Abstract
With the development of remote sensing techniques, the fusion of multimodal data, particularly hyperspectralLight Detection And Ranging (HS-LiDAR) and hyperspectral-SAR, has become an important research field in
numerous application areas. Multispectral, HS, LiDAR, and Synthetic Aperture Radar (SAR) images contain
detailed information about the monitored surface that are complementary to each other. Thus, data fusion
methods have become a promising solution to obtain high spatial resolution remote-sensing images. The main
point of this review paper is to classify hyperspectral-LiDAR and hyperspectral-SAR data fusion with approaches.
Moreover, recent achievements in the fusion of hyperspectral-LiDAR and hyperspectral-SAR data are highlighted
in terms of faced challenges and applications. Most frequently used data fusion datasets that include IEEE GRSS
Data Fusion Contests are also described.