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The analysis based on geospatial data from different measurement systems now constitutes a complex numerical and practical enterprise. The dynamic development of modern technologies enables rapid and precise acquisition of such data. Nonetheless, the diversity of reference systems is today one of the main challenges for their correct interpretation. The combined use of the processed measurement results and archival data in paper form constitutes an important direction for the development of this discipline. This issue is visible during the implementation of complex hydrographic and geodetic surveys requiring geospatial integration of results. The publication presents both the theoretical basis and the practical verification of the adopted methodology. The research material comes from the measurement campaign conducted to determine geospatial parameters for the tombolo phenomenon in Sopot. The results of differential GNSS RTK measurements, terrestrial laser scanning, bathymetric survey, photogrammetry, and analog archival bathymetric map were subjected to the integration process. The effectiveness of the presented procedure was confirmed by the obtained error estimators of values not exceeding three centimeters.

The study aims to assess the applicability of the ordinary least squares method, robust estimation, and conditions-binded adjustment in processing the six synchronous coordinate pairs of global navigation satellite system (GNSS) receivers. The research is part of the research project InnoSatTrack, focused on the enhancement of the determination of geometrical parameters of railway tracks using GNSS, inertial, and other sensors. A fixed frame of installation of six receivers is used in the data processing. Due to the limited availability of railway routes for measurements, the stationary campaign was conducted to gather data for the adjustment procedures tests. Six GNSS receivers in the frame-restricted configuration were set up using the tachymetric method for recording 96,729 synchronous static observations. Post-processed coordinates of the receivers were adjusted according to the geometrical conditions of the survey frame. Analysis showed higher applicability of the conditions-binded method than other estimation methods by obtaining superior results in both the precision and the maintenance of the design conditions factors than in the OLS and robust estimators.

Currently, the primary method for determining the object coordinates is positioning using Global Navigation Satellite Systems (GNSS) supported by Inertial Navigation Systems (INS). The main goal of this solution is to ensure high positioning availability, particularly when access to satellite signals is limited (in tunnels, areas with densely concentrated buildings and in forest areas). The aim of this article is to determine whether the GNSS/INS system supported by the RTK receiver is suitable for the implementation of selected geodetic and construction tasks in railway engineering, such as determining the place and extent of rail track deformations (1 cm (p = 0.95)), the process of a rapid stocktaking of existing rail tracks (3 cm (p = 0.95)) and for design and construction works (10 cm (p = 0.95)), as well as what the impact of various terrain obstacles have on the obtained positioning accuracy of the tested system. During the research, one INS was used, the Ekinox2-U by the SBG Systems, which was supported by the Real-Time Kinematic (RTK) receiver. GNSS/INS measurements were conducted on three representative sections varying in terms of terrain obstacles that limit the access to satellite signals during mobile railway measurements in Tricity (Poland). The acquired data allowed us to calculate the basic position accuracy measures that are commonly used in navigation and transport applications. On this basis, it was concluded that the Ekinox2-U system can satisfy the positioning accuracy requirements for rapid stocktaking of existing rail tracks (3 cm (p = 0.95)), as well as for design and construction works (10 cm (p = 0.95)). On the other hand, the system cannot be used to determine the place and extent of rail track deformations (1 cm (p = 0.95)).

A photogrammetry from an unmanned aerial vehicle (UAV) can be understood as a new measurement tool. It introduces low-cost alternatives for a traditional aerial photogrammetry, combining terrestrial, aerial, and satellite photogrammetry techniques. This paper presents a photogrammetric UAV construction basics, a recommended platform analysis, and a review of commercially available components and systems’ elements designed for photogrammetric UAV purposes. As the results show, a motoglider can be recommended as a platform for a photogrammetric task, where the priority is to execute the maximum area coverage during one flight. That platform type is resistant to windy conditions and is able to execute long flight, opposite to multirotor platforms.[b]Keywords:[/b] photogrammetry, remote sensing, navigation, unmanned aerial vehicle, commercial of-the-shelf

Bathymetric surveys of the same body of water, performed at regular intervals, apart from updating the geospatial information used to create paper and electronic maps, allow for several additional analyses, including an evaluation of geomorphological changes occurring in the coastal zone. This research is particularly important in places where the shape of the coastal zone has been violently disturbed, including by human activity. Tombolo is such a phenomenon and it dynamically shapes the new hydrological conditions of the coastal zone. Apart from natural factors, it may be caused by the construction of hydrotechnical facilities in the littoral zone. It causes a significant disturbance in the balance of the marine environment, resulting in the bottom accretion and dynamic changes in the coastline. This has been the case since 2010 in Sopot, where the rapidly advancing tombolo is not only changing environmental relations but also threatening the health-spa character of the town by stopping the transport of sand along the coast. This paper analyses changes in seabed shape in the pier area in Sopot between 2010 and 2018. In the analysis, both archival maps and bathymetric surveys over a period of 8 years were used; based on these, numerical bottom models were developed and their geospatial changes were analyzed. The results showed that changes in the seabed in this area are progressing very quickly, despite periodic dredging actions organized by administrative bodies.

The coastline is the boundary between the water surface in a reservoir or watercourse and the land, which is characterised by high instability and functional diversity. For these reasons, research on coastal monitoring has been conducted for several decades. Currently, satellite images performed with synthetic aperture radars (SARs) are used to determine its course and variability together with high-resolution multispectral imagery from satellites such as IKONOS, QuickBird, and WorldView, or moderate-resolution multispectral images from Landsat satellites. This paper analysed the coastline variability in Sopot (2008–2018) based on Landsat satellite imagery. Furthermore, based on multispectral images obtained, it was determined how the beach surface in Sopot changed. Research has shown that the coastline keeps moving away from the land every year. This was particularly noticeable between 2008 and 2018 when the coastline moved on average 19.1 m towards the Baltic Sea. Moreover, it was observed that the area of the sandy beach in Sopot increased by 14 170.6 m2, which translates into an increase of 24.7% compared to 2008. The probable cause of the continuous coastline shift towards the sea and the increase of the beach surface is the oceanographic phenomenon called tombolo, which occurred in this area as a result of the construction of a yacht marina near the coast.

The human impact on the ecosystem has been particularly evident in the last century; it transforms the Earth’s surface on an unprecedented scale and brings about irreversible changes. One example is an oceanographic phenomenon known as a tombolo, i.e., a narrow belt connecting the mainland with an island lying near the shore formed as a result of sand and gravel being deposited by sea currents. The phenomenon contributes to an increase in the biogenic substance content in the littoral zone, which leads to increased cyanobacteria blooming in the summer period. Moreover, the debris accumulation in the littoral zone results in the mud formation, which makes the beach landscape less attractive. One of the main features of the tombolo phenomenon is its variability of shape, which includes the form of both the shore and the seabed adjacent to it. Therefore, to describe its size and spatio-temporal variability, it is necessary to apply methods for geodetic (the land) and hydrographic (the sea) measurements that can be carried out in different ways. The aim of the paper is to present the methodology for carrying out measurements of the tombolo oceanographic phenomenon using Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV) on the example of a waterbody adjacent to the Sopot pier. It also presents the results of surveys carried out in November 2019 within this area. The study demonstrated that the integration of two measuring devices whose development began in the second decade of the 20th century, i.e., UAVs and USVs, enables accurate (even up to several centimeters) and reliable determination of the scale and variability of the phenomena occurring in the littoral zone.

Autonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneuvers. This situation also arises in near-coastal areas, where shore structures like berths or moored vessels can be encountered. On the other hand, detection of coastal structures may also be helpful for berthing operations. An ASV can be launched and moored automatically only if it can detect obstacles in its vicinity. One commonly used method for target detection by ASVs involves the use of laser rangefinders. The main disadvantage of this approach is that such systems perform poorly in conditions with bad visibility, such as in fog or heavy rain. Therefore, alternative methods need to be sought. An innovative approach to this task is presented in this paper, which describes the use of automotive three-dimensional radar on a floating platform. The goal of the study was to assess target detection possibilities based on a comparison with photogrammetric images obtained by an unmanned aerial vehicle (UAV). The scenarios considered focused on analyzing the possibility of detecting shore structures like berths, wooden jetties, and small houses, as well as natural objects like trees or other kinds of vegetation. The recording from the radar was integrated into a single complex radar image of shore targets. It was then compared with an orthophotomap prepared from AUV camera pictures, as well as with a map based on traditional land surveys. The possibility and accuracy of detection for various types of shore structure were statistically assessed. The results show good potential for the proposed approach—in general, objects can be detected using the radar—although there is a need for development of further signal processing algorithms.

The study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need to study the phenomenon on a microscale, i.e., locally within small locations such as housing estates, parks, buildings, or even inside buildings. Therefore, there is an important need to measure light pollution at a lower level, at the low level of the skyline. In this paper, the authors present a new drone design for light pollution measurement. A completely new original design for an unmanned platform for light pollution measurement is presented, which is adapted to mount custom sensors (not originally designed to be mounted on a unmanned aerial vehicles) allowing registration in the nadir and zenith directions. The application and use of traditional photometric sensors in the new configuration, such as the spectrometer and the sky quality meter (SQM), is presented. A multispectral camera for nighttime measurements, a calibrated visible-light camera, is used. The results of the unmanned aerial vehicle (UAV) are generated products that allow the visualisation of multimodal photometric data together with the presence of a geographic coordinate system. This paper also presents the results from field experiments during which the light spectrum is measured with the installed sensors. As the results show, measurements at night, especially with multispectral cameras, allow the assessment of the spectrum emitted by street lamps, while the measurement of the sky quality depends on the flight height only up to a 10 m above ground level.

In modern digital photogrammetry, an image is usually registered via a digital matrix with an array of colour filters. From the registration of the image until feature points are detected on the image, the image is subjected to a series of calculations, i.e., demosaicing and conversion to greyscale, among others. These algorithms respond differently to the varying light spectrum of the scene, which consequently results in the feature location changing. In this study, the effect of scene illumination on the localisation of a feature in an image is presented. The demosaicing and greyscale conversion algorithms that produce the largest and smallest deviation of the feature from the reference point were assessed. Twelve different illumination settings from polychromatic light to monochromatic light were developed and performed, and five different demosaicing algorithms and five different methods of converting a colour image to greyscale were analysed. A total of 300 different cases were examined. As the study shows, the lowest deviation in the polychromatic light domain was achieved for light with a colour temperature of 5600 K and 5000 K, while in the monochromatic light domain, it was achieved for light with a green colour. Demosaicing methods have a significant effect on the localisation of a feature, and so the smallest feature deviation was achieved for smooth hue-type demosaicing, while for greyscale conversion, it was achieved for the mean type. Demosaicing and greyscale conversion methods for monochrome light had no effect. The article discusses the problem and concludes with recommendations and suggestions in the area of illuminating the scene with artificial light and the application of the algorithms, in order to achieve the highest accuracy using photogrammetric methods.

This paper addresses several important problems and methods related to studies of inland waters based on the existing scientific literature. The use of UAVs in freshwater monitoring is described, including recent contact and non-contact solutions. Due to a decline in biological diversity in many parts of the globe, the main threats are described together with a modern method for algae and cyanobacteria monitoring utilizing chlorophyll a fluorescence. Observed disturbances in the functioning of river biocenoses related to mine waters’ discharge, causing changes in the physico-chemical parameters of waters and sediments, give rise to the need to develop more accurate methods for the assessment of this phenomenon. Important problems occurring in the context of microplastic detection, including the lack of unification, standardization and repeatability of the methods used, were described. In conclusion, accurate results in the monitoring of water quality parameters of inland waters can be achieved by combining modern methods and using non-contact solutions.

In recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications [...]

One of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence on the quality of the photogrammetric study of a 3D urban mock-up. An important issue in this study was the measurement and evaluation of the artificial light sources used, based on illuminance (E), correlated colour temperature (CCT), colour rendering index (CRI) and Spectral power distribution (SPD) and the evaluation of the obtained point clouds (seven photogrammetric products of the same object, developed for seven different lighting conditions). The general values of the quality of the photogrammetric studies were compared. Additionally, we determined seventeen features concerning the group of tie-points in the vicinity of each F-point and the type of study. The acquired traits were related to the number of tie-points in the vicinity, their luminosities and spectral characteristics for each of the colours (red, green, blue). The dependencies between the identified features and the obtained XYZ total error were verified, and the possibility of detecting F-points depending on their luminosity was also analysed. The obtained results can be important in the process of developing a photogrammetric method of urban lighting monitoring or in selecting additional lighting for objects that are the subject of a short-range photogrammetric study.

Autonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications [...]

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.

Commercial unmanned aerial vehicles continue to gain popularity and their use for collecting image data and recording new phenomena is becoming more frequent. This study presents an effective method for measuring the concentration of fluorescent dyes (fluorescein and Rhodamine WT) for the purpose of providing a mathematical dispersion model. Image data obtained using a typical visible-light camera was used to measure the concentration of the dye floating on water. The reference measurement was taken using a laboratory fluorometer. The article presents the details of three extensive measurement sessions and presents elements of a newly developed method for measuring fluorescent tracer concentrations. The said method provides tracer concentration maps presented on the example of an orthophoto within a 2 × 2 m discrete grid.

The use of low-level photogrammetry is very broad, and studies in this field are conducted in many aspects. Most research and applications are based on image data acquired during the day, which seems natural and obvious. However, the authors of this paper draw attention to the potential and possible use of UAV photogrammetry during the darker time of the day. The potential of night-time images has not been yet widely recognized, since correct scenery lighting or lack of scenery light sources is an obvious issue. The authors have developed typical day- and night-time photogrammetric models. They have also presented an extensive analysis of the geometry, indicated which process element had the greatest impact on degrading night-time photogrammetric product, as well as which measurable factor directly correlated with image accuracy. The reduction in geometry during night-time tests was greatly impacted by the non-uniform distribution of GCPs within the study area. The calibration of non-metric cameras is sensitive to poor lighting conditions, which leads to the generation of a higher determination error for each intrinsic orientation and distortion parameter. As evidenced, uniformly illuminated photos can be used to construct a model with lower reprojection error, and each tie point exhibits greater precision. Furthermore, they have evaluated whether commercial photogrammetric software enabled reaching acceptable image quality and whether the digital camera type impacted interpretative quality. The research paper is concluded with an extended discussion, conclusions, and recommendation on night-time studies.

The continuous and intensive development of measurement technologies for reality modelling with appropriate data processing algorithms is currently being observed. The most popular methods include remote sensing techniques based on reflected-light digital cameras, and on active methods in which the device emits a beam. This research paper presents the process of data integration from terrestrial laser scanning (TLS) and image data from an unmanned aerial vehicle (UAV) that was aimed at the spatial mapping of a complicated steel structure, and a new automatic structure extraction method. We proposed an innovative method to minimize the data size and automatically extract a set of points (in the form of structural elements) that is vital from the perspective of engineering and comparative analyses. The outcome of the research was a complete technology for the acquisition of precise information with regard to complex and high steel structures. The developed technology includes such elements as a data integration method, a redundant data elimination method, integrated photogrammetric data filtration and a new adaptive method of structure edge extraction. In order to extract significant geometric structures, a new automatic and adaptive algorithm for edge extraction from a random point cloud was developed and presented herein. The proposed algorithm was tested using real measurement data. The developed algorithm is able to realistically reduce the amount of redundant data and correctly extract stable edges representing the geometric structures of a studied object without losing important data and information. The new algorithm automatically self-adapts to the received data. It does not require any pre-setting or initial parameters. The detection threshold is also adaptively selected based on the acquired data.

The visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases rapidly together with an increasing blur kernel. The nature of blur can be non-uniform, which makes it hard to forecast for traditional deblurring methods. Due to the above, the author of this publication concluded that the neural methods developed in recent years were able to eliminate blur on UAV images with an unpredictable or highly variable blur nature. In this research, a new, rapid method based on generative adversarial networks (GANs) was applied for deblurring. A data set for neural network training was developed based on real aerial images collected over the last few years. More than 20 full sets of photogrammetric products were developed, including point clouds, orthoimages and digital surface models. The sets were generated from both blurred and deblurred images using the presented method. The results presented in the publication show that the method for improving blurred photo quality significantly contributed to an improvement in the general quality of typical photogrammetric products. The geometric accuracy of the products generated from deblurred photos was maintained despite the rising blur kernel. The quality of textures and input photos was increased. This research proves that the developed method based on neural networks can be used for deblur, even in highly blurred images, and it significantly increases the final geometric quality of the photogrammetric products. In practical cases, it will be possible to implement an additional feature in the photogrammetric software, which will eliminate unwanted blur and allow one to use almost all blurred images in the modelling process.

The main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of intense human activity, they should be constantly monitored. In 2018 and 2019, several measurement campaigns took place in the littoral zone in Sopot, related to the intensive uplift of the seabed and beach caused by the tombolo phenomenon. In this research, a unique combination of bathymetric data obtained from an unmanned surface vessel, photogrammetric data obtained from unmanned aerial vehicles and ground laser scanning were used, along with geodetic data from precision measurements with receivers of global satellite navigation systems. This paper comprehensively presents photogrammetric measurements made from unmanned aerial vehicles during these campaigns. It describes in detail the problems in reconstruction within the water areas, analyses the accuracy of various photogrammetric measurement techniques, proposes a statistical method of data filtration and presents the changes that occurred within the studies area. The work ends with an interpretation of the causes of changes in the land part of the littoral zone and a summary of the obtained results.

Unmanned aerial vehicles (UAVs) have now become very popular in photogrammetric and remote-sensing applications. Every day, these vehicles are used in new applications, new terrains, and new tasks, facing new problems. One of these problems is connected with flight altitude and the determined ground sample distance in a specific area, especially within cities and industrial and construction areas. The problem is that a safe flight altitude and camera parameters do not meet the required or demanded ground sampling distance or the geometrical and texture quality. In the cases where the flight level cannot be reduced and there is no technical ability to change the UAV camera or lens, the author proposes the use of a super-resolution algorithm for enhancing images acquired by UAVs and, consequently, increase the geometrical and interpretation quality of the final photogrammetric product. The main study objective was to utilize super-resolution (SR) algorithms to improve the geometric and interpretative quality of the final photogrammetric product, assess its impact on the accuracy of the photogrammetric processing and on the traditional digital photogrammetry workflow. The research concept assumes a comparative analysis of photogrammetric products obtained on the basis of data collected from small, commercial UAVs and products obtained from the same data but additionally processed by the super-resolution algorithm. As the study concludes, the photogrammetric products that are created as a result of the algorithms’ operation on high-altitude images show a comparable quality to the reference products from low altitudes and, in some cases, even improve their quality.

A new trend in recent years for hydrographic measurement in water bodies is the use of unmanned surface vehicles (USVs). In the process of navigation by USVs, it is particularly important to control position precisely on the measuring profile. Precise navigation with respect to the measuring profile avoids registration of redundant data and thus saves time and survey costs. This article addresses the issue of precise navigation of the hydrographic unit on the measuring profile with the use of a nonlinear adaptive autopilot. The results of experiments concerning hydrographic measurements performed in real conditions using an USV are discussed.

The paper addresses the fields of combined close-range photogrammetry and terrestrial laser scanning in the light of ship modelling. The authors pointed out precision and measurement accuracy due to their possible complex application for ship hulls inventories. Due to prescribed vitality of every ship structure, it is crucial to prepare documentation to support the vessel processes. The presented methods are directed, combined photogrammetric techniques in ship hull inventory due to submarines. The class of photogrammetry techniques based on high quality photos are supposed to be relevant techniques of the inventories’ purpose. An innovative approach combines these methods with Terrestrial Laser Scanning. The process stages of data acquisition, post-processing, and result analysis are presented and discussed due to market requirements. Advantages and disadvantages of the applied methods are presented.