Unmanned Aerial Vehicles (UAVs) have become essential tools in landslide studies, particularly for on-site investigations. This review discusses the applications of UAVs in landslide research, focusing on static geological characteristics, monitoring temporal and spatial dynamics, and responses post-events. Various types of UAVs and sensors, including RGB cameras, multi-spectral cameras, thermal IR cameras, SAR, and LiDAR, are analyzed for their roles and data processing methods in landslide applications. The review emphasizes UAVs' roles in landslide geology surveys, highlighting landslide mapping, modeling, and characterization. For change monitoring, UAV-based monitoring provides insights into dynamic landslide processes. The paper also underscores UAVs' crucial role in emergency response scenarios, detailing strategies and automated detection using machine learning algorithms. Challenges and opportunities in UAV technology are discussed, emphasizing the need for ongoing advancements to address regulatory hurdles, hover time limitations, 3D reconstruction accuracy, and potential integration with technologies like UAV swarms. UAVs are used for landslide monitoring, including surface change detection, crack and fissure monitoring, and emergency response. UAVs provide high-resolution imagery, access to challenging terrains, and frequent data collection, making them valuable for time-series landslide monitoring. UAVs are also used for SAR, which is particularly valuable in landslide monitoring, allowing analysis of surface changes through radar images. UAVs are used for crack and fissure change monitoring, enabling the detection of cracks in landslide-prone areas. UAVs are also used in emergency response, providing rapid assessment of landslide activity and aiding in decision-making. UAVs have proven effective in landslide studies for monitoring displacements and characterizing structures, addressing both dynamic and static aspects of landslides. UAVs offer a rapid response option in the aftermath of hazard events, particularly when ground investigations are time-consuming. They are also useful in high-resolution 3D model reconstruction based on aerial images. UAVs provide a cost-effective method for studying landslides, enabling real-time monitoring to assess damage extent, evaluate risks, and inform timely decision-making in emergency situations. The integration of sensors, including optical, LiDAR, and SAR, into UAV platforms enhances the versatility and effectiveness of landslide studies. These sensors provide valuable data for both qualitative and quantitative analyses, making substantial contributions to the field of landslide studies. The functions and limitations of each sensor are presented in Figure 2. UAV-based remote sensing in landslide applications typically emphasizes both static characteristic identification and multi-temporal monitoring. Basic static characteristics are derived from mono-temporal aerial images. Subsequently, a static 3D model can be reconstructed based on a series of overlapping aerial images or LiDAR data, providing detailed insights into the topography in three dimensions. Additionally, the differences observed in multi-temporal models serve as a valuable means to monitor the dynamic changes within landslide-prone areas. UAVs are used for landslide monitoring, including surface change detection, crack and fissure monitoring, and emergency response. UAVUnmanned Aerial Vehicles (UAVs) have become essential tools in landslide studies, particularly for on-site investigations. This review discusses the applications of UAVs in landslide research, focusing on static geological characteristics, monitoring temporal and spatial dynamics, and responses post-events. Various types of UAVs and sensors, including RGB cameras, multi-spectral cameras, thermal IR cameras, SAR, and LiDAR, are analyzed for their roles and data processing methods in landslide applications. The review emphasizes UAVs' roles in landslide geology surveys, highlighting landslide mapping, modeling, and characterization. For change monitoring, UAV-based monitoring provides insights into dynamic landslide processes. The paper also underscores UAVs' crucial role in emergency response scenarios, detailing strategies and automated detection using machine learning algorithms. Challenges and opportunities in UAV technology are discussed, emphasizing the need for ongoing advancements to address regulatory hurdles, hover time limitations, 3D reconstruction accuracy, and potential integration with technologies like UAV swarms. UAVs are used for landslide monitoring, including surface change detection, crack and fissure monitoring, and emergency response. UAVs provide high-resolution imagery, access to challenging terrains, and frequent data collection, making them valuable for time-series landslide monitoring. UAVs are also used for SAR, which is particularly valuable in landslide monitoring, allowing analysis of surface changes through radar images. UAVs are used for crack and fissure change monitoring, enabling the detection of cracks in landslide-prone areas. UAVs are also used in emergency response, providing rapid assessment of landslide activity and aiding in decision-making. UAVs have proven effective in landslide studies for monitoring displacements and characterizing structures, addressing both dynamic and static aspects of landslides. UAVs offer a rapid response option in the aftermath of hazard events, particularly when ground investigations are time-consuming. They are also useful in high-resolution 3D model reconstruction based on aerial images. UAVs provide a cost-effective method for studying landslides, enabling real-time monitoring to assess damage extent, evaluate risks, and inform timely decision-making in emergency situations. The integration of sensors, including optical, LiDAR, and SAR, into UAV platforms enhances the versatility and effectiveness of landslide studies. These sensors provide valuable data for both qualitative and quantitative analyses, making substantial contributions to the field of landslide studies. The functions and limitations of each sensor are presented in Figure 2. UAV-based remote sensing in landslide applications typically emphasizes both static characteristic identification and multi-temporal monitoring. Basic static characteristics are derived from mono-temporal aerial images. Subsequently, a static 3D model can be reconstructed based on a series of overlapping aerial images or LiDAR data, providing detailed insights into the topography in three dimensions. Additionally, the differences observed in multi-temporal models serve as a valuable means to monitor the dynamic changes within landslide-prone areas. UAVs are used for landslide monitoring, including surface change detection, crack and fissure monitoring, and emergency response. UAV