Integrating field-based and digital datasets to improve geometric accuracy of geologic cross sections constructed from outcrop

Outcrop exposures of sedimentary rocks preserve vital records of depositional processes and offer key insights into Earth's depositional history. Traditional field-based techniques, such as measuring bed orientations, sketches, and field photography, have long been used to document stratigraphic patterns, while modern approaches now leverage high-resolution panoramas and drone-based photogrammetry to quantify and geolocate measurements. Although Digital Outcrop Models (DOMs) derived from UAVs (drones) markedly improve our ability to capture and interpret spatial details, these modern approaches, when used to generate 2-D stratigraphic correlation panels, are still challenged by distortions caused by outcrop perspective and structural deformation. To accurately constrain stratigraphic reconstructions derived from DOMs, calibrated field data is necessary to corroborate these observations with thicknesses, length scales, and lithologies. Here, we present a method to correct stratigraphic interpretations from DOMs for structural overprint and outcrop perspective using field-based paleocurrent and strike-and-dip measurements to produce geometrically accurate surface length, height, and dip in stratigraphic correlation panels. We demonstrate this method on Cerro Cazador, a 15 km-long outcrop transect in Patagonia, Chile, recognized as containing continental shelf and shelf-margin sedimentary deposits. By systematically comparing three data projection strategies: no correction, a single correction, and a novel multi-correction workflow that applies localized adjustments to distinct structural regions, we show that the multi-correction method yields depositional geometries consistent with expected stratigraphic patterns (e.g., flat topset and bottomset deposits, sloping foresets, shelf-edge trajectories). These findings underscore the need for incorporating field-based calibrations into drone-derived models to accurately capture depositional patterns in geologically complex settings and highlight important implications for quantitative sedimentary analysis across diverse outcrop environments.