Conference Agenda

The Dragon 4 project 32292 dealt with using new Earth Observation data for developing and improving new products obtained from radar altimetry and for operational monitoring of sea ice and surface salinity (SSS). To improve sea ice thickness retrieval, a new method was developed to match the Cryosat-2 radar waveform. Also, an automated sea ice drift detection scheme was developed and tested on Sentinel-1 data, and the sea ice drifty capability of Gaofen-4 geostationary optical data was evaluated. A second topic included implementation and validation of a prototype of a Fully-Focussed SAR processor adapted for Sentinel-3 and Sentinel-6 altimeters and evaluation of its performance with Sentinel-3 data over the Yellow Sea; the assessment of sea surface height (SSH), significant wave height (SWH), and wind speed measurements using different altimeters and CFOSAT SWIM; and the fusion of SSH measurements in mapping sea level anomaly (SLA) data to detect mesoscale eddies. Thirdly, the investigations on the retrieval of SSS include simulations to analyse the performances of the Chinese payload configurations of the Interferometric Microwave Radiometer and the Microwave Imager Combined Active and Passive, SSS retrieval under rain conditions, and the combination of active and passive microwave to study extreme winds.

It is presented in this paper the final results of ESA-MOST China Dragon Cooperation Program “Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-Sensors (ID. 32249)” including: (1) GF-3 SAR ocean wind retrieval: the first view and preliminary assessment; (2) Preliminary analysis of Chinese GF-3 SAR quad-polarization measurements to extract winds in each polarization; (3) Assessments of ocean wind retrieval schemes and geophysical model functions used for Chinese GF-3 SAR data at each polarization; (4) Combined co- and cross-polarized SAR measurements under extreme wind conditions; (5) Joint retrieval of directional ocean wave spectra from SAR and RAR; (6) Wind and waves remote sensing by using interferometric imaging radar altimeter onboard the Chinese Tiangong-2 Space Laboratory (TG-2); (7) Top cloud motion field of Typhoon Megi–2016 revealed by GF-4 Images; (8) Using satellite altimetry to calibrate the simulation of typhoon Seth storm surge off southeast china.

In this paper, we presented our collaboration on studies retrieval of ocean wave parameters, i.e., integral wave parameters by spaceborne SAR data, in the global and regional oceans.

By using the ENVISAT/ASAR wave mode data acquired in its full life cycle (2002 – 2012) over the global ocean, we developed a dataset consisting of integral ocean wave parameters of significant wave height (SWH) and mean wave period (MWP). Both parameters are calibrated and validated against buoy data. A cross-validation between the ASAR SWH and radar altimeter (RA) data is also performed to ensure that the SAR-derived wave height data are of the same quality as the RA data. These data are stored in the standard NetCDF format, which are produced for each ASAR wave mode Level1B data provided by the European Space Agency. This is for the first time that a full sea state product is derived from spaceborne SAR data over the global ocean for a decadal temporal scale. Using similar algorithm, i.e., parametric model, which relates SAR observed normalized radar cross section (NRCS) and other radar parameters with ocean wave parameters, we further developed Sentinel-1 SAR wave mode data product for global oceans.

In regional scale, SAR data acquired in stripmap or ScanSAR modes are used to derive ocean wave parameters. These data have not only high spatial resolution but also relatively large spatial coverages, and therefore are useful for mapping of ocean wave in regional scales. Compared with wave mode data with fixed radar incidence angles, they vary significantly from near to far ranges, particularly for ScanSAR and wide ScanSAR modes. Therefore, by adopting previously developed parametric model, effect of incidence angles is included. The SAR-derived SWH is systematically validated by comparing RA data and buoy measurements and shows a good accuracy.

High resolution, in the temporal, spatial or spectral dimensions is one of the major trends of satellite remote sensing, with which one may derive more detailed information from the earth observation data. The paper summarizes the main results of the Dragon-4 coastal zone project (2016-2020), the objective of which is to explore and demonstrate the technical possibility and capability of the high resolution remote sensing in the monitoring of suspended sediment and coastal wetlands, whose variability is of vital importance to human being. Specifically, in the monitoring of suspended sediment, new retrieval algorithms were developed and applied to the geostationary and the polar-orbiting optical satellite images for spatio-temporal variability analysis. For the monitoring of coastal wetlands, new algorithms were developed for wetland types classification in fine scale to identify invasive species from hyperspectral images, aboveground carbon storage and water clarity estimation from high spatial resolution satellite images. With these algorithms, the distribution of the invasive species S. alterniflora in the wetlands were mapped, and the carbon storage per unit area of the estuarine wetlands was estimated.

In this paper, the main outcomes relevant to the European Space Agency (ESA) – Ministry of Science and Technology Dragon 4 cooperation project ID 32235 “Microwave satellite measurements for coastal area and extreme weather monitoring” are reported. The project is to strengthen the Sino-European research cooperation in the framework of the exploitation of ESA, Chinese and third-party mission Earth Observation microwave satellite data to perform an effective monitoring of coastal areas, even under extreme weather conditions. An integrated approach, based on the use of complementary microwave sensors (e.g.; multi-frequency and multi-polarization Synthetic Aperture Radar, scatterometer and radiometer), together with ancillary information coming from independent sources, i. e., optical imagery, numerical simulations and ground measurements, is designed.

The main outcomes are both theoretical (i.e.; new models and algorithms have been developed to deal with marine target detection, sea pollution, sea surface wind estimation, coastline extraction) and applicative (i.e.; user-friendly maps have been provided that, based on an intelligent processing of remotely sensed measurements, can coastal area management).

In studies of upwelling, usually data from infrared and optical sensors are used which provide information on the sea surface temperature (SST) and the chlorophyll-a (Chl-a) concentration. However, when including synthetic aperture (SAR) additional information on upwelling can be obtained. Areas of cold upwelled water becomes visible on SAR images as areas of reduced image intensity because cold water changes the stability of the air-sea interface which causes a reduction of the normalized cross section (NRCS). Since SAR is ultra-sensitive to variations in the small-scale sea surface roughness, and since variable surface currents associated upwelling modulate, boundaries of upwelling become visible on SAR images as bright lines. Due to its high resolution, SAR also can detect internal waves and sub-mesoscale eddies, which are sometimes present in upwelling areas. In this paper, we analyze SAR images acquired by the European satellites Sentinel-1A and 1B and the Chinese satellite Guofen-3 (GF-3) satellite that show radar signatures of upwelling caused by coastal winds, cyclonic eddies, and cyclonic meanders. The investigation is focused on the upwelling areas south of Sicily in the Mediterranean Sea, south of South Africa, the Strait of Taiwan, and north of Taiwan.