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Kinematic laser scanning is widely used for the fast and accurate acquisition of road corridors. In this context, road monitoring is a crucial application, since deficiencies of the road surface due to non-planarity and subsidence put traffic at risk. In recent years, a Mobile Mapping System (MMS) has been developed at the University of Bonn, consisting of a GNSS/IMU unit and a 2D laser scanner. The goal of this paper is to evaluate the accuracy and precision of this MMS, where the height component is of main interest. Following this, the applicability of the MMS for monitoring the planarity and subsidence of road surfaces is analyzed. The test area for this study is a 6 km long section of the A44n motorway in Germany. For the evaluation of the MMS, leveled control points along the motorway as well as point cloud comparisons of repeated passes were used. In order to transform the ellipsoidal heights of the MMS into the physical height system of the control points, undulations were utilized. In this respect, a local tilt correction for the geoid model was determined based on GNSS baselines and leveling, leading to a physical height accuracy of the MMS of < 10 mm (RMS). The related height precision has a standard deviation of about 5 mm. Hence, a potential subsidence of the road surface in the order of a few cm is detectable. In addition, the point clouds were used to analyze the planarity of the road surface. In the course of this, the cross fall of the road was estimated with a standard deviation of < 0.07 %. Yet, no deficiencies of the road surface in the form of significant rut depths or fictive water depths were detected, indicating the proper condition of the A44n motorway. According to our tests, the MMS is appropriate for road monitoring.

Site-dependent effects are accuracy-limiting factors in static and kinematic GNSS-based positioning applications since they cannot be minimized using differential techniques. In general, these effects are separated into signal diffraction, non-line-of-sight (NLOS) signal reception, multipath, and quality of the satellite geometry. In particular, signal diffraction and NLOS reception can lead to huge positioning errors. We present a straight forward approach to mitigate signal diffraction and NLOS reception by forming obstruction adaptive elevation masks, based on terrestrial laser scans. This enables an improvement of the positioning accuracy in high-precision static GNSS applications, even under challenging GNSS measurement conditions. By means of empirical investigations, the approach was tested successfully, and the site-dependent systematic errors can be separated and analyzed. Furthermore, the site-dependent effects and their error sources are assessed in relation to their impact on the accuracy of the positioning solution. We demonstrate that despite poor GNSS measurement conditions, positional accuracies better than 2 mm can be achieved and the ambiguity fixing rate is improved significantly.

Vegetation is an important factor influencing solifluction processes, while at the same time, solifluction processes and landforms influence species composition, fine-scale distribution and corresponding ecosystem functioning. However, how feedbacks between plants and solifluction processes influence the development of turf-banked solifluction lobes (TBLs) and their geomorphic and vegetation patterns is still poorly understood. We addressed this knowledge gap in a detailed biogeomorphic investigation in the Turtmann glacier foreland (Switzerland). Methods employed include geomorphic and vegetation mapping, terrain assessment with unmanned aerial vehicle (UAV) and temperature logging. Results were subsequently integrated with knowledge from previous geomorphic and ecologic studies into a conceptual model. Our results show that geomorphic and vegetation patterns at TBLs are closely linked through the lobe elements tread, risers and ridge. A conceptual four-stage biogeomorphic model of TBL development with ecosystem engineering by the dwarf shrub Dryas octopetala as the dominant process can explain these interlinked patterns. Based on this model, we demonstrate that TBLs are biogeomorphic structures and follow a cyclic development, during which the role of their components for engineer and non-engineer species changes. Our study presents the first biogeomorphic model of TBL development and highlights the applicability and necessity of biogeomorphic approaches and research in periglacial environments. Copyright © 2016 John Wiley & Sons, Ltd.

In recent years, unmanned aerial vehicles (UAVs) have increasingly been used in various application areas, such as in the remote sensing or surveying. For these applications the UAV has to be equipped with a mapping sensor, which is mostly a camera. Furthermore, a georeferencing of the UAV platform and/or the acquired mapping data is required. The most efficient way to realize this georeferencing is the direct georeferencing, which is based on an onboard multi-sensor system. In recent decades, direct georeferencing systems have been researched and used extensively in airborne, ship and land vehicle applications. However, these systems cannot easily be adapted to UAV platforms, which is mainly due to weight and size limitations. In this paper a direct georeferencing system for micro- and mini-sized UAVs is presented, which consists of a dual-frequency geodetic grade OEM GPS board, a low-cost single-frequency GPS chip, a tactical grade IMU and a magnetometer. To allow for cm-level position and sub-degree attitude accuracies, RTK GPS (real-time kinematic) and GPS attitude (GPS compass) determination algorithms are running on this system, as well as a GPS/IMU integration. Beside the direct georeferencing, also the precise time synchronization of the camera, which acts as the main sensor for mobile mapping applications, and the calibration of the lever arm between the camera reference point and the direct georeferencing reference point are explained in this paper. Especially the high accurate time synchronization of the camera is very important, to still allow for high surveying accuracies, when the images are taken during the motion of the UAV. Results of flight tests demonstrate that the developed system, the camera synchronization and the lever arm calibration make directly georeferenced UAV based single point measurements possible, which have cm-level accuracies on the ground.

For some years now, UAVs (unmanned aerial vehicles) are commonly used for different mobile mapping applications, such as in the fields of surveying, mining or archeology. To improve the efficiency of these applications an automation of the flight as well as the processing of the collected data is currently aimed at. One precondition for an automated mapping with UAVs is that the georeferencing is performed directly with cm-accuracies or better. Usually, a cm-accurate direct positioning of UAVs is based on an onboard multi-sensor system, which consists of an RTK-capable (real-time kinematic) GPS (global positioning system) receiver and additional sensors (e.g. inertial sensors). In this case, the absolute positioning accuracy essentially depends on the local GPS measurement conditions. Especially during mobile mapping applications in urban areas, these conditions can be very challenging, due to a satellite shadowing, non-line-of sight receptions, signal diffraction or multipath effects. In this paper, two straightforward and easy to implement strategies will be described and analyzed, which improve the direct positioning accuracies for UAV-based mapping and surveying applications under challenging GPS measurement conditions. Based on a 3D model of the surrounding buildings and vegetation in the area of interest, a GPS geometry map is determined, which can be integrated in the flight planning process, to avoid GPS challenging environments as far as possible. If these challenging environments cannot be avoided, the GPS positioning solution is improved by using obstruction adaptive elevation masks, to mitigate systematic GPS errors in the RTK-GPS positioning. Simulations and results of field tests demonstrate the profit of both strategies.

Online pose estimation and mapping in unknown environments is essential for most mobile robots. Especially autonomous unmanned aerial vehicles require good pose estimates at comparably high frequencies. In this paper, we propose an effective system for online pose and simultaneous map estimation designed for light-weight UAVs. Our system consists of two components: (1) real-time pose estimation combining RTK-GPS and IMU at 100 Hz and (2) an effective SLAM solution running at 10 Hz using image data from an omnidirectional multi-fisheye-camera system. The SLAM procedure combines spatial resection computed based on the map that is incrementally refined through bundle adjustment and combines the image data with raw GPS observations and IMU data on keyframes. The overall system yields a real-time, georeferenced pose at 100 Hz in GPS-friendly situations. Additionally, we obtain a precise pose and feature map at 10 Hz even in cases where the GPS is not observable or underconstrained. Our system has been implemented and thoroughly tested on a 5 kg copter and yields accurate and reliable pose estimation at high frequencies. We compare the point cloud obtained by our method with a model generated from georeferenced terrestrial laser scanner.

Antenna near-field effects are one of the accuracy limiting factors on GNSS-based distance measurements. In order to analyse these influences, a measurement campaign at an EDM calibration baseline site with optimum GNSS conditions was performed. To vary the distance between the antenna mount and the absolutely calibrated antennas, spacers with different lengths were used. Due to the comparison of the resulting GNSS-based distance measurements to a reference solution, the influences of the antenna near-field could be analyzed.The standard deviations of the differences to the reference solution, i. e., 0.31 mm for the distance and 0.46 mm for the height component, indicate that equal spacer and antenna combinations at both stations lead to a very high accuracy level. In contrast, different spacer and antenna combinations decrease the accuracy level. Thus, an identical set-up at both antenna stations and the usage of individually calibrated antennas minimize the near-field effects during the double-differencing process. Hence, these aspects can be identified as a prerequisite for highly accurate GNSS-measurements.In addition to near-field effects, the influence of satellite obstructions is investigated. Four realistic shadowing scenarios are numerically simulated on the basis of the observations, which were collected in the optimum surrounding of the EDM calibration baseline site. The comparison to nominal values indicates that a shadowing leads only to a slight decreasing of the accuracy. Consequently, there is a strong suspicion that multipath effects and signal distortions seem to have a greater influence on the accuracy of GNSS-based distance measurements than the satellite constellation.