Airborne Snow Radar Data Simulation With Deep Learning and Physics-Driven Methods

Monitoring properties of ice sheets in polar regions is one of the main challenges in glaciology. There is a large amount of heterogeneous radar data from the polar regions that have been gathered through expensive missions. However, retrieving meaningful information from this large volume of data i...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.12035-12047
Hauptverfasser:	Yari, Masoud, Ibikunle, Oluwanisola, Varshney, Debvrat, Chowdhury, Tashnim, Sarkar, Argho, Paden, John, Li, Jilu, Rahnemoonfar, Maryam
Format:	Artikel
Sprache:	eng
Schlagworte:	Airborne radar Airborne remote sensing Algorithms Data models Data simulation Datasets Deep learning Generative adversarial networks Generative adversarial networks (GANs) Glaciation Glaciology Ice sheets Information retrieval Learning algorithms Machine learning Methods Physics Polar environments Radar Radar data Radar imaging Radar remote sensing Radar scattering Radar tracking Regions remote sensing Similarity Simulation Simulators Snow snow radar Tracking Training
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