Multi-parameter dataset of self-potential, electrical resistivity tomography, soil properties, and UAV LiDAR topography from the Fengjiaping loess-mudstone landslide, China.

The Fengjiaping landslide is located in the transition zone between the western Qinling Mountains and the southwestern Loess Plateau in China. Multi-parameter datasets were acquired from the Fengjiaping landslide, including hydrogeophysical, soil parameters, and topographic measurements. Self-potential (SP) data were acquired using 86 Pb-PbCl₂ non-polarizable electrodes at a sampling rate of 10 Hz over 20 min intervals. Electrical resistivity tomography (ERT) data were acquired along four survey lines using an ERT acquisition system. Soil parameters data were acquired using a portable soil sensor and include temperature, volumetric water content, and electrical conductivity measurements. Topographic data were acquired using a drone-based LiDAR system, and sensor positions were determined using real-time kinematic (RTK) positioning. The dataset is organized into raw and processed files together with information on acquisition parameters, measurement units, and data formats. The dataset can be reused for joint interpretation of SP and ERT data, hydrogeophysical analysis of landslide processes, development of machine-learning approaches for landslide investigation, and validation of coupled hydrological-geophysical inversion methods.