Topographic and geomorphological surveys of coastal areas usually require the aerial mapping of long and narrow sections of littoral. The georeferencing of photogrammetric models is generally based on the signalization and survey of Ground Control Points (GCPs), which are very time-consuming tasks. Direct georeferencing with high camera location accuracy due to on-board multi-frequency GNSS receivers can limit the need for GCPs. Recently, DJI has made available the Phantom 4 Real-Time Kinematic (RTK) (DJI-P4RTK), which combines the versatility and the ease of use of previous DJI Phantom models with the advantages of a multi-frequency on-board GNSS receiver. In this paper, we investigated the accuracy of both photogrammetric models and Digital Terrain Models (DTMs) generated in Agisoft Metashape from two different image datasets (nadiral and oblique) acquired by a DJI-P4RTK. Camera locations were computed with the Post-Processing Kinematic (PPK) of the Receiver Independent Exchange Format (RINEX) file recorded by the aircraft during flight missions. A Continuously Operating Reference Station (CORS) located at a 15 km distance from the site was used for this task. The results highlighted that the oblique dataset produced very similar results, with GCPs (3D RMSE = 0.025 m) and without (3D RMSE = 0.028 m), while the nadiral dataset was affected more by the position and number of the GCPs (3D RMSE from 0.034 to 0.075 m). The introduction of a few oblique images into the nadiral dataset without any GCP improved the vertical accuracy of the model (Up RMSE from 0.052 to 0.025 m) and can represent a solution to speed up the image acquisition of nadiral datasets for PPK with the DJI-P4RTK and no GCPs. Moreover, the results of this research are compared to those obtained in RTK mode for the same datasets. The novelty of this research is the combination of a multitude of aspects regarding the DJI Phantom 4 RTK aircraft and the subsequent data processing strategies for assessing the quality of photogrammetric models, DTMs, and cross-section profiles.

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The sudden algal bloom in shallow water may be a serious problem for sea coastal economy based on clams farming because it leads quickly to anoxia conditions with the consequent death of the molluscs. In order to detect the rise of algae, normally satellite remote sensing is used, exploiting the higher response in the near infrared wavelengths. A recent progress in monitoring this phenomenon derives from the availability of unmanned aerial vehicles (UAVs) equipped with lightweight multispectral cameras. Such technique makes it possible to acquire detailed spectral information with narrow bands attaining an assessment of the algal bloom at both high geometric and radiometric resolutions. In this work, we tested the MicaSense RedEdge-M multispectral camera mounted on a DJI Phantom 3 Professional aircraft to map submerged seaweeds and assess their evolution with particular regard to the importance of the radiometric calibration of raw imageries using a Downwelling Light Sensor (DLS) and a known reflectance panel. The case study is the lagoon of Goro (Northern Adriatic Sea, Italy), a crucial environment for the clams farming in the Emilia-Romagna region. Digital images acquired in two subsequent flights were processed with either Agisoft PhotoScan Professional and Pix4D Mapper Pro varying the calibration strategies. After a pre-analysis, we applied two different approaches for the seaweed detection: NDVI and maximum likelihood classification. All the tests performed in this study confirm that the monitoring over time with a multispectral lightweight camera mounted on a UAV is possible, but also that by applying proper radiometric corrections, most accurate and reliable results can be achieved.

<p><strong>Abstract.</strong> Imagery acquisition systems by Unmanned Aerial Vehicles (UAVs) have been rapidly evolving within the last few years. In mapping applications, it is the introduction of a considerable amount of Ground Control Points (GCPs) that enables the final reconstruction of a real-scale framed model. Since the survey of GCPs generally requires the use of total stations or GNSS receivers in Real Time Kinematic (RTK), either with or without a Network approach (NRTK), this on-site operation is particularly time consuming. In addition, the lack of clearly image-recognizable points may force the use of artificial markers (signalised GCPs) whenever no features are naturally available in the field. This implies a real waste of time for the deployment of the targets, as well as for their recovery. Recently, aircrafts’ manufacturers have integrated the on-board RTK capability on their UAVs. In such a way, the high precision GNSS system allows the 3D position detection of the camera at the time of each capture within few centimetres. In this work, we tested the DJI Phantom 4 RTK for the topographic survey of a coastal section in the Northern Adriatic Sea (Italy). The flights were performed flying at an 80&amp;thinsp;m altitude to ensure a Ground Sample Distance (GSD) of about 2 centimetres. The site extended up to 2 kilometres longitudinally. The results confirm that the on-board RTK approach really speeds up the precise mapping of coastal regions and that a single GCP may be needed to make a reliable estimation of the focal length.</p>

Aerial photogrammetry by Unmanned Aerial Vehicles (UAVs) is a widespread method to perform mapping tasks with high-resolution to reconstruct three-dimensional (3D) building and façade models. However, the survey of Ground Control Points (GCPs) represents a time-consuming task, while the use of Real-Time Kinematic (RTK) drones allows for one to collect camera locations with an accuracy of a few centimeters. DJI Phantom 4 RTK (DJI-P4RTK) combines this with the possibility to acquire oblique images in stationary conditions and it currently represents a versatile drone widely used from professional users together with commercial Structure-from-Motion software, such as Agisoft Metashape. In this work, we analyze the architectural application of this drone to the photogrammetric modeling of a building with particular regard to metric survey specifications for cultural heritage for 1:20, 1:50, 1:100, and 1:200 scales. In particular, we designed an accuracy assessment test signalizing 109 points, surveying them with total station and adjusting the measurements through a network approach in order to achieve millimeter-level accuracy. Image datasets with a designed Ground Sample Distance (GSD) of 2 mm were acquired in Network RTK (NRTK) and RTK modes in manual piloting and processed both as single façades (S–F) and as an overall block (4–F). Subsequently, we compared the results of photogrammetric models generated in Agisoft Metashape to the Signalized Point (SP) coordinates. The results highlight the importance of processing an overall photogrammetric block, especially whenever part of camera locations exhibited a poorer accuracy due to multipath effects. No significant differences were found between the results of network real-time kinematic (NRTK) and real-time kinematic (RTK) datasets. Horizontal residuals were generally comparable to GNSS accuracy in NRTK/RTK mode, while vertical residuals were found to be affected by an offset of about 5 cm. We introduced an external GCP or used one SP per façade as GCP, assuming a poorer camera location accuracy at the same time, in order to fix this issue and comply with metric survey specifications for the widest architectural scale range. Finally, both S–F and 4–F projects satisfied the metric survey requirements of a scale of 1:50 in at least one of the approaches tested.

Coastal environments are usually characterized by a brittle balance, especially in terms of sediment transportation. The formation of dunes, as well as their sudden destruction as a result of violent storms, affects this balance in a significant way. Moreover, the growth of vegetation on the top of the dunes strongly influences the consequent growth of the dunes themselves. This work presents the results obtained through a long-term monitoring of a complex dune system by the use of Unmanned Aerial Vehicles (UAVs). Six different surveys were carried out between November 2015 and December 2017 in the littoral of Rosolina Mare (Italy). Aerial photogrammetric data were acquired during flight repetitions by using a DJI Phantom 3 Professional with the camera in a nadiral arrangement. The processing of the captured images consisted of the reconstruction of a three-dimensional model using the Structure-from-Motion (SfM). Each model was framed in the European Terrestrial Reference System (ETRS) using GNSS geodetic receivers in Network Real Time Kinematic (NRTK). Specific data management was necessary due to the vegetation by filtering the dense cloud. This task was performed by both performing a slope detection and a removal of the residual outliers. The final products of this approach were thus represented by Digital Elevation Models (DEMs) of the sandy coastal section. In addition, DEMs of Difference (DoD) were also computed for the purpose of monitoring over time and detecting variations. The accuracy assessment of the DEMs was carried out by an elevation comparison through especially GNSS-surveyed points. Relevant cross sections were also extracted and compared. The use of the Structure-from-Motion approach by UAVs finally proved to be both reliable and time-saving thanks to quicker in situ operations for the data acquisition and an accurate reconstruction of high-resolution elevation models. The low cost of the system and its flexibility represent additional strengths, making this technique highly competitive with traditional ones.

Anthropogenic marine debris (AMD) represent a global threat for aquatic environments. It is important to locate and monitor the distribution and presence of macroplastics along beaches to prevent degradation into microplastics (MP), which are potentially more harmful and more difficult to remove. UAV imaging represents a quick method for acquiring pictures with a ground spatial resolution of a few centimeters. In this work, we investigate strategies for AMD mapping on beaches with different ground resolutions and with elevation and multispectral data in support of RGB orthomosaics. Operators with varying levels of expertise and knowledge of the coastal environment map the AMD on four to five transects manually, using a range of photogrammetric tools. The initial survey was repeated after one year; in both surveys, beach litter was collected and further analyzed in the laboratory. Operators assign three levels of confidence when recognizing and describing AMD. Preliminary validation of results shows that items identified with high confidence were almost always classified properly. Approaching the detected items in terms of surface instead of a simple count increased the percentage of mapped litter significantly when compared to those collected. Multispectral data in near-infrared (NIR) wavelengths and digital surface models (DSMs) did not significantly improve the efficiency of manual mapping, even if vegetation features were removed using NDVI maps. In conclusion, this research shows that a good solution for performing beach AMD mapping can be represented by using RGB imagery with a spatial resolution of about 200 pix/m for detecting macroplastics and, in particular, focusing on the largest items. From the point of view of assessing and monitoring potential sources of MP, this approach is not only feasible but also quick, practical, and sustainable.

ABSTRACT:The balance of a coastal environment is particularly complex: the continuous formation of dunes, their destruction as a result of violent storms, the growth of vegetation and the consequent growth of the dunes themselves are phenomena that significantly affect this balance. This work presents an approach to the long-term monitoring of a complex dune system by means of Unmanned Aerial Vehicles (UAVs). Four different surveys were carried out between November 2015 and November 2016. Aerial photogrammetric data were acquired during flights by a DJI Phantom 2 and a DJI Phantom 3 with cameras in a nadiral arrangement. GNSS receivers in Network Real Time Kinematic (NRTK) mode were used to frame models in the European Terrestrial Reference System. Processing of the captured images consisted in reconstruction of a three-dimensional model using the principles of Structure from Motion (SfM). Particular care was necessary due to the vegetation: filtering of the dense cloud, mainly based on slope detection, was performed to minimize this issue. Final products of the SfM approach were represented by Digital Elevation Models (DEMs) of the sandy coastal environment. Each model was validated by comparison through specially surveyed points. Other analyses were also performed, such as cross sections and computing elevation variations over time. The use of digital photogrammetry by UAVs is particularly reliable: fast acquisition of the images, reconstruction of high-density point clouds, high resolution of final elevation models, as well as flexibility, low cost and accuracy comparable with other available techniques.