With the development of remote sensing techniques, the fusion of multimodal data, particularly hyperspectral-Light 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.

随着遥感技术的发展，多模态数据的融合，特别是高光谱光探测与测距（HS-LiDAR）与高光谱SAR的融合，已成为众多应用领域的重要研究领域。多光谱、HS、LiDAR 和合成孔径雷达 (SAR) 图像包含有关彼此互补的监测表面的详细信息。因此，数据融合方法已成为获得高空间分辨率遥感图像的有前途的解决方案。这篇综述论文的重点是用方法对高光谱激光雷达和高光谱 SAR 数据融合进行分类。此外，在面临的挑战和应用方面，突出了高光谱激光雷达和高光谱 SAR 数据融合的最新成果。