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RSS FeedsRemote Sensing, Vol. 14, Pages 3921: Marine Gravimetry and Its Improvements to Seafloor Topography Estimation in the Southwestern Coastal Area of the Baltic Sea (Remote Sensing)

 
 

12 august 2022 16:04:26

 
Remote Sensing, Vol. 14, Pages 3921: Marine Gravimetry and Its Improvements to Seafloor Topography Estimation in the Southwestern Coastal Area of the Baltic Sea (Remote Sensing)
 


Marine gravimetry provides high-quality gravity measurements, particularly in coastal areas. After the update of new sensors in GFZ’s air-marine gravimeter Chekan-AM, gravimetry measurements showed a significant improvement from the first new campaign DENEB2017 with an accuracy of 0.3/2=0.21 mGal @ 1 km along the tracks, which is at the highest accuracy level of marine gravimetry. Then, these measurements were used to assess gravity data derived from satellite altimetry (about 3 mGal) and a new finding is that a bias of −1.5 mGal exists in the study area. Additionally, ship soundings were used to assess existing seafloor topography models. We found that the accuracy of SRTM model and SIO model is at a level of 2 m, while the accuracy of the regional model EMODnet reaches the lever of sub-meters. Furthermore, a bias of 0.7 m exists and jumps above 5 m in the SRTM model near the coast of Sweden. Finally, new combined gravity anomalies with sounding data are used to reveal the fine structure of ocean topography. Our estimated seafloor topography model is more accurate than existing digital elevation data sets such as EMODnet, SRTM and SIO models and, furthermore, shows some more detailed structure of seafloor topography. The marine gravimetry and sounding measurements as well as the estimated seafloor topography are crucial for future geoid determination, 3D-navigation and resource exploration in the Baltic Sea.


 
110 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 14, Pages 3920: Identifiability Analysis for Configuration Calibration in Distributed Sensor Networks (Remote Sensing)
Remote Sensing, Vol. 14, Pages 3922: Multi-Path Interactive Network for Aircraft Identification with Optical and SAR Images (Remote Sensing)
 
 
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