Abstract. Photogrammetry and geosciences have been closely linked since the late 19th century due to the acquisition of high-quality 3-D data sets of the environment, but it has so far been restricted to a limited range of remote sensing specialists because of the considerable cost of metric systems for the acquisition and treatment of airborne imagery. Today, a wide range of commercial and open-source software tools enable the generation of 3-D and 4-D models of complex geomorphological features by geoscientists and other non-experts users. In addition, very recent rapid developments in unmanned aerial vehicle (UAV) technology allow for the flexible generation of high-quality aerial surveying and ortho-photography at a relatively low cost.The increasing computing capabilities during the last decade, together with the development of highperformance digital sensors and the important software innovations developed by computer-based vision and visual perception research fields, have extended the rigorous processing of stereoscopic image data to a 3-D point cloud generation from a series of non-calibrated images. Structure-from-motion (SfM) workflows are based upon algorithms for efficient and automatic orientation of large image sets without further data acquisition information, examples including robust feature detectors like the scale-invariant feature transform for 2-D imagery. Nevertheless, the importance of carrying out well-established fieldwork strategies, using proper camera settings, ground control points and ground truth for understanding the different sources of errors, still needs to be adapted in the common scientific practice.This review intends not only to summarise the current state of the art on using SfM workflows in geomorphometry but also to give an overview of terms and fields of application. Furthermore, this article aims to quantify already achieved accuracies and used scales, using different strategies in order to evaluate possible stagnations of current developments and to identify key future challenges. It is our belief that some lessons learned from former articles, scientific reports and book chapters concerning the identification of common errors or "bad practices" and some other valuable information may help in guiding the future use of SfM photogrammetry in geosciences.

This study presents a computer vision application of the structure from motion (SfM) technique in three dimensional high resolution gully monitoring in southern Morocco. Due to impractical use of terrestrial Light Detection and Ranging (LiDAR) in difficult to access gully systems, the inexpensive SfM is a promising tool for analyzing and monitoring soil loss, gully head retreat and plunge pool development following heavy rain events. Objects with known dimensions were placed around the gully scenes for scaling purposes as a workaround for ground control point (GCP) placement. Additionally, the free scaling with objects was compared to terrestrial laser scanner (TLS) data in a field laboratory in Germany. Results of the latter showed discrepancies of 5.6% in volume difference for erosion and 1.7% for accumulation between SfM and TLS. In the Moroccan research area soil loss varied between 0.58 t in an 18.65 m

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ABSTRACT:This study evaluates the potential that lies in the photogrammetric processing of aerial images captured by unmanned aerial vehicles. UAV-Systems have gained increasing attraction during the last years. Miniaturization of electronic components often results in a reduction of quality. Especially the accuracy of the GPS/IMU navigation unit and the camera are of the utmost importance for photogrammetric evaluation of aerial images. To determine the accuracy of digital elevation models (DEMs), an experimental setup was chosen similar to the situation of data acquisition during a field campaign. A quarry was chosen to perform the experiment, because of the presence of different geomorphologic units, such as vertical walls, piles of debris, vegetation and even areas. In the experimental test field, 1042 ground control points (GCPs) were placed, used as input data for the photogrammetric processing and as high accuracy reference data for evaluating the DEMs. Further, an airborne LiDAR dataset covering the whole quarry and additional 2000 reference points, measured by total station, were used as ground truth data. The aerial images were taken using a MAVinci Sirius I -UAV equipped with a Canon 300D as imaging system. The influence of the number of GCPs on the accuracy of the indirect sensor orientation and the absolute deviation's dependency on different parameters of the modelled DEMs was subject of the investigation. Nevertheless, the only significant factor concerning the DEMs accuracy that could be isolated was the flying height of the UAV.