) and average school size based on the Southwest Fisheries Science Center's 1986-96 survey data. The survey area encompassed over 25 million sq. km, and the tracklines covered almost 200,000 km. Models ...
2008 New Trends for Environmental Monitoring Using Passive Systems, 2008
We present recent results from several studies and field experiments that were conducted to improve the retrieval of sea surface salinity from space, preparing for the soil moisture and ocean salinity (SMOS) mission. The sea surface roughness impact on L-band emissivity is analysed based on the data from the CoSMOS airborne campaign conducted in April 2006 in the Norway sea. ...
2009 IEEE International Conference on Signal and Image Processing Applications, 2009
This paper presents a new approach for retrieving sea surface salinity (SSS) from MODIS satellite data. In doing so, the least squares method is used which is based on the hypothesis of linearity between visual bands and the real sea surface salinity. The study shows that offshore sea surface salinity tends to be homogenous with SSS value of 33.8 psu. ...
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003
The small slope approximation (SSA) theory is applied to the prediction of the foam-free sea surface brightness temperatures at L-band and nadir incidence angle. If surface geometry is assumed to be Gaussian, the wind induced polarized brightness temperature signals are integral functions of the product of the directional curvature spectrum harmonics and electromagnetic weighting functions. At nadir incidence angle, these ...
IMS 2011 Microapps - A Multi-Level Conductor Surface Roughness Model
Life Sciences: Surface Enhanced Raman Spectroscopy, and more
Power: A Fundamental Ingredient of Advanced Science and Applied Technology - Adam Hamilton, APEC 2018
Geoff Mulligan: Welcome Address: WF IoT 2016
Quantum Computation - ASC-2014 Plenary series - 4 of 13 - Tuesday 2014/8/12
IMPASS: Intelligent Mobility Platform with Active Spoke System
2011 IEEE Dennis J. Picard Medal for Radar Technologies and Applications - James M. Headrick
3D Body-Mapping for Severely Burned Patients - Julia Loegering - IEEE EMBS at NIH, 2019
IEEE Magnetics Distinguished Lecture - Yoshichika Otani
BSIM Spice Model Enables FinFET and UTB IC Design
SCV SSIT Chapter Meeting, July 8, 2020, Ethics and Covid-19
Making Orthogonal Transitions with Climbing Mini-Whegs
A Robot to Mine the Moon
Microwave PCB Structure Selection Microstrip vs. Grounded Coplanar Waveguide: MicroApps 2015 - Rogers Corporation
Silicon THz: an Opportunity for Innovation
The ALMA Array: An IMS 2013 Closing Keynote
IROS TV 2019-STAR LAB at the University of Surrey Space Technology for Autonomous systems & Robotics
Perpendicular magnetic anisotropy: From ultralow power spintronics to cancer therapy
Lighting the Way: Optical Sensors in the Life Sciences
To identify and quantify spatial patterns in cetacean density in the eastern Pacific Ocean, we have built generalized additive models (GAMs) of encounter rate (number of sightings per km) and average school size based on the Southwest Fisheries Science Center's 1986-96 survey data. The survey area encompassed over 25 million sq. km, and the tracklines covered almost 200,000 km. Models were constructed using stepwise selection of predictor variables, including time-invariant geographic variables (latitude, longitude, offshore distance, ocean depth, slope of the ocean floor) and temporally dynamic oceanographic and biological variables (sea surface temperature, gradient in sea surface temperature, sea surface salinity, thermocline depth, thermocline strength, depth of the euphotic zone, and chlorophyll concentration). We built separate models to describe the northern and southern regions of our study area for each of the following eight species or species groups: blue whale (Balaenoptera musculus, n= 98 sightings), fin whale (B. physalus, n=44), sei and Bryde 's whales (B. borealis and B. edeni, respectively; n=99 sightings total), sperm whale (Physetermacrocephalus, n=165), dwarf and pygmy sperm whales (Kogia sima and K. breviceps, respectively; n=89 sightings total), Cuvier's beaked whale (Ziphius cavirostris, n=99), beaked whales of the genus Mesoplodon (n=94), and delphinids (n=2413). One variable that factored prominently into the analysis was sea surface temperature, which was correlated with the encounter rates of delphinids and sei/Bryde's whales, and with the school sizes of delphinids, sperm whales, blue whales, and sei/ Bryde's whales. In addition, thermocline characteristics helped explain observed patterns in the encounter rates of delphinids and blue whales, and the school sizes of Cuvier's beaked whales and sei/Bryde's whales.
We present recent results from several studies and field experiments that were conducted to improve the retrieval of sea surface salinity from space, preparing for the soil moisture and ocean salinity (SMOS) mission. The sea surface roughness impact on L-band emissivity is analysed based on the data from the CoSMOS airborne campaign conducted in April 2006 in the Norway sea. Comparisons with electromagnetic scattering models used in SMOS algorithm indicate likely overestimation in the sea surface spectrum model energies at decimetric surface wave scales.
This paper presents a new approach for retrieving sea surface salinity (SSS) from MODIS satellite data. In doing so, the least squares method is used which is based on the hypothesis of linearity between visual bands and the real sea surface salinity. The study shows that offshore sea surface salinity tends to be homogenous with SSS value of 33.8 psu. Onshore SSS variation, however, has irregular pattern as compared with offshore SSS that is ranged between 28.5 and 29.5 psu. The results also show a good correlation between in situ SSS measurements and the SSS that is retrieved from MODIS satellite data with high r2of 0.96. In conclusion, the least squares method can be used to provide a new algorithm for SSS retrieval from MODIS satellite data with RMS of bias value of ±0.37 psu.
The small slope approximation (SSA) theory is applied to the prediction of the foam-free sea surface brightness temperatures at L-band and nadir incidence angle. If surface geometry is assumed to be Gaussian, the wind induced polarized brightness temperature signals are integral functions of the product of the directional curvature spectrum harmonics and electromagnetic weighting functions. At nadir incidence angle, these electromagnetic weighting functions are equals in magnitude for horizontal and vertical polarization and exhibit peaky distribution as function of wavenumber. Using these properties together with azimuthal characteristics of the directional curvature spectrum at L-band, the combination of vertically and horizontally polarized brightness temperature signals at normal incidence is shown to form a simple linear equation of the dielectric constant, the SST and the wind direction. A simple analytical inversion algorithm is proposed to retrieve the Sea Surface Salinity without a priori knowledge of the wind speed using the previously established dependence.
The Aquarius/SAC-D mission will employ three L-band (1.41 GHz) radiometers dedicated to remote sensing of sea surface salinity. The mission will be in a dawn/dusk sun- synchronous orbit with the beam oriented toward the night time side of the orbit in order to limit interference from the Sun. The effect of surface roughness on solar radiation reflected from the surface will be examined. It will be shown that including the small scale roughness (waves) can have a major impact. Also, it will be shown that when the small scale waves are included it is possible to have significant radiation reflected into the main beam during seasonal extremes when a portion of the main beam is on the illuminated side of day-night terminator.
A project was proposed, and funded, to use the airborne polarimetric L-band multi-beam radiometer (PLMR) to observe salinity gradients across the continental shelf in order to evaluate the cross-shelf mixing and residence time for water in the Great Barrier Reef. This paper examines issues of accuracy and uses first results from the project to demonstrate that the PLMR is capable of observing salinity gradients of the order of 0.01 PSU per km.
In preparation for SMOS Cal/Val phase, we simulate SMOS retrieved data (first cm) from in situ data (a few meters depth). We study vertical gradients of salinity in the Tropical Atlantic Ocean with three types of data: TSG and XCTD measurements from boats (POLARSTERN and ARAMIS project) and from ARGO floats. Between 0 and 10degnorth, nearly 5% of vertical gradients between 5 and 10 m are larger than 0.1 psu. They appeared in a zone characterized by warm SST and low wind and are linked to rain events or river discharges. The mean value of all the data stays less than 0.02 psu. However their distribution is skewed towards positives values, implying a non Gaussian repartition of differences between SMOS and in situ data.
The WISE 2000 and WISE 2001 field campaigns were sponsored by ESA to gather experimental data to improve the knowledge of the L-band brightness temperature dependence with wind speed at different incidence angles and azimuth angles. The goal is to help the development of sea surface salinity retrieval algorithms for SMOS Earth Explorer Mission of the European Space Agency. The L-band AUtomatic RAdiometer (LAURA) plus other sensors to characterize the sea surface state were installed at the Casablanca oil rig, 40 km south east off the coast of Tarragona in Spain. During WISE 2000 wind conditions were low-to-moderate, but during WISE 2001 two strong storms beat the Catalonian coast with sustained winds higher than 100 km/h at the platform meteorological station (69 m height). The first results of the radiometric measurements (azimuth and elevation scans) acquired with LAURA during the WInd and Salinity Experiment (WISE-2001) are presented.
This article explains the way to resolve one of the main difficulties of using neural networks to retrieve the ocean salinity from SMOS observations. By designing a set of networks which inputs are adapted to the variability of SMOS incidence angles, we are able to process practically any point on the ocean surface
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