Height estimation from single images has become a highly requested topic in the remote sensing community. While most methods use optical data, a first attempt with SAR intensity imagery was recently performed and achieved promising results. The actual practical value of any Deep Learning-based method such as this, however, then depends on how well it can be applied to sceneries unknown to the model, maybe even recorded under different acquisition conditions. This paper focuses on that very aspect of this methodology. For this purpose, the differences of distinct data types and test scenes are highlighted and the obtained results by the pre-trained models are evaluated and interpreted.    «

Height estimation from single images has become a highly requested topic in the remote sensing community. While most methods use optical data, a first attempt with SAR intensity imagery was recently performed and achieved promising results. The actual practical value of any Deep Learning-based method such as this, however, then depends on how well it can be applied to sceneries unknown to the model, maybe even recorded under different acquisition conditions. This paper focuses on that very aspec...    »