On Removal of Sea State Contribution to Sentinel‐1 Doppler Shift for Retrieving Reliable Ocean Surface Current

First multi-year assessment of Sentinel-1 radial velocity products using HF radar currents in a coastal environment

The SAR Doppler frequencies are directly related to the motion of the scatterers in the illuminated area and have already been used in marine applications to monitor moving water surfaces. Here we investigate the possibility of retrieving surface water velocity from SAR Doppler analysis in medium-size lakes. ENVISAT images of the test site (Lake Garda) are processed and the Doppler Centroid Anomaly technique is adopted. The resulting surface velocity maps are compared with the outputs of a hydrodynamic model specifically validated for the case study. Thermal images from MODIS Terra are used in support of the modeling results. The surface velocity retrieved from SAR is found to overestimate the numerical results and the existence of a bias is investigated. In marine applications, such bias is traditionally removed through Geophysical Model Functions (GMFs) by ascribing it to a fully developed wind waves spectrum. We found that such an assumption is not supported in our case study, due to the small-scale variations of topography and wind. The role of wind intensity and duration on the results from SAR is evaluated, and the inclusion of lake bathymetry and the SAR backscatter gradient is recommended for the future development of GMFs suitable for lake environments.

Monitoring Lakes Surface Water Velocity with SAR: A Feasibility Study on Lake Garda, Italy

The accurate monitoring of water quality indicators, bathymetry and distribution of benthic habitats in vulnerable ecosystems is key to assessing the effects of climate change, the quality of natural areas and to guide appropriate biodiversity, tourism or fisheries policies. Coastal and inland water ecosystems are very complex but crucial due to their richness and primary production. In this context, remote sensing can be a reliable way to monitor these areas, mainly thanks to satellite sensors’ improved spatial and spectral capabilities and airborne or drone instruments. In general, mapping bodies of water is challenging due to low signal-to-noise (SNR) at sensor level, due to the very low reflectance of water surfaces as well as atmospheric effects. Therefore, the main objective of this work is to provide a robust processing framework to estimate water quality parameters in inland shallow waters using multiplatform data. More specifically, we measured chlorophyll concentrations (Chl-a) from multispectral and hyperspectral sensors on board satellites, aircrafts and drones. The Natural Reserve of Maspalomas, Canary Island (Spain), was chosen for the study because of its complexity as well as being an inner lagoon with considerable organic and inorganic matter and chlorophyll concentration. This area can also be considered a well-known coastal-dune ecosystem attracting a large amount of tourists. The water quality parameter estimated by the remote sensing platforms has been validated using co-temporal in situ measurements collected during field campaigns, and quite satisfactory results have been achieved for this complex ecosystem. In particular, for the drone hyperspectral instrument, the root mean square error, computed to quantify the differences between the estimated and in situ chlorophyll-a concentrations, was 3.45 with a bias of 2.96.

Multiplatform earth observation systems for monitoring water quality in vulnerable inland ecosystems: Maspalomas water lagoon

Evaluation of Radial Ocean Surface Currents Derived From Sentinel-1 IW Doppler Shift Using Coastal Radar and Lagrangian Surface Drifter Observations

Recent developments on calibration and partitioning of the signal between the wave and current contributions significantly improve the accuracy of geophysical retrievals from Sentinel-1 Synthetic Aperture Radar-based Doppler shift measurements in the open ocean. In this study, we revise the Sentinel-1B Interferometric Wide products acquired from December 2017 to January 2018 along the coastal zone of northern Norway. We find that the satellite attitude is responsible for 30% of the variation in the Doppler shift observations, while the antenna pattern can describe an additional 15%. The residual variation after the re-calibration is about 3.8 Hz, corresponding to 0.21 - 0.15 m/s radial velocity depending on the incidence angle. Using re-calibrated Sentinel-1 observations, collocated with near-surface wind from MEPS and sea state from MyWaveWAM, we develop an empirical function (CDOP3SiX) for estimating the sea-state-induced Doppler shift. CDOP3SiX improves the accuracy of sea state contribution estimates under mixed wind fetch conditions and demonstrates that the Norwegian Coastal Current can be detected in the Sentinel-1 derived ocean surface current radial velocity maps. Moreover, two anticyclonic mesoscale eddies with radial velocities of about 0.5 m/s are detected. The surface current patterns are consistent with the collocated sea surface temperature observations. The Doppler shift observations from Sentinel-1 can therefore be used to study ocean surface currents in the coastal zone with a 1.5 km spatial resolution. 

Towards Retrieving Reliable Ocean Surface Currents in the Coastal Zone from the Sentinel‐1 Doppler Shift Observations

The Doppler shift obtained from synthetic aperture radar (SAR) measurements comprises the combined contribution to the radial motion of the ocean surface induced by the sea state (wind waves and swell) and underlying surface currents. Hence, to obtain reliable estimates of the ocean surface current (OCS), the sea-state-induced Doppler shifts must be accurately estimated and eliminated. In this study, we use a semiempirical dual co-polarization Doppler velocity (DPDop) model, presented in the companion paper, to calculate sea-state-induced Doppler shifts using buoy-measured wind speed, wind direction, and ocean wave spectra. The DPDop model-simulated Doppler shifts are compared with the collocated Sentinel-1B SAR Wave (WV) mode observations at the 24° and 37° incidence angles, showing a bias of −0.24 Hz and a root-mean-square error (RMSE) of 5.55 Hz. This evaluation is also implemented on a simplified DPDop model at the same incidence angles. The model inputs include wind fields from the European Center for Medium-Range Weather Forecasts (ECMWF) and wave characteristic parameters (e.g., significant wave height (SWH), mean wave direction, and mean wavenumber) from WAVEWATCH III (WW3). The estimated Doppler shifts are validated using the ascending and descending observations of Sentinel-1B WV over the global ocean. Furthermore, the comparisons show that the bias and RMSE are −0.71 and 9.25 Hz, respectively. Based on accurate wave bias correction, we obtain the radial current speeds of the ocean surface from the Doppler shift measurements. The estimated current speeds are compared with the collocated high-frequency (HF) radar measurements, with a bias of −0.04 m/s and an RMSE of 0.15 m/s. These results suggest that the original and simplified DPDop models can be used to estimate sea-state-induced Doppler shifts and, thus, derive accurate surface current retrievals.

https://ieeexplore.ieee.org/ielx7/36/4358825/10049461.pdf

On the Use of Dual Co-Polarized Radar Data to Derive a Sea Surface Doppler Model—Part 2: Simulation and Validation

Озеро Мичиган относится к олиготрофному типу водоемов. Сильнее всего это проявляется в прибрежной зоне, где гидрологический режим вод формируется под действием различных природных и антропогенных факторов, протекающих на водосборной территории. Влияние дна достаточно сильно искажает регистрируемый спутником сигнал, препятствуя выполнению дистанционного зондирования параметров качества воды в этой части озера. Для извлечения из спутниковых снимков параметров качества воды в оптически мелких районах озера Мичиган был разработан новый биооптический алгоритм. Он основан на модели переноса излучения, гидрооптической модели озера Мичиган и многомерной оптимизации и позволяет получать оценку концентрации всех основных оптически активных веществ (ОАВ) в областях с различным типом дна: песок, ил, макрофиты ( Chara или Cladophora ) и известняковая галька. Тестирование алгоритма показало, что при очень низких концентрациях ОАВ (менее 0,01 в соответствующих единицах измерения) оптическое влияние дна становится незначительным при глубине около 20 метров. В воде с более высокими концентрациями взвешенного вещества (ВВ) и хлорофилла влияние дна становится неразличимым при глубине ~10 м. Тестирование чувствительности алгоритма к шуму показало, что чем меньше толщина исследуемого водного столба и чем выше альбедо дна, тем выше погрешность восстановления концентраций ОАВ. Например, в случае песчаного дна и глубины 5 м погрешность в 10 % при оценке альбедо дна приводит к ошибкам в 18, 28 и 10 % при восстановлении хлорофилла, ВВ и окрашенного растворенного органического вещества соответственно.

/pdf/bio-optical-retrieval-algorithm-for-the-optically-shallow-4uup0ug1or.pdf

Artem Moiseev

Papers

Evaluation of Radial Ocean Surface Currents Derived From Sentinel-1 IW Doppler Shift Using Coastal Radar and Lagrangian Surface Drifter Observations

On Removal of Sea State Contribution to Sentinel‐1 Doppler Shift for Retrieving Reliable Ocean Surface Current

Towards Retrieving Reliable Ocean Surface Currents in the Coastal Zone from the Sentinel‐1 Doppler Shift Observations

On the Use of Dual Co-Polarized Radar Data to Derive a Sea Surface Doppler Model—Part 2: Simulation and Validation

Bio-optical retrieval algorithm for the optically shallow waters of Lake Michigan. I. model description and sensitivity/robustness assessment