Surface geological mapping is generally carried out conventionally, which takes a long time and costs much money because it involves many people. Cutting the time and number of people involved is the best solution, such as automating geological mapping using the Structure from Motion (SfM) method and the results obtained in digital or virtual form, which can be used repeatedly by other researchers openly (open-access). This research aims to develop and simultaneously implement an automated geological mapping technique using the SfM method on Gading Formation sandstone, Tangkit Serdang Village, Tanggamus. Images acquired from multiple drone camera positions are simultaneously and automatically computed on the fly using highly redundant bundle adjustments based on feature matching in overlapping offset images. High-resolution GPS RTK data and detailed geological measurements were then corrected in the obtained model. Digital interpretation of outcrop stratigraphy and lithologic units relies on visible coloration and is calibrated by field observations of facies in rock samples (VoF). Sandstone (VoF1), mudstone (VoF5), and coal (VoF7) are identified primarily based on the dominant color in the VO (VoF1 = light brown to white; VoF5 = dark gray to brown; VoF7 = black). The silty sandstone (VoF5) and sandy mudstone (VoF3) facies typically vary in color between the boundaries of the two members. Photogrammetry combined with drone-based remote sensing (SfM-VMS) and the application of this technology in geology to study and model large-scale geological outcrops appears to be a state-of-the-art solution in terms of cost, safety, accuracy, and efficiency.