The role of active remote sensors for geological studies: a preliminary review

Active remote sensing technologies such as Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) have been established as tools for geological investigations since the 1980s. These sensors, deployable on Unmanned Aerial Vehicles (UAVs), aircrafts and satellites, emit their own electromagnetic signals to map Earth's surface features. LiDAR provides high-resolution topographic data, enabling detailed analysis of geomorphology, tectonics, and landslide identification. However, its spatial resolution and application scope depend on the platform: UAV-mounted sensors yield denser point clouds (hundreds/thousands of points per m²) suited for local-scale studies, whereas airborne or satellite systems offer broader coverage at reduced point densities, limiting fine-scale geological interpretation. SAR sensors capture amplitude and phase data from the backscattered signal, enabling advanced geological and engineering applications such as interferometric deformation monitoring and subsurface imaging. The utility of SAR further depends on wavelength selection (e.g., X-, L-, or C-band), where longer wavelengths (e.g., L-band) exhibit greater penetration through vegetation and surface layers, enabling soil moisture mapping or sediment thickness estimation, while shorter wavelengths (e.g., Xband) enhance surface displacement measurements. This study synthesizes recent advancements in the application of SAR and LiDAR technologies for geological analyses, performing a systematic review of peer-reviewed literature indexed in the Scopus database, focusing on the latest publications from 2015 to 2025. The key terms used for the techniques employed were <i>SAR</i> and <i>LiDAR</i>, which were combined with geological domain terms – <i>mineral, geology, tectonics, lithology, structural geology,</i> and <i>geological exploration</i>. The bibliometric analysis was structured in three stages: search, refinement, and screening. The study relied solely on abstract analysis to prioritize scalability, with no full-text review performed. The results provide insights into the evolution of the application of active remote sensors in geological studies.