Abstract's details
FFSAR data radargram exploitation for improving the altimeter retracking performance in coastal zone.
CoAuthors
Event: 2023 Ocean Surface Topography Science Team Meeting
Session: Coastal Altimetry
Presentation type: Type Poster
Contribution: PDF file
Abstract:
The coastal zone is of particular interest for the altimetry. However, no coastal altimeter processing is, today, able to provide highly accurate and precise measurements without removing many observations (the so-called outliers) that we would be interested in. Despite the efforts being made in the development of new solutions, those methods can still be clearly improved. An important step forward towards this objective would demand a detailed knowledge of the observed surface and the corresponding radar intensity variations to be accounted for in the waveform retracking.
With the launch of the Sentinel-6 mission, and the development of the high-resolution Fully Focused SAR (FFSAR), we are now able to capture sharp details in complex areas, such as coastal zones, which cannot be seen in conventional and unfocussed-SAR altimetry. By exploiting consecutive FF-SAR waveforms gathered in a radargram, valuable information on the coastal environment can therefore be extracted. It is possible for example to distinguish surfaces from one to another by analyzing the difference of their backscattering signatures in the radargram. This feature can help separating oceanic water from high specularity surroundings surfaces (associated to high backscattering coefficients σ_0) that are often encountered in coastal zones. We can cite shallow water, sandbanks and inland water for example. Those surfaces are responsible of major distortion on the oceanic waveform shape making them hard to retrack (resulting in significant errors in the altimeter measurements).
In this study, we developed a method to extract features from S6 FF-SAR data radargrams using a point clouds classifier (based on a statistical distribution analysis of the σ_0 radar intensity values), in order to accurately locate the ocean targets within complex coastal environments. More specifically, this pre-processing algorithm allows the determination of the last useful waveform gate to retrack the useful part of the FF-SAR altimeter waveform. This method is compared with a shapefile-based method that uses a static coastline that does not include natural phenomena such as tides or storms. Advantages and drawbacks of both methods are discussed.
With the launch of the Sentinel-6 mission, and the development of the high-resolution Fully Focused SAR (FFSAR), we are now able to capture sharp details in complex areas, such as coastal zones, which cannot be seen in conventional and unfocussed-SAR altimetry. By exploiting consecutive FF-SAR waveforms gathered in a radargram, valuable information on the coastal environment can therefore be extracted. It is possible for example to distinguish surfaces from one to another by analyzing the difference of their backscattering signatures in the radargram. This feature can help separating oceanic water from high specularity surroundings surfaces (associated to high backscattering coefficients σ_0) that are often encountered in coastal zones. We can cite shallow water, sandbanks and inland water for example. Those surfaces are responsible of major distortion on the oceanic waveform shape making them hard to retrack (resulting in significant errors in the altimeter measurements).
In this study, we developed a method to extract features from S6 FF-SAR data radargrams using a point clouds classifier (based on a statistical distribution analysis of the σ_0 radar intensity values), in order to accurately locate the ocean targets within complex coastal environments. More specifically, this pre-processing algorithm allows the determination of the last useful waveform gate to retrack the useful part of the FF-SAR altimeter waveform. This method is compared with a shapefile-based method that uses a static coastline that does not include natural phenomena such as tides or storms. Advantages and drawbacks of both methods are discussed.