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[Display omitted] • A novel UAV-based snow depth retrieval method combining MSI imagery and direct georeferencing was tested in Northern Sweden. • The preprocessing routine improved the automatic feature detection in homogeneous snow areas generating 10× more key points. • The importance of red and NIR bands for 3D reconstruction of snow areas has been highlighted and quantified through PCA. • Snow depth maps were estimated with high accuracy (RSME 11.52 cm) for optimal illumination conditions. • The data set composed by UAV multispectral imagery, GNSS and IMU data, and ground validation is openly and freely available. More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (< 7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of closing the scale gap between discrete point measurements and regional-scale remote sensing and complements large-scale remote sensing data and snow model output with an adequate validation source. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Accuracy and cost-analysis of 4 UAV georeferencing methods (ASPRS standards). • UAV GNSS data without post-processing can be used in combination with Sentinel-2. • PPK1 single-frequency with corrections of a base at <4 km can reach RMSEr≤0.256 m. • PPK2 double-frequency with a base in the study area can reach RMSEr≤0.036 m. • GCP the most accurate, PPK2 the most expensive, PPK1 avoids in situ ground support. • Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms. Abstract This work is aimed at the environmental remote sensing community that uses UAV optical frame imagery in combination with airborne and satellite data. Taking into account the economic costs involved and the time investment, we evaluated the fit-for-purpose accuracy of four positioning methods of UAV-acquired imagery: 1) direct georeferencing using the onboard raw GNSS (GNSSNAV) data, 2) direct georeferencing using Post-Processed Kinematic single-frequency carrier-phase without in situ ground support (PPK1), 3) direct georeferencing using Post-Processed Kinematic double-frequency carrier-phase GNSS data with in situ ground support (PPK2), and 4) indirect georeferencing using Ground Control Points (GCP). We tested a multispectral sensor and an RGB sensor, onboard multicopter platforms. Orthophotomosaics at <0.05 m spatial resolution were generated with photogrammetric software. The UAV image absolute accuracy was evaluated according to the ASPRS standards, wherein we used a set of GCPs as reference coordinates, which we surveyed with a differential GNSS static receiver. The raw onboard GNSSNAV solution yielded horizontal (radial) accuracies of RMSEr≤1.062 m and vertical accuracies of RMSEz≤4.209 m; PPK1 solution gave decimetric accuracies of RMSEr≤0.256 m and RMSEz≤0.238 m; PPK2 solution, gave centimetric accuracies of RMSEr≤0.036 m and RMSEz≤0.036 m. These results were further improved by using the GCP solution, which yielded accuracies of RMSEr≤0.023 m and RMSEz≤0.030 m. GNSSNAV solution is a fast and low-cost option that is useful for UAV imagery in combination with remote sensing products, such as Sentinel-2 satellite data. PPK1, which can register UAV imagery with remote sensing products up to 0.25 m pixel size, as WorldView-like satellite imagery, airborne lidar or orthoimagery, has a higher economic cost than the GNSSNAV solution. PPK2 is an acceptable option for registering remote sensing products of up to 0.05 m pixel size, as with other UAV images. Moreover, PPK2 can obtain accuracies that are approximate to the usual UAV pixel size (e.g. co-register in multitemporal studies), but it is more expensive than PPK1. Although indirect georeferencing can obtain the highest accuracy, it is nevertheless a time-consuming task, particularly if many GCPs have to be placed. The paper also provides the approximate cost of each solution. [ABSTRACT FROM AUTHOR]

Processing of raw point cloud data obtained as a result of terrestrial laser scanning (TLS) sometimes involves georeferencing, i.e. transformation of point cloud data to an external coordinate system. This paper focuses on defining the error model of point positions obtained through a “station-orientation” procedure of direct georeferencing. The original error model presented by the authors relevant in this field is partly altered. All modifications are explained in detail within the paper and the reported model is statistically verified based on the carefully conducted experiment using Leica ScanStation P20 scanner. The obtained values of the uncertainty measures of direct georeferencing which are of a few millimetre magnitude prove that this procedure can be efficiently used for planning and carrying out even more demanding surveying tasks, including those during monitoring and maintenance of constructed facilities. Additionally, traversing capabilities of terrestrial laser scanners tightly connected with direct georeferencing should contribute to mass introduction of laser scanning into the construction industry thanks to its similarities to the highly automated procedures of polar surveying and traversing which are traditionally employed among surveyors. [ABSTRACT FROM AUTHOR]

Reconstruction of 3D models through integrating vertical and oblique imagery has been studied extensively. For a 3D reconstruction, object point cloud coordinates could be calculated using direct georeferencing (DG) obtained from the direct orientation data of a GPS/INS system. This paper implemented DG approaches for vertical and oblique imagery in the earth centered earth fixed frame (e-frame), local tangent frame (l-frame), and map projection frame (p-frame), respectively. In the p-frame, the earth curvature correction formulas were derived through naturalizing oblique imagery to vertical imagery to achieve a high positioning precision. Five basic stereo-pair models for vertical and oblique imagery were simulated to verify the positioning accuracy of different frames. Simulation experiments showed that DG in the e-frame and l-frame of these five scenarios were rigorous, and no systematic errors were imported by the DG model as these frames are Cartesian. DG in the p-frame has obvious systematic errors which are aroused by the earth curvature and projection deformation unconformity in the vertical and horizontal directions. These errors, however, can be compensated effectively through correcting image coordinates of the oblique imagery by extending the standard image coordinate correction approach and the exterior orientation (EO) height term. After the correction, the absolute positioning error is lower than 1/20 GSD for simulation test-1. In the p-frame, the process is straightforward, and it is convenient for producing maps. For high accuracy DG, though, it is recommended to adopt e-frame or l-frame options. [ABSTRACT FROM AUTHOR]

Abstract: This paper develops a novel Coordinate Transformation method (CT-method), with which the orientation angles (roll, pitch, heading) of the local tangent frame of the GPS/INS system are transformed into those (omega, phi, kappa) of the map projection frame for direct georeferencing (DG). Especially, the orientation angles in the map projection frame were derived from a sequence of coordinate transformations. The effectiveness of orientation angles transformation was verified through comparing with DG results obtained from conventional methods (Legat method [1] Legat method: Klaus Legat published the paper “Approximate direct georeferencing in national coordinates” in 2006. He presented a method to calculate the attitude matrix and perspective center (PC) coordinates in national mapping frame. This method is termed Legat method in this paper. 1 and POSPac method [2] POSPac method: The method is presented by Applanix POSPac software technical note (Hutton and Savina, 1997). It is implemented in the POSEO module of POSPac software. 2 ) using empirical data. Moreover, the CT-method was also validated with simulated data. One advantage of the proposed method is that the orientation angles can be acquired simultaneously while calculating position elements of exterior orientation (EO) parameters and auxiliary points coordinates by coordinate transformation. These three methods were demonstrated and compared using empirical data. Empirical results show that the CT-method is both as sound and effective as Legat method. Compared with POSPac method, the CT-method is more suitable for calculating EO parameters for DG in map projection frames. DG accuracy of the CT-method and Legat method are at the same level. DG results of all these three methods have systematic errors in height due to inconsistent length projection distortion in the vertical and horizontal components, and these errors can be significantly reduced using the EO height correction technique in Legat’s approach. Similar to the results obtained with empirical data, the effectiveness of the CT-method was also proved with simulated data. [Copyright &y& Elsevier]

Abstract: The accessibility of global data, such as the digital elevation model (DEM), and the development of global visualisations allow promising new methods for minimising the distortion in the online generation of rough orthorectified products to be developed. Direct georeferencing (DG) has attracted a considerable amount of attention in the applications of pushbroom raw images in orthorectification or mono-plotting using ancillary satellite data. This study builds on recent DG studies to achieve an “orthoimage” from raw data and to determine potential mapping errors due to the DG procedure. Thus, this paper focuses on establishing a simple method for mitigating the misalignments of space-borne imageries to be used in direct orthorectification. Towards this goal, instead of image resectioning, affine transformation in different coordinate systems is employed in the orthorectification algorithm to compensate for the systematic DG errors. For a given point, the elevation corresponding to the obtained planimetric coordinate is extracted using available topographic maps and global DEMs, such as SRTM’s and ASTER’s DEMs. As a result, parameters no longer need to be updated, as in the conventional orthophoto generation methods. To evaluate the proposed procedures, experiments were conducted over three different IRS-p6 sensors in five datasets with different swath widths and tilt angles. The obtained results also demonstrate that the geographic coordinate system and a simple 2D affine transformation can efficiently correct misalignments. [Copyright &y& Elsevier]

Abstract: During the HRS (High Resolution Stereo) Scientific Assessment Program the French space agency CNES delivered data sets from the HRS camera system with high precision ancillary data. Two test data sets from this program were evaluated: one is located in Germany, the other in Spain. The first goal was to derive orthoimages and digital surface models (DSM) from the along track stereo data by applying the rigorous model with direct georeferencing and without ground control points (GCPs). For the derivation of DSM, the stereo processing software, developed at DLR for the MOMS-2P three line stereo camera was used. As a first step, the interior and exterior orientation of the camera, delivered as ancillary data from positioning and attitude systems were extracted. A dense image matching, using nearly all pixels as kernel centers provided the parallaxes. The quality of the stereo tie points was controlled by forward and backward matching of the two stereo partners using the local least squares matching method. Forward intersection lead to points in object space which are subsequently interpolated to a DSM in a regular grid. DEM filtering methods were also applied and evaluations carried out differentiating between accuracies in forest and other areas. Additionally, orthoimages were generated from the images of the two stereo looking directions. The orthoimage and DSM accuracy was determined by using GCPs and available reference DEMs of superior accuracy (DEM derived from laser data and/or classical airborne photogrammetry). As expected the results obtained without using GCPs showed a bias in the order of 5–20 m to the reference data for all three coordinates. By image matching it could be shown that the two independently derived orthoimages exhibit a very constant shift behavior. In a second step few GCPs (3–4) were used to calculate boresight alignment angles, introduced into the direct georeferencing process of each image independently. This method improved the absolute accuracy of the resulting orthoimages and DSM significantly. [Copyright &y& Elsevier]