Accuracy Assessment of UAV-Photogrammetric-Derived Products Using PPK and GCPs in Challenging Terrains: In Search of Optimized Rockfall Mapping

Unmanned aerial photogrammetric surveys are increasingly being used for mapping and studying natural hazards, such as rockfalls. Surveys using unmanned aerial vehicles (UAVs) can be performed in remote, hardly accessible, and dangerous areas, while the photogrammetric-derived products, with high spatial and temporal accuracy, can provide us with detailed information about phenomena under consideration. However, as photogrammetry commonly uses indirect georeferencing through bundle block adjustment (BBA) with ground control points (GCPs), data acquisition in the field is not only time-consuming and labor-intensive, but also extremely dangerous. Therefore, the main goal of this study was to investigate how accurate photogrammetric products can be produced by using BBA without GCPs and auxiliary data, namely using the coordinates X0, Y0 and Z0 of the camera perspective centers computed with PPK (Post-Processing Kinematic). To this end, orthomosaics and digital surface models (DSMs) were produced for three rockfall sites by using images acquired with a DJI Phantom 4 RTK and the two different BBA methods mentioned above (hereafter referred to as BBA_traditional and BBA_PPK). The accuracy of the products, in terms of the Root Mean Square Error (RMSE), was computed by using verification points (VPs). The accuracy of both BBA methods was also assessed. To test the differences between the georeferencing methods, two statistical test were used, namely a paired Student’s t-test, and a non-parametric Wilcoxon signed-rank. The results show that the accuracy of the BBA_PPK is inferior to that of BBA_traditional, with the total RMSE values for the three sites being 0.056, 0.066, and 0.305 m, respectively, compared to 0.019, 0.036 and 0.014 m obtained with BBA_traditional. The accuracies of the BBA methods are reflected in the accuracy of the orthomosaics, whose values for the BBA_PPK are 0.039, 0.043 and 0.157 m, respectively, against 0.029, 0.036 and 0.020 m obtained with the BBA_traditional. Concerning the DSM, those produced with the BBA_PPK method present accuracy values of 0.065, 0.072 and 0.261 m, respectively, against 0.038, 0.060 and 0.030 m obtained with the BBA_traditional. Even though that there are statistically significant differences between the georeferencing methods, one can state that the BBA_PPK presents a viable solution to map dangerous and exposed areas, such as rockfall transit and deposit areas, especially for applications at a regional level.

EXPLOITING MULTI-CAMERA CONSTRAINTS WITHIN BUNDLE BLOCK ADJUSTMENT: AN EXPERIMENTAL COMPARISON

The growing deployment of multi-head camera systems encouraged the emergence of specific processing algorithms, able to face the challenges posed by slanted view geometry. Such multi-camera systems are rigidly tied by their manufacturers hence the exploitation of this internal constraint should be further exploited. Several approaches have been proposed to deal with orientation constraints, with the aim of reducing the number of unknowns, computational time and possibly improve the accuracy. In this paper we compare the results provided by publicly available implementations in order to further investigate the advantages of enforcing relative orientation constraints for aerial and terrestrial triangulation of multi-head camera systems. Data from a Leica CityMapper and a Stereopolis-Ladybug are considered, reporting how constrained solution can improve accuracy with respect to traditional (unconstrained) bundle block adjustment solutions.

LOW-COST DGPS ASSISTED AERIAL TRIANGULATION FOR SUB-DECIMETRIC ACCURACY WITH NON-RTK UAVS

The possibility of equipping UAVs with lightweight GNSS receivers in order to estimate the camera position within a photogrammetric block allows for a reduction of the number of Ground Control Points (GCP), saving time during the field work and decreasing operational costs. Additionally, this makes it possible to build photogrammetric models even in morphologically complex areas or in emergency situations. This work is proposing a non-intrusive and low-cost procedure to retrieve the coordinates of the camera projection centre with decimetric accuracy. The method was designed and tested with the quadcopter DJI Matrice 210 V2 drone equipped with a DJI ZENMUSE X5S camera and an Emlid reach M, a low-cost, single-frequency (L1) GNSS receiver. GNSS observations are post-processed in PPK in order to obtain the UAV trajectory. Synchronization between the camera and the GNSS receiver is achieved by looking at the camera triggering timestamps in flight telemetry data, without requiring an electronic connection between camera and the GNSS that may be troublesome with commercial UAVs. Two surveys were carried out, respectively to calibrate and validate the procedure. The validation test evidenced the possibility of obtaining the coordinates of the camera projection centres with decimetric accuracy. The centre of projections can then be employed for GNSS-assisted aerial triangulation as input of the bundle block adjustment. Provided that at least one GCP is used, it is possible to reach centimetric accuracy on the ground.

High-Quality UAV-Based Orthophotos for Cadastral Mapping: Guidance for Optimal Flight Configurations

During the past years, unmanned aerial vehicles (UAVs) gained importance as a tool to quickly collect high-resolution imagery as base data for cadastral mapping. However, the fact that UAV-derived geospatial information supports decision-making processes involving people’s land rights ultimately raises questions about data quality and accuracy. In this vein, this paper investigates different flight configurations to give guidance for efficient and reliable UAV data acquisition. Imagery from six study areas across Europe and Africa provide the basis for an integrated quality assessment including three main aspects: (1) the impact of land cover on the number of tie-points as an indication on how well bundle block adjustment can be performed, (2) the impact of the number of ground control points (GCPs) on the final geometric accuracy, and (3) the impact of different flight plans on the extractability of cadastral features. The results suggest that scene context, flight configuration, and GCP setup significantly impact the final data quality and subsequent automatic delineation of visual cadastral boundaries. Moreover, even though the root mean square error of checkpoint residuals as a commonly accepted error measure is within a range of few centimeters in all datasets, this study reveals large discrepancies of the accuracy and the completeness of automatically detected cadastral features for orthophotos generated from different flight plans. With its unique combination of methods and integration of various study sites, the results and recommendations presented in this paper can help land professionals and bottom-up initiatives alike to optimize existing and future UAV data collection workflows.

GEOMETRIC ACCURACY EVALUATION OF THE ZY-3 STEREO MAPPING SATELLITE FOR 8 YEARS

The Ziyuan-3 (ZY-3) is the first civil high-resolution optical stereoscopic mapping satellite developed by China. It was launched on January 9, 2012, and as of January 9, 2020, it has been in a continuous operation for 8 years in orbit. The direct geolocation performances of ZY-3 based on the Rational Polynomial Coefficients (RPC) model are discussed, and the monoscopic and stereoscopic geometric accuracy of ZY-3 with ground control point (GCP) have also been studied using a bundle block adjustment with the affine correction in image space. Through the analysis of 47 sets of ZY-3 stereo data in Harbin, China, it can be found that from 2012 to 2019, the ZY-3 geolocation accuracy without GCP remains stable, with an average planimetric accuracy of approximately 16.2m, an average elevation accuracy of about 7.5m. The internal accuracy of the panchromatic triplet images is better than 1.0 pixel, the planimetric accuracy and elevation accuracy of stereo triplets and and stereo pairs are better than 2.0 meters with control points. In general, the results show that the ZY-3 satellite has been in good and stable condition during in-orbit operation in the past 8 years, and the various test indicators have been able to meet the design specifications.

WAVELETS FOR SELF-CALIBRATED BUNDLE BLOCK ADJUSTMENT

This paper entails a methodological novelty and builds upon prior research on a wavelets-based model for digital camera self-calibration. We introduce a new kernel function based on the compactly supported orthogonal third-order asymmetric Daubechies wavelet to correct systematic image distortion errors. Tests are done by using aerial images taken with a high-resolution metric digital aerial mapping camera. The quality of experimental results is evaluated by using reliable and high precision ground check points in the calibration field. For example, a four-fold block with this wavelet self-calibration model has the external accuracy of about 0.28 GSD (=ground sampling distance) in the horizontal direction, and about 0.43 GSD in the vertical direction, respectively, where 1GSD ≈ 4.6cm. The posterior standard deviations σ̂0 of unit weight are reduced from 0.37 pixel to 0.27 pixel. The residual vector lengths are also significantly reduced after our wavelet additional parameters are used. Experimental results support the proposal and demonstrate the applicability of this new model.

BUNDLE BLOCK ADJUSTMENT WITH CONSTRAINED RELATIVE ORIENTATIONS

This paper deals with bundle adjustment with constrained cameras, i.e. where the orientation of certain cameras is expressed relatively to others, and these relative orientations are part of the unknowns. Despite the remarkable interest for oblique multi-camera systems, an empirical study on the effect of enforcing relative orientation constraints in bundle adjustment is still missing. We provide experimental evidence that indeed these constraints improve the accuracy of the results, while reducing the computational load as well. Moreover, we report for the first time in the literature the complete derivation of the Jacobian matrix for bundle adjustment with constrained cameras, to foster other implementations.

ACCURATE REGISTRATION OF AERIAL IMAGES AND ALS-POINTCLOUD VIA AUTOMATED JUNCTION MATCHING AND PLANAR CONSTRAINTS

Accurate geometric registration of images and pointclouds is the key step of many 3D-reconstruction or 3D-sensing tasks. In this paper, a novel L-junction based approach is proposed for semi-automatic accurate registration of aerial images and the airborne laser scanning (ALS) point-cloud in urban areas. The approach achieves accurate registration by associating the LiDAR points with the local planes extracted via L-junction detection and matching from multi-view aerial images. An L-junction is an intersection of two line-segments. Through the forward intersection of multi-view corresponding L-junctions, an accurate local junction-plane can be obtained. In the proposed approach, L-junction is manually collected from one view on the flat object-surfaces like walls, roads, and roofs and then automatically matched to other views with the aid of epipolar-geometry and vanishing-point constraints. Then, a plane-constrained bundle block adjustment of the image-orientation parameters is conducted, where the LiDAR points are treated as reference data. The proposed approach was tested with two datasets collected in Guangzhou city and Ningbo city of China. The experimental results showed that the proposed approach had better accuracy than the closest-point based method. The horizontal/vertical registration RMS of the proposed approach reached 4.21cm/5.72cm in Guangzhou dataset and 4.46cm/4.34cm in Ningbo dataset, which was much less than the average LiDAR-point distance (over 25cm in both datasets) and was very close to the image GSDs (3.2cm in Guangzhou and 4.8cm in Ningbo) and the a-priori ranging accuracy of the ALS equipment (about 3cm).

DIRECT ESTIMATION OF THE RELATIVE ORIENTATION IN UNDERWATER ENVIRONMENT

While accuracy, detail, and limited time on site make photogrammetry a valuable means for underwater mapping, the establishment of reference control networks in such settings is oftentimes difficult. In that respect, the use of the coplanarity constraint becomes a valuable solution as it requires neither knowledge of object space coordinates nor setting a reference control network. Nonetheless, imaging in such domains is subjected to non-linear and depth-dependent distortions, which are caused by refractive media that alter the standard single viewpoint geometry. Accordingly, the coplanarity relation, as formulated for the in-air case does not hold in such environment and methods that have been proposed thus far for geometrical modeling of its effect require knowledge of object-space quantities. In this paper we propose a geometrically-driven approach which fulfills the coplanarity condition and thereby requires no knowledge of object space data. We also study a linear model for the establishment of this constraints. Clearly, a linear form requires neither first approximations nor iterative convergence scheme. Such an approach may prove useful not only for object space reconstruction but also as a preparatory step for application of bundle block adjustment and for outlier detection. All are key features in photogrammetric practices. Results show that no unique setup is needed for estimating the relative orientation parameters using the model and that high levels of accuracy can be achieved.

Accuracy Assessment of a UAV Block by Different Software Packages, Processing Schemes and Validation Strategies

Unmanned aerial vehicle (UAV) systems are heavily adopted nowadays to collect high-resolution imagery with the purpose of documenting and mapping environment and cultural heritage. Such data are currently processed by programs based on the Structure from Motion (SfM) concept, coming from the computer vision community, rather than from classical photogrammetry. It is interesting to check whether some widely accepted rules coming from old-fashioned photogrammetry still holds: the relation between accuracy and ground sampling distance (GSD), the ratio between the vertical and horizontal accuracy, accuracy estimated on ground control points (GCPs) vs. that estimated with check points (CPs) also in relation to their ratio and distribution. To face the envisaged aspects, the paper adopts a comparative approach, as several programs are used and numerous configurations considered. The paper illustrates the dataset adopted, the carefully tuned processing strategies and bundle block adjustment (BBA) results in terms of accuracy for both GCPs and CPs. Finally, a leave-one-out (LOO) cross-validation strategy is proposed to assess the accuracy for one of the proposed configurations. Some of the reported results were previously presented in the 5th GISTAM Conference.