Hassan Emami; Seyyed Ghasem Rostami
Abstract
Extended Abstract
Introduction
Unmanned Aerial System (UAS) photogrammetry now provides a low-cost, fast, and effective approach to real-time acquisition of high resolution and digital geospatial information, as well as automatic 3D modeling of objects, for a variety of applications including topographical ...
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Extended Abstract
Introduction
Unmanned Aerial System (UAS) photogrammetry now provides a low-cost, fast, and effective approach to real-time acquisition of high resolution and digital geospatial information, as well as automatic 3D modeling of objects, for a variety of applications including topographical mapping, 3D city modelling, orthophoto generation, and cultural heritage preservation. UASs are known by a variety of names and acronyms, including aerial robots or simply drones, with UAV and drone being the most commonly used terminology. Because of the versatility of their on-board Global Navigation Satellite System (GNSS) navigation systems and inertial measurement unit (IMU) sensors, UASs open up new options for photogrammetric projects. In this research, the ability of four different state-of-the-art and professional drone-based software packages, including AgisoftMetashape, InphoUASmaster, Photomodeler UAS, and Pix4D Mapper, to generate a high density point cloud as well as a Digital Surface Model (DSM) and true orthoimage over barren, residential, green space, and uniform textured areas in urban and exurban areas is investigated.
Methodology
The following are the major processes in this study: image acquisition, point cloud, DSM, DEM generation, and accuracy assessment. Data planning and acquisition are the initial steps in commencing any project. The overlapping images are initially obtained using four data sets with distinct surface feature attributes and camera kinds with different shooting situations. The data sets that must be acquired include pictures taken with FC6310 (8.8 mm), NEX-5R (5.2 mm), and Canon IXUS 220HS (4.3 mm) cameras at varied flight heights and spatial resolutions ranging from 52 to 246 m. The four data sets, two of which are connected to Iran and two of which are related to other nations, were chosen from barren, residential, green space, and uniform texture areas. GPS coordinates for these photos must also be recorded using a GPS device. This is done to geo-reference the images for improved model accuracy. The calibration of the camera must also be addressed, and its characteristics and readings must be determined at the start of the project. The images will be calibrated first in order to determine camera pose estimate. The following stage is to compare survey measurements to model measurements in order to assess the overall correctness of the 3D model. The correctness of the point cloud, DSM, and 3D textured model is next evaluated. The accuracy evaluation evaluates the orientation correctness, and measurement uncertainties in the various modeling procedures. Finally, the various products of the mentioned software packages were statistically and qualitatively evaluated.
Results and discussion
The outcomes of this study demonstrate the ability of commercial photogrammetric software packages to do automatic 3D reconstruction of numerous attributes across urban and exurban regions using high quality aerial imagery. This assessment employs a variety of visual and geometric measurements to assess the quality of produced point clouds as well as the performance of the four software packages. According to the visual quality findings, AgisMesh software performs better in 3D modeling of all varieties of surfaces in all locations, but badly in the reconstruction of building edges in urban regions. Pix4D software, on the other hand, performs poorly in areas with uniform texture but excels at recognizing height changes and reconstructing building site boundaries. In terms of visual outcomes, the other software falls somewhere in the middle. In quantitative tests, they were tested first with checkpoints and then with randomly selected points in three distinct classes of urban and exurban regions. Check point findings revealed that the root mean square error (RMSE) in AgisMesh, UASmas, Pix4D, and PhUAS software packages was 2.82, 2.63, 5.84, and 3.03 cm, respectively. Furthermore, quantitative findings obtained by choosing random locations revealed that UASmas had an accuracy of 1.83, 1.20, and 2.74 cm, respectively, in three residential, barren, and green space zones. In addition to the 6.90, 2.96, and 7.24 cm accuracy of the PhUAS, the Pix4D was 4.72, 3.46, and 3.59 cm more accurate than AgisMesh software in the three stated classes. Table 1 displays the assessment findings based on the RMSE criterion.
Conclusions
The findings of this study indicate the capacity of specialist drone-based photogrammetric software packages to automatically reconstruct 3D features from high quality aerial images over desolate, residential, green space, and uniform texture environments. In this study, all conditions and parameters in all software were regarded the same, and owing to the similarity of statistical parameters, number of points, and so on in various products, only the discrepancies and their differences were discussed in depth. Various visual and geometric parameters are utilized in this evaluation to analyze the quality of generated 3D point clouds, DSM, and true orthophoto. AgisMesh offers a simple and easy user interface in general and visual assessment, and it is possible to describe and execute data from any camera, even unknown models, without utilizing coordinate images by utilizing powerful processing methods. In contrast, the UASmas program has a highly complex user interface, and the user must be familiar with all of the concepts of photogrammetry as well as the camera parameters file, which is not readily set. It is possible to manually alter restricted processing results in Pix4D. As a result, faulty results are not obtained in regions with the same texture, while production points in other areas are of poor quality. When compared to the other three applications, PhUAS fared poorly aesthetically and geometrically. The user must enter many parameters or thresholds in the processing phases. Therefore, the user must be sufficiently informed of the specifics of photogrammetric and machine vision algorithms to understand that the quality of software output is largely reliant on these factors. Furthermore, check point findings revealed that theRMSE in AgisMesh, UASmas, Pix4D, and PhUAS software packages was 2.82, 2.63, 5.84, and 3.03 cm, respectively. Furthermore, quantitative findings obtained by picking random points revealed that UASmas has an accuracy of 3.51 cm, PhUAS has 10.45 cm, and Pix4D was 6.87 cm more accurate than AgisMesh in three residential, barren, and green space regions. Taking into account all of the benefits and evaluations of visual and geometric correctness, the performance and accuracy of AgisMesh, UASmas, Pix4D, and PhUAS may be ranked from one to four, accordingly.
Amir Hosein Shokri; Saied Sadeghian
Abstract
Introduction Recently, cadastre has become a suitable platform for global partnership in management of land and its assets. Due to ever- increasing population, spatial organization of citiesis considered to be one of the most important issues in national development planning. This indicates the necessity ...
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Introduction Recently, cadastre has become a suitable platform for global partnership in management of land and its assets. Due to ever- increasing population, spatial organization of citiesis considered to be one of the most important issues in national development planning. This indicates the necessity of using 3D land information systems since theenvironment, quality, ownership and other benefits of lands do not only change horizontallyany moreand height is also a decisive and vital factor.Therefore, 3D cadastreis used as abasis for integrating information into a complete and efficient information storage system. This system is usedtomanage scarce land resources and plays a key role in achieving future legal and managerial success in the field ofreal-estate. Designing and implementing a system capable of displaying the third dimension (height) is very complex. Common methods of producing 3D cadastral models include land surveying, classical aerial photogrammetry, high-resolution satellite imagery, and so on. Recently, the advent of drones has provided a suitable platform for large-scale cadastral mapping. Collecting high resolution images, processing withstructure from motion(SFM) method, multi-stereo vision (MSV), and dense 3D point cloud with a high resolution of about a few centimeters are the main advantages of these tools. Recentstudies in this field indicate high capabilities of UAV-based photogrammetry method for the production and updating of cadastral maps. Materials and Methods Due to the applied nature of the present study, guideline for the spatial information production using photogrammetric method published by Tehran Municipality and other Surveying and Mapping guidelines published by the National Cartographic Center of Iran have been used to produce 3D cadastral modeland reach relatively real results. The study area is Khosban village in MiyanTaleqan rural district, in the central district of Taleqan County, Alborz Province, Iran. Necessary information was collected using an eBee Plus survey drone with a SODA camera (designed for professional photogrammetric applications). Besides, exterior orientation parameters were measured using the preciseinertial measurement unit (IMU), global navigation satellite system (GNSS) Antenna withreal-time kinematic (RTK) and post-processing kinematic (PPK) techniques and triangulation was performed using these parameters. To increase the accuracy, reduce hidden areas and achieve more accurate 3D models, 75%longitudinal and transverse overlappingwere considered for the images. Image processing was performed using Pix4dmapper and Metashape software and products such as orthomosaic, dense 3D point cloud, and digital surface model were produced. To prove thegeometric accuracy of triangulation, 8 ground control points were used, and32 checkpoints were also used for the final evaluation of 3D models. Results and Discussion 3D cadastre implementation was performedin the present paperusing UAV based photogrammetry without any ground control points. According to the results of triangulation, the maximum root mean square error in the X-component was reported 3.21 cm, the Y-componentwas reported2.86 cm, and the Z-component was reported 3.96 cm using Pix4dmapper and Metashape software. Moreover, 32 sample checkpoints were used for the final evaluation of the 3D models and data collected from these points were compared with the reference data. Results indicated the occurrence of maximum root mean square error in the horizontal components (X, Y) of 0.2 and 0.21 meter respectively, and 0.27 meter in the height component (Z). A correlation coefficient of about 1 represents high geometric accuracy of the 3D models produced using UAV based photogrammetry. Conclusion 3D cadastre can be used as a tool for improving land management and related issues. Due to structural complexity and ownership issues,most developed countrieshave not yet fully implemented 3D cadastre. However, these countries are always looking for ways to achieve such a system. So far in our country, the issue of 3D cadaster has only been pursued in academic studies and no practical stephas been taken to implement this system. Unfortunately, technical dimension and preparation of 3D models are only a part of 3d cadastre and legal issues occurring due to insufficient understanding of the third dimensionand its complexity alsolead to failure in the implementation of 3D cadaster.
Sara Karami; Mohammad Taleai
Abstract
Extended Abstract Introduction Road signs not only provide drivers with the necessary information and guidance, but also inform them of related rules and probable risks along roads. Safety of roads, and thus minimum delay and discomfort for drivers depends on traffic order. This order is only achieved ...
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Extended Abstract Introduction Road signs not only provide drivers with the necessary information and guidance, but also inform them of related rules and probable risks along roads. Safety of roads, and thus minimum delay and discomfort for drivers depends on traffic order. This order is only achieved if road signs can accurately guide drivers. Design of road signs have been evaluated in different fields of traffic engineering and urban design. Based on these evaluations, parameters like proper distance (distance in which a sign is legible for those driving in different speeds), and proper height (the height in which light reflection from the surface of the sign is minimized) have been introduced. Lack of a generalized method for designing and positioning of road signs, along with inadequate attention to their proper installation can cause a serious risk for drivers. Systematic positioning of road signs on highways and urban pathways with an especial attention to different criteria of sights has a significant impact on drivers’ ability to find the best route on time, and thus minimizes probable confusion and heavy traffic. Visibility in three-dimensional space refers to three-dimensional characteristic of different barriers along the roads. In most analytical studies, extruded objects and a perspective of the three-dimensional model are simulated. In this approach, three-dimensional analysis is usually performed based on an analysis in two-dimensional space. As an instance, the concept of spatial openness index (SOI) was introduced in 3D space. This concept refers to the volume of space observable for an observer. SOI is measured by defining a cone in the observers’ position based on which simulation is performed. In this way, the volume of observable space will be reduced in the presence of obstacles. 3D visibility analysis is closely related to human perception. When human eyes observe a scene, distant objects appear smaller than closer ones. Thus, if this difference in distance is considered, the final simulation will be closer to reality. Distance index shows the space width scale by calculating the distance between the observer and the target. In this method, a decrease in distance results in a more comprehensive perception, while increased distance decreases observers’ ability to perceive the environment. Based on the distance to target and observer’s view angle, three-dimensional projection simulates observers’ view and illustrates 3D obstacles on a 2D plane. The present study seeks to provide an approach based on spatial analysis in 3D space to evaluate the visibility of road signs. Materials & Methods Indices like height and direction of road signs, perceivable distance and horizontal angle between signs and the observer (driver), and finally perceivable area of the signs effect the visibility of signs. In the proposed method, total area of each sign perceivable for drivers driving in different situations is calculated using projective geometry. In order to evaluate visibility of road signs for vehicles (driver) in different positions, spatial indices such as overlap area (area resulted from the reflection of barriers on the sign face), distance between the center of road signs and the center of overlap area, and a combination of overlap area and distance are presented. Then, different simulation scenarios are designed for the vehicle’s motion on a simulated roadway and the performance of each indicator are evaluated. Index of combination (combination of overlap area and distance) was selected as final visibility measure. With an increase in distance from the center of the sign, the overlap area decreases and visibility increases. In order to determine visibility, visual status of the vehicle (driver) is evaluated based on four categories: poor, good, medium and excellent. Results & Discussion In order to simulate drivers’ vision, model spatial objects along the route and find optimal position for road signs, an appropriate analytical model is required. Results indicate that the proposed method can be used as an appropriate tool for optimal positioning of road signs along a route.
Amir Shahrokh Amini
Abstract
Facilitation and automation of the process of visual and geometric reconstruction is one of the issues considered in 3D modeling of environment, especially in urban areas. Since the positions of the lenses of a stereo camera are fixed relative to each other, it can be used to facilitate the modeling ...
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Facilitation and automation of the process of visual and geometric reconstruction is one of the issues considered in 3D modeling of environment, especially in urban areas. Since the positions of the lenses of a stereo camera are fixed relative to each other, it can be used to facilitate the modeling process. This article shows that producing 3D environment model can be facilitated by using stereo camera calibration data without the needto matchthe process, especially in the areas where the matching has problem because of insufficient information required. Moreover, using camera calibration information, geometric information and depth map of the environment can be extracted and produced without the need to define the specified scale between features. The results of practical studies and the reconstruction done in the urban environment were assessed later in this paper.
