Development of Low-Cost Ground Control System for UAV-Based Mapping

<p>Detailed information on rock formations and assessment of their geological structures, such as joints, faults, shears and bedding planes, are required for evaluation of rock integrity and stability. Our research demonstrates a comprehensive approach for producing high spatial resolution 3D information of rock formations from unmanned aerial vehicle (UAV) imagery for rock joint identification, and presents an innovative technique for using Terrestrial Laser Scanning (TLS) data to derive ground control points (GCPs) for geo-referencing of UAV imagery of vertical rock walls. UAV imagery was collected from a freestanding 90 m tall rock formation with a 3.5 km perimeter, via oblique rock façade scans and also at-nadir, covering a ground and rock facade area of approximately 0.32 and 0.25 km<sup>2</sup>, respectively. Seventy-two GCPs were distributed around the rock for geo-referencing of the UAV imagery. As GCPs could not be deployed on vertical rock walls, a TLS system was used for identification of 93 distinct natural features as pseudo-GCPs on the rock walls. Forty scans were collected and geo-referenced from triplets of GCPs placed on the ground near the TLS system for each scan. A Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) survey was performed on the GCPs, using a base station and a rover. Continuously Operating Reference Stations (CORS) data were used to fix the position of the base station and improve the absolute geometric position to an average and lowest accuracy of 3.3 and 18.6 mm for 177 GCPs. A total of 44 façade scans, as well as 14 low and 5 high altitude nadir-viewing UAV flights, were undertaken with a Zenmuse X3 RGB camera mounted to a DJI Matrice 100 platform, resulting in a collection of nearly 17,000 photos. The five high altitude flights were designed to include a larger area around the rock to incorporate additional GCPs, while the low altitude flights were to increase the spatial resolution of the imaged rock. Flight planning was undertaken with the Universal Ground Control Station Client application. Façade scans were flown horizontally and parallel to the rock walls at a distance of 20-30 m and at heights between 10-80 m with sidelaps >70% between horizontal flight lines and >80% forward overlap along flight lines. Façade scans were collected with a 4° viewing angle to ensure the base of the rock was included. The Agisoft MetaShape software was initially used to generate a sparse point cloud using all façade scans and nadir-viewing imagery. Geo-referencing of the UAV imagery was based on 136 GCPs, which produced an accuracy of 0.1558 m, with an addition 100 control points kept aside for independent evaluation, yielding an accuracy of 0.2018 m. Subsequent image processing was split into 14 evenly sized “chunks” to enable more efficient processing of a dense point cloud (4.33 billion points) and 3D model (mesh with 129.5 million faces and texture layer) for the entire area. The produced 3D model was found suitable for identification of rock joints larger than 1 m in length.</p>

Abstract. Utilizing ground control points (GCPs) to georeference photogrammetry-based point cloud data is a common practice in unmanned aerial system (UAS) mapping. Direct georeferencing or integrated sensor orientation (ISO) can be used to obtain georeferenced point clouds from UAS without relying heavily on GCPs. However, the accuracy of the point cloud may be impacted by the accuracy of the trajectory solution obtained by GNSS. To improve point cloud accuracy, post-processing kinematic (PPK) solutions can be applied to the UAS trajectory, which may provide higher accuracy than low-accuracy trajectory solutions and minimize the reliance on GCPs. This study compares the accuracy and precision of two different point clouds generated using different methods. One point cloud was generated using traditional photogrammetric methods with low accuracy Global Navigation Satellite System (GNSS) observations from the UAS and GCPs that have an average accuracy of one to two centimeters, while the other was generated using PPK trajectory solution for the UAS’s trajectory with two software: open-source Emlid Studio and the widely used Inertial Explorer. The use of PPK techniques in UAS mapping may have several potential benefits over traditional methods. By correcting the errors in the UAS's trajectory, a user may only need to depend on fewer ground control points, which can reduce the time and cost associated with fieldwork. This is particularly useful in areas that are difficult to access or have limited ground control point options, such as in urban or forested areas. To evaluate performance, a GNSS receiver is used to obtain measurements on checkpoints, which are used to assess the accuracies of the point clouds. In our experiments, the accuracy of the point clouds generated using PPK trajectory solution with high accuracy GCPs was found to be higher than those generated with low accuracy GNSS observations while aided with high accuracy ground control points. While the use of PPK with GCPs is generally expected to provide more accurate and reliable data than low-accuracy GNSS observations even after adjusting with GCPs, the number and distribution of GCPs can still significantly impact overall accuracy. Therefore, careful consideration of the number of GCPs and their placement is essential to achieve the desired level of efficiency and effectiveness in UAS mapping.

Global Navigation Satellite Systems (GNSS) at the time of writing comprise four systems, two of which are fully operational and two of which are on their way (see Table 1.1). A brief history of GNSS is given in Chapter 10 along with a timeline of application development and prospects for this development, especially concerning mobile applications. Each GNSS comprises a constellation of satellites, called a space segment, and a ground segment (Figure 1.1). The main idea behind GNSS is to measure distances between a satellite and a user located on the surface of the Earth or in a lower atmosphere. Satellite coordinates can be calculated at any moment of time. The information that allows the calculation of satellite position is uploaded to and then broadcast from satellites to the user. The ground segment is responsible for determining satellite orbits, which it then uploads to the satellites, and also for defining the coordinate frame and time frame in which satellite and user positions are estimated. Having received the information on satellite orbits and measured distances to the satellites, a user can calculate receiver position as an intersection of four spheres in a four-dimensional space-time continuum. If the receiver clock is perfectly synchronized with the satellite time frame, only three satellites would be required to determine receiver position in three-dimensional space (Figure 1.2).

Uncrewed aircraft systems (UASs) and structure-from-motion/multi-view stereo (SfM/MVS) photogrammetry are efficient methods for mapping terrain at local geographic scales. Traditionally, indirect georeferencing using ground control points (GCPs) is used to georeference the UAS image locations before further processing in SfM software. However, this is a tedious practice and unsuitable for surveying remote or inaccessible areas. Direct georeferencing is a plausible alternative that requires no GCPs. It relies on global navigation satellite system (GNSS) technology to georeference the UAS image locations. This research combined field experiments and simulation to investigate GNSS-based post-processed kinematic (PPK) as a means to eliminate or reduce reliance on GCPs for shoreline mapping and charting. The study also conducted a brief comparison of real-time network (RTN) and precise point positioning (PPP) performances for the same purpose. Ancillary experiments evaluated the effects of PPK base station distance and GNSS sample rate on the accuracy of derived 3D point clouds and digital elevation models (DEMs). Vertical root mean square errors (RMSEz), scaled to the 95% confidence interval using an assumption of normally-distributed errors, were desired to be within 0.5 m to satisfy National Oceanic and Atmospheric Administration (NOAA) requirements for nautical charting. Simulations used a Monte Carlo approach and empirical tests to examine the influence of GNSS performance on the quality of derived 3D point clouds. RTN and PPK results consistently yielded RMSEz values within 10 cm, thus satisfying NOAA requirements for nautical charting. PPP did not meet the accuracy requirements but showed promising results that prompt further investigation. PPK experiments using higher GNSS sample rates did not always provide the best accuracies. GNSS performance and model accuracies were enhanced when using base stations located within 30 km of the survey site. Results without using GCPs observed a direct relationship between point cloud accuracy and GNSS performance, with R2 values reaching up to 0.97.

In sport science, Global Navigation Satellite Systems (GNSS) are frequently applied to capture athletes' position, velocity and acceleration. Application of GNSS includes a large range of different GNSS technologies and methods. To date no study has comprehensively compared the different GNSS methods applied. Therefore, the aim of the current study was to investigate the effect of differential and non-differential solutions, different satellite systems and different GNSS signal frequencies on position accuracy. Twelve alpine ski racers were equipped with high-end GNSS devices while performing runs on a giant slalom course. The skiers' GNSS antenna positions were calculated in three satellite signal obstruction conditions using five different GNSS methods. The GNSS antenna positions were compared to a video-based photogrammetric reference system over one turn and against the most valid GNSS method over the entire run. Furthermore, the time for acquisitioning differential GNSS solutions was assessed for four differential methods. The only GNSS method that consistently yielded sub-decimetre position accuracy in typical alpine skiing conditions was a differential method using American (GPS) and Russian (GLONASS) satellite systems and the satellite signal frequencies L1 and L2. Under conditions of minimal satellite signal obstruction, valid results were also achieved when either the satellite system GLONASS or the frequency L2 was dropped from the best configuration. All other methods failed to fulfill the accuracy requirements needed to detect relevant differences in the kinematics of alpine skiers, even in conditions favorable for GNSS measurements. The methods with good positioning accuracy had also the shortest times to compute differential solutions. This paper highlights the importance to choose appropriate methods to meet the accuracy requirements for sport applications.

It is well known that the presence of unintentional or intentional Radio Frequency Interference (RFI) signals in the Global Navigation Satellite Systems (GNSS) frequency bands can cause severe positioning performance degradation and even a complete service unavailability. Moreover, with the development of Software Defined Radio (SDR) GNSS signal generators and the popularization of low-cost SDR front-ends, the spoofing of the GNSS civil service turns out to be a real threat for GNSS receivers. Complementary to time and frequency-domain mit-igation techniques, antenna-array based receivers can benefit from spatial domain processing. An antenna array receiver can also discriminate between legitimate GNSS signals from these being broadcasted by the spoofer. In this work, we present an evolution of a receiver-independent GNSS smart antenna architecture for a real-time, automatic and autonomous, simultaneous anti-jamming and anti-spoofing spatial filtering for GNSS bands. The novel spoofer detection and mitigation algorithm is able to detect the spoofer and protect the receiver even in a scenario where the spoofer is transmitted in combination with a strong jammer to force the receiver to lose the legitimate GNSS signal lock. A prototype is also presented, implemented using Commercial Off The Shelf (COTS) components. The proposed smart antenna can be connected to any conventional single-antenna GNSS receiver. The paper includes both the theory of operation, the implementation details and its performance analysis in an extended measurement campaign.

Unmanned aerial vehicle (UAV) photogrammetry is a technology used to create highly accurate maps, and the real-time kinematic (RTK) global navigation satellite system (GNSS) network has been implemented by several organizations to support their missions.Recent advancements in computer vision have driven progress in photogrammetry, alongside the development of more accessible UAVs equipped with GNSS technology.This paper evaluates the accuracy of UAV imagery and processing using ground control points (GCPs) with coordinates from the Thailand RTK GNSS network.The study area is located on the Sathing-Phra Peninsula in Songkhla Province, southern Thailand, covering approximately 174 hectares with a total of 660 images.The average ground sampling distance (GSD) was around 4.35 cm.The processed photogrammetry system used 8 GCPs via the GNSS RTK network, and results were compared with 25 checkpoints from a static survey.The UAV photogrammetry results showed a horizontal accuracy for orthomosaics and vertical accuracy for the digital surface model (DSM), with CE 95 values of 6.99 cm and 12.44 cm, respectively, as per the NSSDA standard.These results comply with the Thailand UAV Surveying for Engineering (TUSE) standards.According to the 2014 American Society for Photogrammetry and Remote Sensing (ASPRS) standards, horizontal accuracy class I and vertical accuracy class II should be applied.The map scale factor (MSF) standard was 1:160, with a contour interval of 20 cm.Additionally, the orthomosaic DSM can be imported into open-source programs for use in a web GIS online system, enabling local agencies to retrieve and utilize the data.

Abstract. Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability.

Developing an image processing pipeline to improve the position accuracy of single UAV images

Unmanned Aerial Vehicles (UAVs) have been used for accurate orthophoto generation based on advanced Global Navigation Satellite System (GNSS) techniques. In recent years, the UAV systems have become an effective tool for fast monitoring of damages caused by disasters such as the earthquake hazards. The conventional orthophoto generation based on ground control points takes too much time during emergency situations. In the study, different methodologies for the processing of the acquired GNSS Positioning data for direct georeferencing of UAVs were investigated in terms of various orbit products. Evaluating the fitness for emergency response applications, the ground control points (GCPs) also used for validation of the generated orthophoto without using GCPs and based on Precise Point Positioning (PPP) approach. In this study, Ultra-Rapid, Rapid and Final PPP methods based on GNSS observations were used for direct geo-referencing. Thirteen GCPs were located at the study area for the validation of the orthophoto accuracy generated by direct geo-referencing.

Safety as the key quality property among RAMS (reliability, availability, maintainability, and safety) demonstrates the most stringent performance in correspondence with the safety requirements and performance standards like EN 50126. Meanwhile, GNSS (Global Navigation Satellite Systems) are penetrating the railway now widely in non-safety related applications as passenger information, fleet management, etc. GNSS also have great potential for safety-related applications in railway such as the train location determination function, which the safety performance needs to be assured through hazard analysis and risk assessment process. The train location determination by satellite-based localization system is elevating the train control to the next level. The European Train Control System (ETCS) has being trying to implementing Level 3, the Chinese Train Control System (CTCS) has been implementing CTCS Level 3 low cost especially for secondary lines, and the U.S. is implementing train control systems under Positive Train Control (PTC) requirements. The train control system needs GNSS to provide more accurate location information of trains, more flexible and condensed trains on tracks with the consistency of still keeping the current safety level or even improve safety. Some researchers are trying to understand the performance of GNSS (GPS / EGNOS / Beidou) for railway applications from the fundamental accuracy level. A satellite-based train localization unit (SaLuT) as the entity to perform the train location determination function is to bring the GNSS accuracy evaluation up to safety integrity according to the safety requirements and standards for risk assessment. One of the key consequential result derived from the train location is the adequate safety margin. The safety margin, which can also be called as “safe braking distance”, is a margin indicated to rail traffic that would allow the train to stop with the application of normal service braking. The safety margin estimation quality and the risk of the safety margin shows the hazard rate for the safety margin estimation function performed by the designed localization unit SaLuT. This paper discusses the safety margin estimation method considering both GNSS accuracy and integrity assessment aspects of SaLuT, in accordance of the settled safety requirements of location determination function. To analyze the hazard of the safety margin estimation, a formal method is applied to model the SaLuT behavior and functions. The formal method based on stochastic Petri net enables the modeling process to include the GNSS receiver collected real data on the test track into it. The safety margin estimation method together with the risk assessment method using the real data can generate quantitative indicators to represent the localization function and safety margin estimation quality. The data used for the analysis is collected in the Qinghai-Tibet railway line from Golmud station to Ganlong station by SaLuT installed on a locomotive along the track. With the stochastic Petri net model and the systematic equation using the real collected data to estimate the safety margin based on the GNSS technologies, the SaLuT can be validated and verified for its hazard rates, which provides information for the safety cases in order to meet the industrial normative requirements.

Thanks to their flexibility and availability at reduced costs, Unmanned Aerial Vehicles (UAVs) have been recently used on a wide range of applications and conditions. Among these, they can play an important role in monitoring critical events (e.g., disaster monitoring) when the presence of humans close to the scene shall be avoided for safety reasons, in precision farming and surveying. Despite the very large number of possible applications, their usage is mainly limited by the availability of the Global Navigation Satellite System (GNSS) in the considered environment: indeed, GNSS is of fundamental importance in order to reduce positioning error derived by the drift of (low-cost) Micro-Electro-Mechanical Systems (MEMS) internal sensors. In order to make the usage of UAVs possible even in critical environments (when GNSS is not available or not reliable, e.g., close to mountains or in city centers, close to high buildings), this paper considers the use of a low cost Ultra Wide-Band (UWB) system as the positioning method. Furthermore, assuming the use of a calibrated camera, UWB positioning is exploited to achieve metric reconstruction on a local coordinate system. Once the georeferenced position of at least three points (e.g., positions of three UWB devices) is known, then georeferencing can be obtained, as well. The proposed approach is validated on a specific case study, the reconstruction of the façade of a university building. Average error on 90 check points distributed over the building façade, obtained by georeferencing by means of the georeferenced positions of four UWB devices at fixed positions, is 0.29 m. For comparison, the average error obtained by using four ground control points is 0.18 m.

Reforestation areas undergo rapid and continuous changes in vegetation structure, posing challenges for accurate and cost-effective monitoring. Here, we evaluate the accuracy of the geometric registration of orthomosaic images and digital elevation models using co-alignment, which does not rely on Ground Control Points or the Global Navigation Satellite System, to facilitate time-series analysis of the reforestation area. Three alignment methods – individual alignment (Ind), co-alignment among all epochs together (CA_All), and co-alignment between two epochs (CA_1on1) – were compared. The results show that both co-alignment methods significantly reduce horizontal and vertical relative errors compared to individually aligned images. This approach achieves geometric registration with horizontal accuracy within 0.05 m, whereas the vertical accuracy reaches approximately 0.1 m. When flight conditions and intervals differ markedly, the number of inter-epoch tie points decreases, occasionally leading to meter-scale misalignments. However, connecting more than two epochs reduces these errors and maintains accuracy sufficient for continuous monitoring. These findings suggest that co-alignment, combined with only one accurately georeferenced reference epoch, is highly effective for frequent and detailed forest monitoring. By leveraging a minimal subset of stable features (e.g. logging residues), multi-epoch unmanned aerial vehicle imagery can be seamlessly integrated, providing substantial cost and labor savings over traditional ground-control approaches. This paper presents an easy method for applying time-series analysis to early-stage forest management, with the potential to enable fine-scale detection of growth and changes in spatially complex and rapidly transforming landscapes in the future.

Large Scale Topographic Mapping Using Stereo Pair Imagery from CAS500-1 Satellite

Global navigation satellite systems (GNSS) historically been known as one of the newest technologies since the 1970s.GNSS originally developed for military purposes in the USA (GPS -Global Position System).There are several satellite systems in the world.Satellites, International Research Base Stations, regional/national and local base stations form a permanent geodetic frame.Research on the size and shape of the Earth-planet, climate, sea, urban planning.In geodesy, a network of global positioning base stations makes it possible to assess the movements of continents, land plates at international level.GNSS is an important technology in navigation, logistics, economics, land surveying and other "geo" sectors.GNSS equipment/receivers and their manufacturers are applying new designs and electronics.Initially, GNSS instruments were used with single frequency signal reception, later expanding the number of GNSS signal channels to two frequencies.Such technological improvements nowadays improve the certainty, reliability and accuracythe overall quality of GNSS measurements.The GNSS base station enables the surveyors to determine coordinates with an accuracy of two centimeters in real time (RTK) and with an accuracy of five millimeters using the accumulated post-processing data.Various types of factors hamper GNSS measurements.The GNSS signal (radio wave) travels in airspace, in urban environments and is a physical parameter.Any obstacletree, building walls, and atmospheric effectmakes GNSS measurements less accurate.The GNSS signal must be strong and free from attenuation and suppression effects.This study develops GNSS models that show the comparison, certainty and reliability of GNSS measurements using different types of GNSS techniques.Evaluation of Latvian Global Positioning Reference Station Network -LatPos system measurements against a corresponding RTK solution method using Latvian Global Positioning Network geodetic point (G2 class).