Remote sensing science is one of the most modern approaches for studying oceans, littoral regions, seas and large lakes, as well as sea ice covered regions. An important aspect of remote sensing science is the ability to monitor complex environmental media (air, land, water) and their interfaces (water surface wave, air-sea interaction, water-sediment, and internal interfaces). Understanding complex environmental system phenomena is key to scientific understanding of oceans, littoral zones, estuaries, coastal areas, large lakes, ports and waterways as well as sea ice dynamics since remote sensing data provides valuable monitoring information. This information often serves as input to complex numerical models of environmental systems, such as climate change models, coupled oceanic-atmosphere models at the global (planetary) scale as well as at the mesoscale space and time scales. Remote sensing techniques also provide the most valuable tool set and techniques for monitoring and mapping different bottom features in aquatic systems, such as coral reefs, submerged aquatic vegetation and other "targets" of interest to the oceanographic and aquatic community. Also of interest are robotic and mechatronic platforms for in-situ sensing of interfaces and unique sensing systems & platforms for coastal and ocean monitoring and associated data assimilation into predictive models.

There is a need to improve the accuracy and precision of retrieved geophysical parameters from remote sensing data, and a need to use optical signal processing or filtering of remotely sensed signals from instruments to help improve underwater visibility and atmospheric aerosol influences that affect mapping subsurface water properties, features, and targets. In this context, it is often necessary to integrate data from different sensors as well as to include the knowledge of different disciplines. This is especially important in remote sensing of water quality, submerged aquatic vegetation and coupled ocean-atmosphere models. From a remote sensing point of view, these data are mainly extracted from active or passive sensor systems, and models of complex phenomena are important. Techniques important to the above include radar, acoustic, optical, sensing systems and resulting data and EO sensing of aerosols and turbulence.

With reference to the above, this conference will address the above remote sensing systems and platforms with special emphasis on areas such as:

  • detection of coastal & ocean currents and oceanic frontal features; radar and altimeter uses
  • subsurface sensing using acoustics, optical, laser and magnetic systems, hyperspectral systems
  • ocean sensing techniques and systems including microwave, acoustic and magnetic sensing and EO modeling
  • ocean wave measurement & altimetry as well as coastal imaging systems and analysis including remote sensing of breaking waves, whitecaps, foam, bubbles, and aerosol exchanges
  • use of remote sensing data in global and regional ocean observing platforms
  • use of satellite & airborne data in ocean, coastal & coastal lagoon water quality assessments
  • coastal ocean, estuarine and large lake water-quality monitoring (suspended sediments, dissolved organic matter, phytoplankton pigments and biomass, submerged aquatic vegetation) as well as other bottom feature and target recognition studies
  • oceanic photochemistry and hyperspectral remote sensing; coupled oceanic and mesoscale models at the air-sea boundary, remote sensing input and data assimilation into atmospheric sea breeze models, weather forecasting uses of marine remote sensing data & imagery
  • sensors, imaging and modeling of microwave signatures of ocean and coastal waves and sea ice
  • studies of glaciers, shore-fast ice; polar regions, sea ice prediction monitoring and modeling
  • cubesats, international space station (ISS) and multisatellite sensor configurations, georegistration and sensor integration from various platforms aboard the ISS
  • data fusion, image fusion, deep learning & artificial intelligence, optical signature analysis and modeling, hyperspectral imaging
  • sensor calibrations, airborne sensors & systems and data analysis
  • radar and related active-passive (Raman) sensing theory, applications, systems and techniques
  • regional and global sea and ice monitoring in climate change research, particularly work related to new satellite and suborbital missions with the new SAR instruments designed to investigate continental and marine sea ice thickness change
  • novel use of GNSS signals in large water regions, lakes & coastal regions sensing and deep learning
  • operational glacier, sea ice, ice sheets monitoring and systems (Cryosat, ICEsat, IceBridge, GRACE, IceCube)
  • active and passive remote sensing and techniques for improving underwater imaging for mapping ports, waterways and harbors, and effects of aerosols and turbulence in retrieving geophysical variables
  • airborne (manned, UAV’s, drones) remote sensing missions for observation of oceanic, coastal, sea ice and large water regions, and nearby urban environments; natural disasters; sensor design and calibrations.


  • Note: Special Sessions and Volunteer Session Chair Call:


    Abstracts and papers concerning the above topics and special sessions are invited for review and acceptance for presentation at the conference & publication in the proceedings. Those interested in developing the special session or joint sessions may contact the session chairs, members of the technical committee or contact Charles Bostater at Florida Institute of Technology: bostater@fit.edu.;
    In progress – view active session
    Conference 11857

    Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2021

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    • Remote Sensing Plenary Presentation I: Monday
    • Security+Defence Plenary Presentation
    • Remote Sensing Plenary Presentation II: Wednesday
    • Bathymetry, Shallow Waters and Suspended Sediments
    • Oil, Fluorescence and Hyperspectral Sensing
    • Water Quality and Bio-optical Sensing and Modelling
    • Water Bottom and Surface Wave Sensing
    • Scattering and Multispectral Sensing
    • Poster Session
    Remote Sensing Plenary Presentation I: Monday
    Livestream: 13 September 2021 • 16:30 - 17:30 CEST
    11858-500
    Author(s): Pierluigi Silvestrin, European Space Research and Technology Ctr. (Netherlands)
    On demand | Presented Live 13 September 2021
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    In recent years the Earth observation (EO) programmes of the European Space Agency (ESA) have been dramatically extended. They now include activities that cover the entire spectrum of the wide EO domain, encompassing both upstream and downstream developments, i.e. related to flight elements (e.g. sensors, satellites, supporting technologies) and to ground elements (e.g. operations, data exploitation, scientific applications and services for institutions, businesses and citizens). In the field of EO research missions, ESA continues the successful series of Earth Explorer (EE) missions. The last additions to this series include missions under definition, namely Harmony (the tenth EE) and four candidates for the 11th EE: CAIRT (Changing Atmosphere InfraRed Tomography Explorer), Nitrosat (reactive nitrogen at the landscape scale), SEASTAR (ocean submesoscale dynamics and atmosphere-ocean processes), WIVERN (Wind Velocity Radar Nephoscope). On the smaller programmatic scale of the Scout missions, ESA is also developing two new missions: ESP-MACCS (Earth System Processes Monitored in the Atmosphere by a Constellation of CubeSats) and HydroGNSS (hydrological climate variables from GNSS reflectometry). Another cubesat-scale mission of technological flavor is also being developed, Φ-sat-2. Furthermore, in collaboration with NASA, ESA is defining a Mass change and Geosciences International Constellation (MAGIC) for monitoring gravity variations on a spatio-temporal scale that enables applications at regional level, continuing - with vast enhancements - the successful series of gravity mapping missions flown in the last two decades. The key features of all these missions will be outlined, with emphasis on those relying on optical payloads. ESA is also developing a panoply of new missions for other European institutions, namely Eumetsat and the European Union, which will be briefly reviewed too. These operational-type missions rely on established EO techniques. Nonetheless some new technologies are applied to expand functional and performance envelopes. A brief resume’ of their main features will be provided, with emphasis on the new Sentinel missions for the EU Copernicus programme.
    Security+Defence Plenary Presentation
    Livestream: 14 September 2021 • 09:00 - 10:00 CEST
    11868-500
    Author(s): Patrick R. Body, Tecnobit (Spain)
    On demand | Presented Live 14 September 2021
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    Optronic systems for the defence market are available from the UV to the LWIR wavelengths but the ideal band very much depends on the particular application and their environment. This lecture will cover some of the more important features of each type of optronic sensor and using examples from the experience gained over many years of system development by Tecnobit for Airborne, Navel and Land sectors, suggests some broad recommendations.
    Remote Sensing Plenary Presentation II: Wednesday
    Livestream: 15 September 2021 • 09:00 - 10:00 CEST
    11858-600
    Author(s): Adriano Camps, Institut d'Estudis Espacials de Catalunya (Spain)
    On demand | Presented Live 15 September 2021
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    Today, space is experiencing a revolution: from large space agencies, multimillion dollar budgets, and big satellite missions to spin-off companies, moderate budgets, and fleets of small satellites. Some have called this the “democratization” of space, in the sense that it is now more accessible than it was just a few years ago. To a large extent, this revolution has been fostered on one side by the standardization of the platforms’ mechanical interfaces, and on the other side by the technology developments coming from mobile communications. Standard platform’s mechanical interfaces have led to standard orbital deployers, and new launching capabilities. The technology developed for cell phones has brought more computing resources, with less power consumption and volume. Small satellites are used as pure technology demonstrators, for targeted scientific missions, mostly Earth Observation, some for Astronomy, and they are starting to enter in the field of communications, as huge satellite constellations are now becoming more possible. In this lecture, the most widely used nano/microsats form factors, and its main applications will be presented. Then, the main Scientific Earth Observation and Astronomy missions suitable to be boarded in SmallSats will be discussed, also in the context of the rising Constellations of SmallSats for Communication. Finally, the nanosat program at the Universitat Politècnica de Catalunya (UPC) will be introduced, and the results of the FSSCAT mission will be presented.
    Bathymetry, Shallow Waters and Suspended Sediments
    Session Chair: Larissa Marques Freguete, Texas A&M Univ. Corpus Christi (United States)
    11857-1
    Author(s): Larissa M. Freguete, Michael Starek, Jacob Berryhill, Texas A&M Univ. Corpus Christi (United States)
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    Coastal zones are at the interface of land and sea and provide a buffer to storms, wave action, and coastal inundation. Bathymetric mapping of the submerged littoral zone is essential for the understanding of sediment transport and good coastal management and planning. Surf zones are dynamic areas, ever-changing, so there is a need for low-cost, rapid response aerial remote sensing techniques that can provide high temporal and spatial coverage of nearshore bathymetry. However, this is a challenging task given water turbidity, wave action, seafoam, and other issues. With this motivation, this study used a small unoccupied aircraft system (UAS) equipped with a digital RGB camera to collect video footage of wave action on the water surface. The video data was then used to apply a spectral depth inversion algorithm called cBathy and estimate nearshore bathymetry at high resolution. Ground truth data were collected using cross-shore transect surveys to a depth of 2 m for assessment of the UAS-based bathymetry estimates. The video data was split into frames with a frequency of 2 frames per second (fps), and ground control points (GCPs) laid out in the scene were used to perform image georectification. A time stack of image pixel values was then generated from the video data for the cBathy depth inversion algorithm. Accuracy assessment resulted in an overall RMSE of 0.2056 m for an area of 390 m offshore and 400 m alongshore, and the maximum depth achieved was up to 3 m. Results show the potential of the cBathy algorithm to provide reasonable depth accuracies in dynamic and turbid water surf zones. However, results also show that this method has constraints for which users need to be aware of prior to applying it, including the study site’s physical characteristics.
    11857-2
    Author(s): Evagoras Evagorou, Christodoulos Mettas, Cyprus Univ. of Technology (Cyprus), ERATOSTHENES Ctr. of Excellence (Cyprus); Diofantos Hadjimitsis, Cyprus Univ. of Technology (Cyprus)
    On demand
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    During the last years, many studies related to Satellite-Derived Bathymetry (SDB) emphasize the potential use of optical satellite remote sensing sensors for bathymetric estimation. For this study, ten multispectral SPOT 6/7 satellite images with a medium resolution covering the coastal waters of the study areas were analyzed. These images were geometric, radiometric, and atmospheric corrected and acquired in three different sensing dates having coverage with at least 30% of lidar data. A number of 5284 random depth measurements with 0 to 50 meters depth were acquired for the ratio conversion algorithm with absolute depths and error assessment. A series of steps were performed to obtain reliable results using satellite optical data such as sun glint process, land/sea extraction, kernel filters. The study area was divided into three sub-regions, based on the sensing date of the satellite imageries. The light attenuation in the water column increases at a depth of about thirty meters as seen in other related studies. This study identified the depth of light attenuation to determine the maximum depth that can be estimated through optical sensors. The results show that better correlation was identified up to 15 meters depth. Results of the regression analysis show the following correlation coefficients R² :0.90, 0.87, 0.80, and 0.89 with the Root Mean Square Error (RMSE) for the respective study areas to be 1.34, 1.53 1.70 and, 1.15.
    11857-3
    Author(s): Evangelos Alevizos, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (Greece); Alexandros Makris, Iason Oikonomidis, Anastasios Roussos, Institute of Computer Science, Foundation for Research and Technology-Hellas (Greece); Dimitrios D. Alexakis, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (Greece)
    On demand
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    Coastal bathymetry is a fundamental component in numerous research and engineering applications, however obtaining such data in detail for large areas is rather complicated due to several natural and technical limitations. In order to overcome these difficulties, we developed a pipeline of novel methods based on drone-imagery for producing high resolution, accurate coastal bathymetric data. As a result, this study was based on combination of state-of-the-art, high resolution datasets, including drone-based imagery and reference bathymetric points using a sonar sensor mounted on a remote-controlled unmanned surface vehicle (USV). Our approach relies on fusion of two conceptually different yet complementary methods for bathymetry estimation, a geometric one and a spectral one using deep learning. In the first approach, we developed a novel structure-from-motion technique, that natively incorporates the correct geometrical optics accounting for water refraction. In the second method we built upon the reconstructed surface of the geometric method together with the reference bathymetric data for training a deep convolutional network (CNN) using a set of spectral features from the RGB imagery. The CNN produced high resolution coastal bathymetry with vertical accuracy varying in the decimeter scale. The main advantage of this approach is that it exploits both the spectral and the multi-view aspects of drone imagery which function complementary to each other. The geometric method yields accurate 3D bathymetry over any kind of seafloor that shows sufficient texture on the images and where seafloor texture is absent, spectral information is utilized for harmonizing the bathymetry surface for the entire scene. Finally, this study demonstrates that modern, unmanned platforms can perform accurate coastal bathymetry mapping far more efficiently than traditional boat surveys, although ideal sea-state conditions are required for obtaining imagery data with optimal quality. This work is part of the ACTYS project (https://actys.ims.forth.gr/) that has received funding from FORTH-Synergy grant.
    11857-4
    Author(s): Olga Y. Lavrova, Ksenia R. Nazirova, Space Research Institute (Russian Federation); Dmitry M. Soloviev, Marine Hydrophysical Institute (Russian Federation); Alexey Y. Strochkov, Space Research Institute (Russian Federation); Yana O. Alferieva, Faculty of Geology, Lomonosov Moscow State University (Russian Federation); Tatiana Yu. Bocharova, Space Research Institute (Russian Federation)
    On demand
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    The performance of various standard algorithms for the retrieval of suspended particulate matter (SPM) from Sentinel-2 MSI and Landsat-8 OLI satellite data obtained in 2019 and 2021 is discussed. The study was conducted for the estuaries of 2 mountainous rivers originating in the Caucasus Mountains: the Sulak River flowing to the Caspian Sea and the Mzymta River flowing to the Black Sea. The rivers differ in the degree of flow control and the composition of terrigenous suspended matter carried to the sea. The main objective of the study was to compare SPM retrieval results of the C2RCC (Case 2 Regional Coast Color) processor and the ACOLITE (Atmospheric correction for OLI ‘lite’) algorithms Nechad 2009, Nechad 2015 and Dogliotti. The satellite data were verified against in-situ measurements of turbidity and SPM performed synchronously with the satellite survey. Field measurements from a small boat were performed in April and May 2019, 2021 in the northeast Black Sea, in the estuary of Mzymta, and in May 2021 in the Sulak estuary. The measuring instruments and methods included a turbidity sensor mounted on a CTD (conductivity / temperature / depth) probe, a portable turbidimeter, and water sampling for further laboratory analysis. It was established that for low SPM, 20-30 g/m3, performances of C2RCC and Nechad 2015 practically coincided and correlated well with the in-situ data. For large SPM, over 300 g/m3, the best performance was demonstrated by Dogliotti, the algorithm designed especially for extreme SPM values. The work was carried out with financial support of the Russian Science Foundation grant #19-77-20060. Processing of satellite data was carried out by Center for Collective Use “IKI-Monitoring” with the use of “See The Sea” system.
    Oil, Fluorescence and Hyperspectral Sensing
    Session Chair: Emna Amri, Univ. Savoie Mont Blanc (France)
    11857-5
    Author(s): Remika S. Gupana, Daniel Odermatt, Eawag (Switzerland), Univ. Zürich (Switzerland); Abolfazl Irani Rahaghi, Eawag (Switzerland); Camille Minaudo, Ecole Polytechnique Fédérale de Lausanne (Switzerland); Alexander Damm, Univ. Zürich (Switzerland), Eawag (Switzerland)
    On demand
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    Sun-induced fluorescence (SIF) emission can be used as a proxy for chlorophyll-a concentration (chl a) and as an indicator of phytoplankton physiological status. However, retrieving and interpreting the SIF signal is challenging due to physiological factors, optical properties of the atmosphere and the water body, instrumental effects, and assumptions inherent to retrieval schemes. Due to the complexity of factors determining SIF occurrence, lack of measurement protocols and few studies on retrieval methods, its exploitation remains limited, especially in lakes. To address some of these challenges, we assess SIF estimate sensitivity to quantum yield of fluorescence (φF). Often assumed constant, φF exhibits a diel cycle related to light stress, which impacts the interpretation of fluorescence signals. Determining φF allows us to estimate and predict SIF diurnal variability, evaluate how this variability impacts chl a estimates, and gain insight into photosynthetic activity of the phytoplankton community. We address the dynamics of φF by using high-frequency optical measurements in Lake Geneva. From this dataset, we are able to calculate φF, infer the strata where non-photochemical quenching occurs and how this affects the SIF signal detected above water. We compare chl a estimates obtained from fluorescence and absorption measurements to assess at which conditions fluorescence-derived estimates are underestimated, and at which conditions saturation irradiance for photosynthesis is reached. The increasing availability of hyperspectral satellite data could improve SIF retrieval since algorithms utilizing contiguous bands can be implemented. Subsequently, an improved retrieval scheme will allow for better φF estimation. An upcoming satellite mission from ESA, the Fluorescence Explorer,designed to measure terrestrial SIF globally, can potentially be used in aquatic environments. Through this study, we demonstrate how hyperspectral measurements improve SIF signal interpretation by understanding φF dynamics. Despite using in-situ data, our findings can also contribute to the evaluation of SIF estimates from hyperspectral satellite data.
    11857-6
    Author(s): Emna Amri, Hermann Courteille, Alexandre Benoit, Philippe Bolon, Univ. Savoie Mont Blanc (France); Dominique Dubucq, Gilles Poulain, Anthony CREDOZ, Total SE (France)
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    Ocean surface monitoring, especially oil slick detection, has become mandatory due to its importance for oil exploration and risk prevention on ecosystems. For years, the detection task has been performed manually by photo-interpreters using Synthetic Aperture Radar (SAR) images with the help of contextual data such as wind. This tedious manual work cannot handle the increasing amount of data collected by the available sensors and thus requires automation. Literature reports conventional and semi-automated detection methods that generally focus either on oil slicks originating from anthropogenic (spills) or natural (seeps) sources on limited data collections. As an extension, this paper presents the automation of offshore oil slicks on an extensive database with both kinds of slicks. It builds upon the slick annotations of specialized photo-interpreters on Sentinel-1 SAR data for 6 years over 3 exploration and monitoring areas worldwide. All the considered SAR images and related annotation relate to real oil slick monitoring scenarios. Further, wind estimation is systematically computed to enrich the data collection. Paper contributions are the following : (i) a performance comparison of two deep learning approaches: semantic segmentation using FC-DenseNet and instance segmentation using Mask-RCNN. (ii) the introduction of meteorological information (wind speed) is deemed valuable for oil slick detection in the performance evaluation. The main results of this study show the effectiveness of slick detection by deep learning approaches, in particular FC-DenseNet, which captures more than 92\% of oil instances in our test set. Furthermore, a strong correlation between model performances and contextual information such as slick size and wind speed is demonstrated in the performance evaluation. %Conclusion/implication This work opens perspectives to design models that can fuse SAR and wind information to reduce the false alarm rate.
    11857-7
    Author(s): Tyler A. Rotkiske, Charles Bostater, Florida Institute of Technology (United States)
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    A non-homogeneous water column Monte Carlo model is utilized for predicting underwater light fields in shallow estuarine waters with suspended muds/flocs and a bottom lutocline boundary layer. This previously developed model creates synthetic water wave surfaces. Outputs are presented to demonstrate the response to water wave facet slopes at the surface and a lutocline bottom fluid mud boundary layer. Synthetic reflectance spectrums and radiometric quantities are modeled with different solar and sensor zenith and azimuth angles. Measurements in Space Coast Florida waters are used as model inputs. Averaged depth dependent concentration profiles for particulate matter suspended from the bottom fluid mud and lutocline layers are estimated from sondes. In this report vertical profiles of shape factors with various water surface slopes and fluid mud assumptions are shown. Model results suggests that suspended muds in the water column will have unique higher absorption influences upon the photosynthetically active light region of the underwater light field.
    Water Quality and Bio-optical Sensing and Modelling
    Session Chair: Evagoras Evagorou, Cyprus Univ. of Technology (Cyprus)
    11857-9
    Author(s): Yossra Moktar, Isabela Walter, Maryam AlShehhi, Khalifa Univ. (United Arab Emirates)
    On demand
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    Water scarcity in hyper-arid regions have led many countries from the Arabian Gulf to invest in desalination plants as a mitigation strategy. Although desalination facilities are indeed a suitable approach to face the drought and supply countries with freshwater, it may bring adverse environmental effects from the long-term brine discharge into the sea. Due to the high reliance of the Gulf countries on desalinated water as the main source of potable water, it is required to regularly monitor the water quality surrounding the desalination plants. The main concerns include thermal pollution and increase in salinity, which can disturb and compromise marine life. Sea Surface Temperature (SST), Chlorophyll-a (Chl-a), and Salinity (SSS) are the most important parameters used to determine marine ecosystems changes and dynamics. SST has great influence on climate, being applied as an indicator of pollution and marine productivity. Chl-a reflects the primary production in marine environments and it performs as a phytoplankton biomass indicator. As an important sea water quality parameter, salinity has a direct effect on the stratification and circulation of the oceans, as well as salinity changes affect the dynamics of tropical oceans and air-sea interaction. Hence, the objective of this study is to analyze the environmental problems in the Arabian Gulf, by analyzing SSS, SST, and Chl-a over the last 20 years retrieved from satellite data. The satellite data of MODIS and SMOS have been pre-processed and time series analysis is performed to investigate the long term spatial and temporal changes in the aforementioned parameters. Additionally, machine learning clustering approach is used to study the spatial patterns of these parameters. By detecting change patterns, we can identify whether brine discharge has been altering such parameters. Furthermore, this will be critical to predict the future environmental impacts of desalination plants in the Arabian Gulf.
    11857-10
    Author(s): Zhe Chen, Yu Xia, Ying Jiang, Jing Zhao, Yibang Wu, Jingwei Li, Changjiang River Scientific Research Institute (China)
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    As an important area of wetland protection in the Yangtze River Economic Belt, Honghu Lake, located in the southern part of Hubei Province, is a habitat or wintering place for many wetland wild animals, including migratory waterfowl and some rare species. In the past two decades, the water environment of Honghu Lake has been suffering from serious deterioration due to the rapid development of agriculture and industry in the urbanization of surrounding areas, especially for the production pollution which tends to become more serious and complicated. Under the combined effect of multiple non-point source pollution and point source pollution, cyanobacteria blooms often occur here. As a proxy of eutrophication, chlorophyll-a (Chl-a) has been considered to be an important indicator of water quality parameters. For better understanding of the change of the water quality of Honghu Lake, an improved empirical model for estimating chlorophyll-a concentrations (Chl-a) from different multi-spectral satellites images was established and validated. (1) We combined the results of two and three-band algorithms(2BDA, 3BDA), normalized difference chlorophyll index (NDCI) and fluorescence line height (FLH) into support vector machine(SVM) model for better multi-nonlinear relationship establishment between Chl-a concentration and surface water reflectance, which acquired higher model accuracy.(2) Based on the long-term time series data derived from Landsat-7, Landsat-8 and Sentinel-2, the variation of Chl-a concentration of Honghu Lake over 20 years was acquired. (3) Our results demonstrate that the average chlorophyll concentration has been at a very high level and showing an increasing tendency in recent years, which may indicate the eutrophication in the Honghu Lake is still getting worse.
    Water Bottom and Surface Wave Sensing
    11857-14
    Author(s): Jennifer L. Closson, Charles R. Bostater, Florida Institute of Technology (United States)
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    Remote sensing technologies are useful tools when gathering spatial and temporal information about dynamic coastal regions. A method is presented using an in-situ space-time drone imaging technique for evaluating wave periods and wavelengths of surface water waves in shallow urban coastal water environments. High-definition drone video imagery (viewed near-nadir) of shallow water waves was acquired and time synchronized with littoral video imagery. Drone video imagery records of a wave patch with reflected sun glint and non-affected sun glint surface water waves facets, staff gauges, and a simultaneously deployed line target were used to determine wave periods and wavelengths. Time series analyses was applied to the video derived time series imagery. Wave energy spectrums can be extracted and used to simulate synthetic images using a gravity wave model based upon a Weibull probability distribution that simulates the sea state. Applications in shallow water coastal environments continue to benefit from knowledge of wind driven water waves. Data extracted from the Banana River in Florida was used to determine the procedure and techniques.
    Scattering and Multispectral Sensing
    Session Chair: Wanjiao Song, National Satellite Meteorological Ctr. (China)
    11857-21
    Author(s): Andrea Taggart, Charles R. Bostater, Florida Institute of Technology (United States)
    On demand
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    The type of bottom resting below the water surface may be difficult to be determined due to the contamination of pixels by glint in satellite reflectance imagery. A nearest neighbor non-glint pixel search algorithm was written in Python to correct glint contaminated pixels. An algorithm was then utilized to estimate water visibility and to analyze the results of the glint corrected pixels by using light attenuation depths and attenuation coefficients based upon glint corrected satellite reflectance in the WorldView-3 (WV-3) image channels. The aforementioned correction was undertaken for sand, mud, and seagrass bottom types. The results suggest that it is possible to estimate attenuation depths (a measure of water visibility).
    11857-22
    Author(s): Olga A. Danilicheva, e1aac196-c404-e011-af7f-005056814748 (Russian Federation); Irina A. Sergievskaya, Stanislav Ermakov, Olga Shomina, Alexander Kupaev, Ivan Kapustin, Institute of Applied Physics (Russian Federation)
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    The paper is focused on investigation of microwave backscattering from wind waves on a clean water surface. Field experiments were carried out in the coastal zone of the Black Sea using dual co-polarized Doppler X-band scatterometer and a three-band Doppler dual co-polarized radar (X-, С-, S-bands). The radar incidence angles were about 50 - 60 degrees, the wind changed in a wide range of speeds. We assumed that microwave backscattering at VV and HH polarizations is composed by a Bragg (polarized) component associated with Bragg waves and a non-polarized component (NBR). Analysis of Doppler spectra of NBR allowed us to remove the effect of strong wave breaking (overturning wave crests) from the time series and to study the backscatter associated only with dm-scale waves. Measurements of wind waves with a wire gauge were carried out simultaneously with the radar monitoring. It is shown that the velocities of non-Bragg scatterers not associated with strong wave breaking in X-, С-, S-bands correspond to the velocities of short dm waves and weakly depend on radar wavelength. The speeds of the scatterers in X-, С-, S-bands associated with overturning wave crests are also close to each other (within the measurement error). The intensity of NBR in X-, С-, S-bands grows with wind speed as well as with the intensity of dm-waves measured by the wire gauge. Strong suppression of NBR and simultaneously measured decrease of short dm-wave intensity are demonstrated, thus confirming the assumption that the intensity of the NBR in X-, С-, S-bands is determined by dm waves. This work was funded by the Russian Foundation of Basic Research (19-05-00605, 18-45-520008) and by the Russian Ministry of Sciences (Project Goszadanije 0030-2021-0006).
    Poster Session
    11857-23
    Author(s): Marina I. Mityagina, Olga Y. Lavrova, Space Research Institute (Russian Federation)
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    This paper discusses some aspects of satellite data usage in monitoring the surface oil pollution in the off-shore oil-producing area in the Caspian Sea. Our primary study area is the major shelf oilfield, “Oil Rocks,” located 35 km off the coast of the Caspian Sea. Oil films are always present on the sea surface here, covering 200 – 1000 sq. km2. We observe and identify large oil slicks in most radar images and many “cloudless” images of optical sensors in VIS bands taken over this oil-production site. Our primary data is SAR imagery obtained by Sentinel-1A, 1B satellites, and imagery taken by scanning radiometer OLI-TIRS of Landsat-8 satellite and by MSI instrument of Sentinel 2A in 2015-2020. We present a detailed map of the spatial distribution of oil slicks detected in satellite imagery and outline areas of high-risk sea surface oil pollution and areas exposed to potential risks. We present statistics on individual sizes of oil patches and describe their seasonal and inter-annual variability and statistics on the frequency of detection of oil patches depending on near-surface winds and ocean-atmosphere boundary layer conditions. We show that the frequency of reliable detection of natural oil showings in satellite images varies greatly and depends sufficiently on a sensor type and the season. The work was supported by the Russian Science Foundation Project # 19-77-20060. Processing of satellite data was carried out by the Center for Collective Use “IKI-Monitoring” with the use of the “See The Sea” system that was implemented in the frame of Theme “Monitoring,” State register No. 01.20.0.2.00164.
    11857-25
    Author(s): Olga A. Danilicheva, Institute of Applied Physics (Russian Federation); Stanislav A. Ermakov, Ivan A. Kapustin, Institute of Applied Physics (Russian Federation), Volga State Univ. of Water Transport (Russian Federation)
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    Investigation of the mixing processes in the river confluence zone is a challenging problem, particularly in application to ecological monitoring of rivers and inland waters. The dynamical processes in the confluence zone can be very complex and can affect riverbed deformation, pollution transport, etc. The river confluence or mixing zone (MZ) is usually visually observed as the relatively thin transition region separating two parallel weakly mixing flows. The typical examples are the confluence of the Rhone and Arve (Switzerland), Rio Negro and Rio Solimoes (Brazil), etc. River MZ at positive air temperatures can be clearly observed visually and in optical imagery due to the flow color difference. Sometimes manifestation of the confluence zone also can be visually observed as a slick band in the mixing area. In the present work, sequential satellite optical (Sentinel-2 MSI) and radar (Sentinel-1 SAR) images of the mixing zone of the Oka and the Volga rivers (Russia) during the active ice cover melting were analyzed. The ice melting begins from the mixing zone area after the point of the river confluence. A wet snow area is formed in the MZ at the initial stages of ice melting. With a further increase in the average air temperature, the area continues to melt, and a polynya appears which is transformed further to a long open water band. This banded polynya is supposed to be associated with both emissions from factories and thermal power plants and with the turbulent mixing of river flows. An increase in the radar signal backscattering of wet snow was observed, which can be associated with an increase in the roughness of the wet snow. Although the wind velocity during the observation period was about 3-5 m/s, which significantly exceeded the threshold of wind wave excitation, the waves were rather small, in particular, due to the wind wave damping on the water covered with the ice floes. This led to the manifestation of the MZ as an extended dark band.
    11857-26
    Author(s): Aleksei V. Ermoshkin, Ivan A. Kapustin, Nikolay A. Bogatov, Alexander A. Molkov, Eugeny I. Poplavskiy, Nikita S. Rusakov, Institute of Applied Physics (Russian Federation); Alexander R. Yunisov, LLC "Radionavigation Company" (Russian Federation)
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    The present paper considers the possibility of a system for environmental monitoring of film pollution in the Gorky reservoir. A combination of the well-known approachs for calculating the drift trajectories of passive particles on the sea surface with the data of remote sensing, which provides primary detection of a pollution spill in the scanned area is proposed. X-band digital coherent radar was the source of remote data. Based on this radar, an automated radar system is being developed for the automatic detection of film contaminants on the water surface. The results of tests of the algorithm for automatic detection of film pollutions based on field measurements are presented. The model component of the system is based on the results of measurements of current velocities and the physical dependence of the slick drift. As a result of comprehensive studies, the developed system has demonstrated operability for detecting and predicting the spread of film pollution in the Gorky reservoir.
    11857-27
    Author(s): Yuliya Troitskaya, Victor Abramov, Georgy Baydakov, Olga Ermakova, Daniil Sergeev, Alexei Ermoshkin, Alexander Kandaurov, Nikita Rusakov, Evgeny Poplavsky, Maxim Vdovin, Institute of Applied Physics (Russian Federation)
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    This work is concerned with modeling the scattering of a microwave signal on a wavy water surface in laboratory conditions. The experiment was carried out on the IAP RAS Wind-Wave Tank 10 m long, with a cross section of 0.4 by 0.4 m2, and a wind speed range from 5 to 25 m/s (which is equivalent to U10 from 7 to 40 m/s). At the same time, radar measurements and measurements of waves and wind flow parameters were carried out, the latter were carried out using a system of wave gauges and a Pitot tube. The system represents an antenna of three resistance-type wave gauges located in the corners of a triangle of equal sides with a side of 2.5 cm. Such a system allows the reconstruction of the frequency-wave number spectra of surface waves using the Fourier directional method (FDM). The upper limit of the wave number spectrum is determined by the distance between the wave gauges in the antenna and is equal to 1.25 rad/cm. The air flow parameters were measured in the working section using an S-shaped pitot tube. To determine the parameters of the atmospheric boundary layer, an algorithm based on the self-similarity of the velocity profile in the channel was used. Microwave measurements were carried out using an X-band coherent Doppler scatterometer with a wavelength of 3.2 cm with sequential reception of linear polarizations. The antenna of the scatterometer was a pyramidal horn with a square section of 224 mm x 224 mm and a length of 680 mm, which was equipped with an orthogonal mode transducer (OMT) with a polarization separation of more than 40 dB; the beam width was 9 degrees. The observation window had dimensions of 40 cm x 40 cm, the incidence angle was 30, 40, and 50 degrees in the upwind and downwind direction, the area around working section was covered with special radio-absorbing material in order to screen parasitic reflections. As a result of measurements, the dependences of NRCS on wind speed and friction velocity at high wind speeds were obtained. It is shown that the cross-polarized NRCS demonstrates sensitivity to the wind speed when its value is more than 20 m/s, in contrast to the co-polarized NRCS. Based on the analysis of the Doppler spectra, it was suggested that the backscattered signal is formed mainly on wave breakers. This assumption was verified by analyzing the dependence of the scattered signal power at both polarizations on the area of the white-cap coverage, which revealed their direct dependence. Based on the phenomenological approach used in statistical physics, a parametrization of the dependence of the white-cap coverage fraction on the wind friction velocity was proposed. This parametrization was based on the use of the universal Gibbs method, the central concept of which is a canonical ensemble or an ensemble of a thermodynamic system states which are in a weak thermal contact with a "thermostat". In this case, the atmospheric boundary layer acts as a thermostat, and the entire ensemble of states of the sea surface, including breakers, is the canonical ensemble. Based on this parametrization, the GMF was proposed to retrieve the wind speed and wind friction velocity for wind speeds above 40 m/s, which also considering the angular dependence of the NRCS.
    11857-28
    Author(s): Olga Ermakova, Nikita Rusakov, Evgeny Poplavsky, Daniil Sergeev, Galina Balandina, Yuliya Troitskaya, Institute of Applied Physics (Russian Federation)
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    This paper describes an algorithm for wind speed retrieval based on the data processing obtained from GPS-dropsonde measurements and their correct collocation with SAR images, where the normalized radar cross-section (NRCS) acts as a brightness characteristic. GPS-dropsonde represents the main NOAA mission tool to obtain vertical wind profiles in tropical cyclones. Since the measured instantaneous wind speed profiles are characterized by a high level of fluctuations, in order to obtain mean wind speed profile, we constructed the statistical ensemble including the profiles having a similar shape, obtained from GPS-dropsonde launched in approximately the same conditions. Usually, the airflow parameters are retrieved from measurements made in the logarithmic part of the turbulent boundary layer located in its lower part. The retrieval of the parameters in this part leads to large errors due to the lack of data associated partly with the influence of surface waves. In this regard, by analogy with the approach used in technical hydrodynamics, an assumption was made and verified that the velocity profile appears self-similar. Using this assumption makes it possible to retrieve the parameters of the airflow from the measurements of the wake part, which is located in the upper part of the turbulent boundary layer and contains fewer errors and more data. This methodology was applied to the dataset of category 4-5 tropical cyclones observed in the Atlantic Basin during the period 2003-2017. As a result, the values of the friction velocity and the aerodynamic drag coefficient were obtained, which are necessary for constructing empirical dependencies connecting these parameters with NRCS of the microwave signal backscattered from the water surface. The dependence of Cd on U10 was constructed demonstrating a well-known effect of reducing surface drag coefficient for the velocities with the values exceeding 30 m/s. Cross-polarized images of the sea surface obtained from the ESA Sentinel-1 satellite were used as SAR images. We used cross-polarized images, since in the case of direct polarization, the dependence of the received microwave signal power is saturated at high wind speeds. To compare the data from GPS-dropsonde with SAR images, it is necessary to collocate them in time and space. The main problem is the lack of data from the GPS-dropsonde obtained directly on the day of the image acquisition, so it becomes necessary to use the data obtained on the neighboring days. Such an approach becomes possible if the hurricane has already formed and retains its structure throughout the time of data collection. This assumption of quasi-stationarity was verified by analyzing the time dependences of the tropical cyclone dynamic parameters (Maximum Wind Speed, Minimum Sea Level Pressure). Thus, the statistical ensemble for averaging included data from GPS-dropsonde located close to each other and obtained a day before and after the time the SAR image was made. This data collocation procedure was successfully carried out for hurricanes Irma and Maria (Irma 2017/09/07, Maria 2017/09/21 and 2017/09/23). Comparison of the obtained dependences of NRCS on the wind speed at meteorological height and on the dynamic wind speed were compared with the data obtained in the work of Hwang (2015), and showed a good agreement. At the same time, in the region of high wind speeds, the dependence of NRCS on the dynamic wind speed demonstrates an ambiguous behavior, which may be associated with the sectoral dependence of the boundary layer parameters in a tropical cyclone.
    11857-29
    Author(s): Aleksei V. Ermoshkin, Mikhail B. Salin, Ivan A. Kapustin, Alexander Molkov, Nikolay A. Bogatov, Institute of Applied Physics (Russian Federation)
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    The present paper is devoted to the development of a multisensory approach to hydrophysical measurements of the ocean surface layer. The combination of coherent acoustic sounding, coherent radar sounding, and optical stereo photography is considered. Each of the methods separately has several advantages, but it is not free from disadvantages. Coherent acoustic sounding, described by resonant scattering, has a large observation area but has a poor spatial resolution. Coherent radar sensing, also described by resonant scattering, has a smaller observation area but a higher spatial resolution. Both methods allow us to recover the velocity characteristics of scattering associated with the velocities of resonant scatterers. Using the relationship between sea surface elevations and orbital wave velocities, it is possible to determine the spatial spectra of wind waves in a wide range of wind wavelengths up to several meters. To determine the characteristics of shorter-scale wind waves, it is proposed to use data from optical stereo photography. As a calibration for the optical system, information on the elevation of the sea surface obtained from coherent acoustic and radar sounding data can be used. Thus, the spatial spectrum of wind waves can be reconstructed in the range of energy-carrying to gravitational-capillary waves. In addition to the spectral characteristics of waves, it is possible to determine the velocity of the near-surface flow by measuring the Doppler shift of acoustic and radar signals. High-resolution data obtained from stereo photography of the sea surface allow clarifying the relationship between the velocities of acoustic and radar scatterers and hydrometeorological parameters.
    11857-31
    Author(s): Stanislav Ermakov, Institute of Applied Physics (Russian Federation), Volga State Univ. of Water Transport (Russian Federation); Gregory Khazanov, Vladimir Dobrokhotov, Daria Vostryakova, Institute of Applied Physics (Russian Federation); Tatiana N. Lazareva, Institute of Applied Physics of the RAS (Russian Federation)
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    It is well known that marginal ice zones are characterized by different forms of initial stages of ice (grease ice, fragmented ice, etc.), which act as surface wave absorbers thus affecting microwave radar backscattering. As a result, mapping of boundaries between solid ice and open water areas using radar may become rather complicated. Another aspect of the “wind wave-ice floe interaction problem” is that wave damping due to ice floes results in enhanced wave induced surface stresses. The latter are responsible for localization of floes in long bands clearly seen on the sea surface in polar areas. Finally, the areas of strong wave damping can be erroneously interpreted as surface pollutions in radar imagery. Studies of wave damping due to ice floes are still insufficient, and relations between the floe geometry and wave damping are poorly established. The motivation of this study is to improve our understanding of the process of wave damping due to ice floes for elaboration of physical models of wave damping. New wave tank experiments were carried out to investigate the damping of regular (mechanically generated) and irregular wind waves due to drifting floe imitators (washing sponges) as well as for the case of stationary, non moving floes. Dependencies of the damping coefficient on wave frequencies for regular and wind waves for different floe sizes and different areas occupied by the floes were obtained. One of the most interesting results was that the damping coefficient indicated a local maximum when the floe size was about half the wave length. A physical interpretation of the results was given, based on the analysis of floe movement under the action of the orbital wave motion taking into account the floe added mass. The research was supported by the Russian Foundation of Basic Research (Project 20-05-00561)
    11857-32
    Author(s): Gregory Khazanov, Stanislav Ermakov, Institute of Applied Physics (Russian Federation)
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    It is known that organic and mineral films appear in microwave radar or optical aircraft/satellite images as the areas of reduced intensity due to suppression of short wind gravity-capillary waves (GCW) - slicks. The suppression of GCW with wavelengths ranged from some millimeters to decimeters can be characterized in terms of film elasticity. Hence, marine slicks in radar/optical images can be quantitatively described if the film elasticity is known. The elastic properties of monomolecular films have been thoroughly studied, while the problem for thick films, particularly for crude oil films remains poorly investigated. The latter are characterized by strong inhomogeneity in thickness. This paper is focused on laboratory analysis of GCW attenuation due to non uniform films. The damping of GCW was measured in laboratory using a method of parametric excitation of standing GCW in a vertically oscillating cuvette mounted on a vibration table. Laboratory measurements were performed for highly inhomogeneous films of pure dodecyl alcohol. When the surfactant concentration exceeded the values corresponding to the saturated monomolecular layer, the surfactant excess was concentrated in non-spreading drops (lenses) of macroscopic thickness(1-3 mm). The GCW attenuation coefficient was studied for GCW frequencies of 10 to 20 Hz and for different sizes and number of lenses. It was found that the attenuation coefficient increased with the relative area of the lenses. A physical explanation of this effect was proposed based on the “lens-wall” model, when assuming that the lenses reduced the area of the monomolecular film and, accordingly, increased the wave attenuation. Theoretical analysis of wave damping based on a “lens-wall” hypothesis has demonstrated good consistence with the experiment. The effective elasticity of a two phase film -a monomolecular layer with a lens phase- is introduced, which replaces the two-phase film with an effective monomolecular film.
    Conference Chair
    Florida Institute of Technology (United States)
    Conference Chair
    Royal Military Academy (Belgium)
    Program Committee
    The City College of New York (United States)
    Program Committee
    ONERA (France)
    Program Committee
    The City College of New York (United States)
    Program Committee
    NASA Kennedy Space Ctr. (United States)
    Program Committee
    Frederic Lamy
    ONERA (France)
    Program Committee
    Univ. dos Açores (Portugal)
    Program Committee
    Technical Univ. of Crete (Greece)
    Program Committee
    Petri Pellikka
    Univ. of Helsinki (Finland)
    Program Committee
    ONERA (France)