Beach Leveling Using a Remotely Piloted Aircraft System (RPAS): Problems and Solutions

Estimation of the Block Adjustment Error in UAV Photogrammetric Flights in Flat Areas

UAV-DAP (unmanned aerial vehicle-digital aerial photogrammetry) has become one of the most widely used geomatics techniques in the last decade due to its low cost and capacity to generate high-density point clouds, thus demonstrating its great potential for delivering high-precision products with a spatial resolution of centimetres. The questions is, how should it be applied to obtain the best results? This research explores different flat scenarios to analyse the accuracy of this type of survey based on photogrammetric SfM (structure from motion) technology, flight planning with ground control points (GCPs), and the combination of forward and cross strips, up to the point of processing. The RMSE (root mean square error) is analysed for each scenario to verify the quality of the results. An equation is adjusted to estimate the a priori accuracy of the photogrammetric survey with digital sensors, identifying the best option for μxyz (weight coefficients depending on the layout of both the GCP and the image network) for the four scenarios studied. The UAV flights were made in Lorca (Murcia, Spain). The study area has an extension of 80 ha, which was divided into four blocks. The GCPs and checkpoints (ChPs) were measured using dual-frequency GNSS (global navigation satellite system), with a tripod and centring system on the mark at the indicated point. The photographs were post-processed using the Agisoft Metashape Professional software (64 bits). The flights were made with two multirotor UAVs, a Phantom 3 Professional and an Inspire 2, with a Zenmuse X5S camera. We verify the influence by including additional forward and/or cross strips combined with four GCPs in the corners, plus one additional GCP in the centre, in order to obtain better photogrammetric adjustments based on the preliminary flight planning.

Comparisons of Differential Filtering and Homography Transformation in Modal Parameter Identification from UAV Measurement

This paper proposes a differential filtering method for the identification of modal parameters of bridges from unmanned aerial vehicle (UAV) measurement. The determination of the modal parameters of bridges is a key issue in bridge damage detection. Accelerometers and fixed cameras have disadvantages of deployment difficulty. Hence, the actual displacement of a bridge may be obtained by using the digital image correlation (DIC) technology from the images collected by a UAV. As drone movement introduces false displacement into the collected images, the homography transformation is commonly used to achieve geometric correction of the images and obtain the true displacement of the bridge. The homography transformation is not always applicable as it is based on at least four static reference points on the plane of target points. The proposed differential filtering method does not request any reference points and will greatly accelerate the identification of the modal parameters. The displacement of the points of interest is tracked by the DIC technology, and the obtained time history curves are processed by differential filtering. The filtered signals are input into the modal analysis system, and the basic modal parameters of the bridge model are obtained by the operational modal analysis (OMA) method. In this paper, the power spectral density (PSD) is used to identify the natural frequencies; the mode shapes are determined by the ratio of the PSD transmissibility (PSDT). The identification results of three types of signals are compared: UAV measurement with differential filtering, UAV measurement with homography transformation, and accelerometer-based measurement. It is found that the natural frequencies recognized by these three methods are almost the same. This paper demonstrates the feasibility of UAV-differential filtering method in obtaining the bridge modal parameters; the problems and challenges in UAV measurement are also discussed.

Polymodal Method of Improving the Quality of Photogrammetric Images and Models

Photogrammetry using unmanned aerial vehicles has become very popular and is already commonly used. The most frequent photogrammetry products are an orthoimage, digital terrain model and a 3D object model. When executing measurement flights, it may happen that there are unsuitable lighting conditions, and the flight itself is fast and not very stable. As a result, noise and blur appear on the images, and the images themselves can have too low of a resolution to satisfy the quality requirements for a photogrammetric product. In such cases, the obtained images are useless or will significantly reduce the quality of the end-product of low-level photogrammetry. A new polymodal method of improving measurement image quality has been proposed to avoid such issues. The method discussed in this article removes degrading factors from the images and, as a consequence, improves the geometric and interpretative quality of a photogrammetric product. The author analyzed 17 various image degradation cases, developed 34 models based on degraded and recovered images, and conducted an objective analysis of the quality of the recovered images and models. As evidenced, the result was a significant improvement in the interpretative quality of the images themselves and a better geometry model.

Determining the Seasonal Variability of the Territorial Sea Baseline in Poland (2018–2020) Using Integrated USV/GNSS/SBES Measurements

The Territorial Sea Baseline (TSB) allows coastal states to define the maritime boundaries, such as: contiguous zone, continental shelf, exclusive economic zone and territorial sea. Their delimitations determine what rights (jurisdiction and sovereignty) a given coastal state is entitled to. For many years, the problem of delimiting baseline was considered in two aspects: legal (lack of clear-cut regulations and different interpretations) and measurement (lack of research tools for precise and reliable depth measurement in ultra-shallow waters). This paper aimed to define the seasonal variability of the TSB in 2018–2020. The survey was conducted in three representative waterbodies of the Republic of Poland: open sea, river mouth and exit from a large port, differing between each other in seabed shape. Baseline measurements were carried out with Unmanned Surface Vehicles (USV), equipped with Global Navigation Satellite System (GNSS) geodetic receivers and miniature Single Beam Echo Sounders (SBES). The survey has shown that the smallest seasonal variability of TSB (1.86–3.00 m) was confirmed for the waterbody located near the Vistula Śmiała River mouth, which features steep shores. On the other hand, the greatest variability in the baseline (5.73–8.37 m) as observed in the waterbody adjacent to the public beach in Gdynia. Factors conditioning considerable changes in TSB determination were: periodically performed land reclamation works in the area and the fact that the depth of the waterbody increases slowly when moving away from the coastline.