CATSNet: a context-aware network for Height Estimation in a Forested Area based on Pol-TomoSAR data

arXiv:2403.20273v1 Announce Type: new
Abstract: Tropical forests are a key component of the global carbon cycle. With plans for upcoming space-borne missions like BIOMASS to monitor forestry, several airborne missions, including TropiSAR and AfriSAR campaigns, have been successfully launched and experimented. Typical Synthetic Aperture Radar Tomography (TomoSAR) methods involve complex models with low accuracy and high computation costs. In recent years, deep learning methods have also gained attention in the TomoSAR framework, showing interesting performance. Recently, a solution based on …

abstract arxiv campaigns carbon context cs.cv data forests global key network radar space synthetic type