Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams

AbstractHigh resolution topographic data are necessary to understand benthic habitat, quantify processes at the water-sediment interface, and support computational fluid dynamics models for both surface and hyporheic hydraulics. In riverine systems, these data are typically collected using traditional surveying methods (total station, DGPS, etc.), airborne or terrestrial laser scanning, and photogrammetry. Recently, handheld surveying equipment has been rapidly acquiring popularity in part due to its processing capacity, price, size, and versatility. One such device is the iPhone LiDAR, which could have a good balance between precision and ease of use and is a potential replacement for conventional measuring tools. Here, we evaluated the accuracy of the LiDAR sensor and a Structure from Motion (SfM) method based on photos collected using the iPhone Cameras. We compared the LiDAR and SfM elevations to those from a high-precision laser scanner for an experimental rough water-worked gravel-bed channel with boulder-like structures. We observed that both the LiDAR and SfM methods captured the overall streambed morphology and detected large (Hs ≥ 15 cm) and macro (5 cm ≤ Hs < 15 cm) scales of topographic variations (Hs, roughness). The SfM technique also captured small scale (Hs <5cm) roughness whereas the LiDAR consistently simplified it with errors of ∼3.7 mm.Keywords: iPhone LiDARStructure from motionChannel bed roughness Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis research was partially supported by National Science Foundation 2100926 grant.