This paper presents a new development in photogrammetric measurement: Structure from Motion (SfM). The authors demonstrate that SfM can produce high-resolution topographic data with high accuracy and precision, comparable to traditional photogrammetry and LiDAR. The study uses a helikite platform to collect aerial photographs and compares the results with GPS and LiDAR data. The SfM approach uses images from multiple viewpoints to reconstruct three-dimensional geometry of an object without requiring ground control points. This method relies on automated image matching and bundle adjustment to calculate topography. The results show that SfM can produce high-quality topographic data with a point density of 10.8 points/m², which is much higher than LiDAR's 0.33 points/m². The SfM data were compared with GPS and LiDAR data, and the results showed a near 1:1 fit between the datasets. The authors conclude that SfM is a viable alternative to traditional photogrammetry and LiDAR for producing high-resolution topographic data. The study also highlights the potential of SfM for use in a wide range of applications, including fluvial geomorphology, disaster response, and environmental monitoring. The authors note that SfM is a cost-effective and accessible method that can be used with freely available software and a variety of platforms, including UAVs and hand-held cameras. However, the method has limitations, such as poor performance in areas with low textural diversity or in areas with smooth surfaces. The study also discusses the potential for further improvements in SfM technology, including the use of high-definition video cameras and more advanced software for denser point cloud reconstruction. Overall, the study demonstrates that SfM is a promising new method for producing high-resolution topographic data with high accuracy and precision.This paper presents a new development in photogrammetric measurement: Structure from Motion (SfM). The authors demonstrate that SfM can produce high-resolution topographic data with high accuracy and precision, comparable to traditional photogrammetry and LiDAR. The study uses a helikite platform to collect aerial photographs and compares the results with GPS and LiDAR data. The SfM approach uses images from multiple viewpoints to reconstruct three-dimensional geometry of an object without requiring ground control points. This method relies on automated image matching and bundle adjustment to calculate topography. The results show that SfM can produce high-quality topographic data with a point density of 10.8 points/m², which is much higher than LiDAR's 0.33 points/m². The SfM data were compared with GPS and LiDAR data, and the results showed a near 1:1 fit between the datasets. The authors conclude that SfM is a viable alternative to traditional photogrammetry and LiDAR for producing high-resolution topographic data. The study also highlights the potential of SfM for use in a wide range of applications, including fluvial geomorphology, disaster response, and environmental monitoring. The authors note that SfM is a cost-effective and accessible method that can be used with freely available software and a variety of platforms, including UAVs and hand-held cameras. However, the method has limitations, such as poor performance in areas with low textural diversity or in areas with smooth surfaces. The study also discusses the potential for further improvements in SfM technology, including the use of high-definition video cameras and more advanced software for denser point cloud reconstruction. Overall, the study demonstrates that SfM is a promising new method for producing high-resolution topographic data with high accuracy and precision.