Principles Of Photogrammetry Research Articles

Rockfall mapping and susceptibility evaluation based on UAV high-resolution imagery and support vector machine method

Abstract This study aims to develop a comprehensive method for automated rockfall mapping and susceptibility assessment using unmanned aerial vehicle (UAV) tilt photography and the support vector machine (SVM) algorithm. By employing Jinzhong Town in the mountainous forest landscapes of Southwest China as a case study, we leverage photogrammetry principles and computer vision algorithms to generate high-precision, high-resolution digital surface models (DSMs), and digital orthophoto maps through a UAV remote sensing system. The rockfall inventory is accurately and automatically mapped using the object-based classification method and SVM algorithm. The automated rockfall identification method achieves a 93% accuracy with a Kappa coefficient of 0.7967. Statistical analyses of spatial distribution characteristics reveal a significant correlation between rockfall volume and area with a correlation coefficient (R²) of 0.92316 under logarithmic coordinates. In addition, a power function relationship describes the link between rockfall volume and slope height (R² = 0.87), while the relationship with sliding distance is characterized by a weaker linear correlation (R² = 0.65). Rockfall runout distance also shows a significant linear correlation with slope height (R² = 0.79) but exhibits a less-pronounced association with rockfall volume (R² = 0.58). The SVM model employed to assess rockfall susceptibility indicates high accuracy (area under the curve = 0.896), affirming its efficacy in rockfall susceptibility assessment. Our findings underscore the utility of UAV remote sensing for rockfall information extraction and susceptibility evaluation, particularly in challenging mountainous forest environments characterized by intricate topography and geological complexities.

Three-dimensional modeling and defect quantification of existing concrete bridges based on photogrammetry and computer aided design

Bridge infrastructure is aging and deteriorating and requires innovative condition monitoring and assessment to ensure safety and maintain serviceability. Current practices for bridge condition assessment depend mainly on visual inspection. Innovative data collection technologies can assist in bridge inspection and defect identification and circumvent the limitations of traditional visual inspection. This research aims to apply photogrammetry principles and image processing techniques to develop a full-scale three-dimensional (3D) bridge structure model for defect identification and quantification. The data source to establish the point cloud models is a set of digital images taken at the bridge site. The point cloud models are developed by analyzing high-resolution images captured using a Nikon D4S camera. The images are captured from different positions/locations to provide extensive stereo coverage and maximum overlapping. Two hundred images of the bridge are processed with PhotoModeler software along with the calibration information, and ground control points (GCPs) coordinates to create the models. A standard digital close-range image processing is implemented to generate the 3D points cloud model. The calibration and orientation processes are made over a deformed situation. However, the developed CAD bridge drawings depict the original undeformed geometry. The extracted bridge inventory data from the 3D model, including bridge geometry information and bridge damage quantification, can provide a baseline for the bridge monitoring system to detect bridge deterioration over the years. The developed photogrammetric 3D model has an RMSE of 0.0081 m and uncertainty of ± 0.0041 m. Future research can aim at developing reusable parametric objects for bridges in Revit and coding scripts using programming languages such as Dynamo or Python to perform further analysis of the captured information.

Advanced 3D Modeling System Utilizing Photogrammetric Techniques

This paper considers approaches and principles of building the 3D modeling system based on photogrammetry principles. It also describes integration with Object Capture, developed by Apple, as an example of technology that allows creating 3D models of real-world objects using a set of photos. Additionally, the article describes the approach to creating client-server applications, which will provide potential users with a convenient interface for interacting with the system.

Structural Health Monitoring: GGBS – Foam concrete evaluation for Stress-Strain Characterization

Digital Image Processing (DIP) uses photogrammetry principles to monitor elements in space and attribute respective coordinates to a pre-set reference frame. The comparison makes the measure of a graphic collection taken above fixed intervals. The technique may be performed in many experiments, including compressive, longitudinal, torque, bending, and different combined loading for static and dynamic applications. As the world’s engineering structures (such as towers and highways) mature, there seems to be a critical necessity to maintain and analyse the integrity of the system of large buildings. As per the American Society of Civil Engineers (ASCE), there were 161,892 obsolete or technically deficient bridges in the U. S. as of 2008, with the mean lifespan of a bridge being 43 years old. The primary method used to assess deck integrity today is subjectively direct observation, which is unreliable since specific damage can be hard to spot, difficult to quantify visibly, or subject to individual perception. Bridges have lately been monitored using classic detectors like strain gauges and deflection indicators.

The Center of the Circle Fitting Optimization Algorithm Based on the Hough Transform for Crane

The basic principle of photogrammetry is mature and widely used in engineering. For gantry cranes, the base of which is usually a cylinder, the measurement of the center of the cylinder cross section is difficult, but its coordinates have an important impact on the safety evaluation of cranes. Aiming at the problem of measuring the center of a circle, an optimization method of fitting the center of a circle based on photogrammetry and the Hough transform is proposed. In this algorithm, the effect of image point distortion on the measurement accuracy is considered, and the similarity between ideal and actual midperpendicular is compared in the Hough space. The similarity is taken as the weight of the midperpendicular, and the space coordinates of the center of the circle are fitted again. This process needs to iterate repeatedly until convergence, and the fitting accuracy of the equal weighted midperpendicular fitting algorithm and the weighted midperpendicular fitting algorithm is compared. Finally, according to the characteristics of the algorithm, a theoretical verification experiment and an engineering experiment are carried out. The experimental results show that the proposed weighted midperpendicular fitting algorithm has a better effect than the equal weighted midperpendicular fitting algorithm, which obviously improves the fitting accuracy of the center of the circle and has high engineering value. In both experiments, the relative error was less than one percent. Especially in the engineering experiments, the weighted midperpendicular algorithm improved accuracy by an order of magnitude. Therefore, the proposed algorithm significantly improves the fitting accuracy of the center of the circle and effectively solves the difficulty that the center of the circle cannot be directly measured on the construction machinery.

Data-driven approach for 2D shoreline, and 3D volumetric change detection analysis: a case study for Jupiter inlet lighthouse outstanding natural area

Coastal areas are constantly changing and are influenced by a variety of variables, including environmental, ecological, geological, and anthropological factors. The plethora of coastal change has created substantial challenges for coastal land infrastructures, animal habitat, vegetation conservation, and monitoring. It is important to track these changes, monitor, predict, and preserve the future of coastal areas. Shoreline mapping has mostly concentrated on two-dimensional (2D) distance changes along the coast due to the lack of coastal elevational data and the precise information required to construct the three-dimensional (3D) surface. Modern technology has covered the gaps by developing a range of sensors and algorithms for data analysis on 3D coastal erosion and accretion changes throughout the beach topography, which has become crucial. The ultimate goal is to develop a cost-effective mapping procedure for an area that includes a high-resolution mapping system that abstracts evidence of coastal areas for long-term 2D change rates from 1953 to 2020 and short-term 3D volumetric changes of sand erosion and accretion rates from 2018 to 2020. This would be accomplished through Unmanned Aircraft Systems Mapping, which employs digital photogrammetry principles including comprehensive geospatial information systems spatial data and linear regression analysis to investigate massive quantities of data. The feasibility of this methodology was applied to the Jupiter Inlet Lighthouse Outstanding Natural Area in Jupiter, Florida, a study coastal area that had receded almost 27 m in the last 67 years. The outcomes of a short-term coastal analysis quantify the amount of soil erosion and accretion that occurred along the shore over two years as a result of rising sea levels. The long-term change analysis indicates how much sand was eroded each year as a result of several variables affecting shoreline changes, which will help the land management team in developing new sustainable policies for future coastal environmental conservation.

Research on the Application of Computer Vision Technology in Power System UAV Line Inspection

The stability of transmission lines is one of the important factors to ensure stable power supply. In this paper, a set of UAV intelligent power line inspection flight control system is designed according to the special flight requirements of UAV in power line inspection operation based on the principle of photogrammetry. The key technologies of the system include UAV flight attitude control, high-precision time synchronization between multiple sensors, defect detection and intelligent diagnosis, airborne sensor calibration, wireless communication, and ground data processing. In this paper, a camera and an on-board computer are innovatively used for real-time image processing and pattern recognition for wire feature acquisition. At the same time, this paper proposes an improved Canny edge detection algorithm combined with image segmentation technology to achieve wire feature extraction and identification. The field test results show that the system can complete the remote control of the UAV and realize the intelligent navigation and inspection of the transmission line UAV.

Effect of Corundum and Basalt Aggregates on the Ballistic Resistance of UHP-SFRC

Ultra-high-performance steel-fibre-reinforced concrete (UHP-SFRC) is a technologically advanced composite with a high ability to absorb and dissipate mechanical energy. This work investigates the possibility of increasing ballistic resistance by adding different percentages of corundum and basalt aggregate into this type of concrete. The most common type of ammunition, a 7.62 mm × 39 mm calibre with a full-metal jacket and a mild-steel core (FMJ-MSC), was used to test all samples. The size of the damage and the mode of failure were determined using a 3D scanner operating on the principle of photogrammetry. The experimental campaign showed that the addition of basalt and, especially, corundum aggregate has a positive effect on ballistic resistance. In particular, the increase in compressive strength and the slight decrease in depth of penetration (DOP) was observed in the case of the usage of the corundum aggregate.

Recycled materials execution through digital image processing

The main aim of composition is to investigate reinforced concrete using a novel approach to the digital image process (DIP). Utilization of the photogrammetry principles to track features and assign their position to a predetermined coordinate system. The present study deals with the systematic investigation of the cracks propagate and created inside the factual is a crucial feature of the sharp Ordinal pictures. They are apprehended ahead of overwhelming (undistorted position) and specific cases of loading. The pictures were explored through the connexion procedure to reckon the shallow displacements, strains, flaw overture, descending shortcomings, transposition of point load, flaw interval, and break gradient position. The obtained results of concrete material using Matlab® tool. The behavior of various samples such as conventional mix, 3%, 3.6%, and 4.2% steel fiber concrete was examined using DIP. The considered of augment structural health monitoring techniques currently practice in various applications. DIP technique employed to assess the external displacement and damage within concrete. In general, various faults transpire in hardened concrete specimens. This analysis deal with damage estimation inside reinforced concrete examples concurred with the code IS:456(limit states approach) through novel techniques. The connexion scrutiny using the program illustrates the proportional displacement along with the rupture arrest on the glued boundaries and the frictional interface. The attained displacement quantities are converted to strain using this novel technique, and respected stresses were obtained. This analysis is a primary pace about expending the digital image process technique in incorporation with high-speed taking pictures to capture the highly transitory singularities complexed in deep cracks.

DIGITAL SURFACE MODEL DERIVED FROM UAS IMAGERY ASSESSMENT USING HIGH-PRECISION AERIAL LIDAR AS REFERENCE SURFACE

Abstract. Imagery captured from aerial unmanned systems (UAS) has found significant utility in the field of surveying and mapping as the efforts of the computer vision field combined the principles of photogrammetry. Its respectability in the remote sensing community as increased as the miniaturization of on-board survey-grade global navigation satellite system (GNSS) signal receivers has made it possible to produce high network accuracy contributing to effective aerotriangulation. UAS photogrammetry has gained much popularity because of its effectiveness, efficiency, economy, and especially its availability and ease of use. Although photogrammetry has proven to meet and exceed planimetric precision and accuracy, variables tend to cause deficiencies in the achievement of accuracy in the vertical plane. This research aims to demonstrate achievable overall accuracy of surface modelling through minimization of systematic errors at a significant level using a fixed-wing platform designed for high-accuracy surveying with the eBee Plus and X models by SenseFly equipped with survey-grade GNSS signal-receiving capabilities and 20MP integrated, fixed-focal length camera. The UAS campaign was flown over a site 320 m by 320 m with 81 surveyed 3D ground control points, where horizontal positions were surveyed to 1.0 cm horizontal accuracy and 0.5 cm vertical accuracy using static GNSS methods and digital leveling respectively. All AT accuracy was based on 75 independent checkpoints. The digital surface model (DSM) was compared to a reference DSM generated from high-precision manned aerial LiDAR using the Optech Galaxy scanner. Overall accuracy was in the sub-decimeter level vertically in both commercial software used, including Pix4Dmapper and Agisoft Metashape.

Imaging network design to improve the automated construction progress monitoring process

PurposeThis paper aims to propose an automatic imaging network design to improve the efficiency and accuracy of automated construction progress monitoring. The proposed method will address two shortcomings of the previous studies, including the large number of captured images required and the incompleteness and inaccuracy of generated as-built models.Design/methodology/approachUsing the proposed method, the number of required images is minimized in two stages. In the first stage, the manual photogrammetric network design is used to decrease the number of camera stations considering proper constraints. Then the image acquisition is done and the captured images are used to generate 3D points cloud model. In the second stage, a new software for automatic imaging network design is developed and used to cluster and select the optimal images automatically, using the existing dense points cloud model generated before, and the final optimum camera stations are determined. Therefore, the automated progress monitoring can be done by imaging at the selected camera stations to produce periodic progress reports.FindingsThe achieved results show that using the proposed manual and automatic imaging network design methods, the number of required images is decreased by 65 and 75 per cent, respectively. Moreover, the accuracy and completeness of points cloud reconstruction is improved and the quantity of performed work is determined with the accuracy, which is close to 100 per cent.Practical implicationsIt is believed that the proposed method may present a novel and robust tool for automated progress monitoring using unmanned aerial vehicles and based on photogrammetry and computer vision techniques. Using the proposed method, the number of required images is minimized, and the accuracy and completeness of points cloud reconstruction is improved.Originality/valueTo generate the points cloud reconstruction based on close-range photogrammetry principles, more than hundreds of images must be captured and processed, which is time-consuming and labor-intensive. There has been no previous study to reduce the large number of required captured images. Moreover, lack of images in some areas leads to an incomplete or inaccurate model. This research resolves the mentioned shortcomings.

Naturalistic measurement of driver eye height and object height using photogrammetry

Driver eye height and object height are key factors in the derivation of basic parameters for safe and economically efficient highway design. In this work, previous approaches to the measurement of these values were critically reviewed and the changes in them over time were investigated. Previous methods of measurement were found to have considerable limitations in terms of coverage or accuracy. A new approach was thus developed for the naturalistic recording of a sample of vehicles using the principles of photogrammetry – the first time this approach has been used for all vehicle types. A field survey on a typical single-carriageway UK trunk road was undertaken and the driver eye and object heights of vehicles using the route were recorded. This work confirms the consumer trend for larger vehicles with a consequential increase in driver eye height and object height. It was found that the values used in current design standards are conservative and robust, but potential exists for further review. The results of this study will be useful to roads authorities internationally in defining their own highway design standards.

Application of a Continuous Terrestrial Photogrammetric Measurement System for Plot Monitoring in the Beijing Songshan National Nature Reserve

Monitoring sample areas is the basis of ecological management. Songshan National Nature Reserve is one of the most important components of the ecosystem of the central metropolitan area of Beijing, and has fallen behind in its monitoring technology and methods. So, updating the existing equipment and technology is necessary. The current system suffers from high equipment costs and is not convenient to carry, so the work efficiency is low. Furthermore, the data cannot be visualized in three dimensions (3D), and complex terrain conditions cannot be measured. Therefore, this study researched and developed a continuous terrestrial photogrammetric measurement system that is theoretically based on the principles of photogrammetry, image processing technology, and dendrometry. The system applies a self-developed personal digital assistant (PDA) photogrammetry-based dendrometer and software to continuously evaluate stand sampling areas. Through experimental verification, the relative root mean square error (RMSE) of the trunk diameter measurements was found to be 5.59%, and the relative RMSE of hypsometrical measurements was 3.93%, which are both higher than the accuracy required for traditional forestry surveys. Furthermore, the advantages of this system include its low cost, lightweight equipment, easy operation, high measurement efficiency, 3D visualization, and applicability under complex terrain conditions. Since it is highly accurate and efficient, the continuous terrestrial photogrammetric system can be easily applied to monitor stand sampling areas in Songshan National Nature Reserve. In addition, it can be applied to second-class forest surveys in China, thus guaranteeing the monitoring of big data for the ecological environment of China.

Point cloud processing techniques and image analysis comparisons for boat shapes measurements

Photomodelling is a new and fast solution for 3D modelling, based on the same principles of photogrammetry. The comparison between photomodelling and the metrological technique of structured light 3D scanning, provided by the Creaform Go Scan 50 with metrological certification, is the aim of this paper, defining performances and verifying the potential of this innovative, simple and economical technique.

Issues in Unmanned Aerial Systems (UAS) Data Collection of Complex Forest Environments

Unmanned Aerial Systems (UAS) offer users the ability to capture large amounts of imagery at unprecedented spatial resolutions due to their flexible designs, low costs, automated workflows, and minimal technical knowledge barriers. Their rapid extension into new disciplines promotes the necessity to question and understand the implications of data capture and processing parameter decisions on the respective output completeness. This research provides a culmination of quantitative insight using an eBee Plus, fixed-wing UAS for collecting robust data on complex forest environments. These analyses differentiate from measures of accuracy, which were derived from positional comparison to other data sources, to instead guide applications of comprehensive coverage. Our results demonstrated the impacts of flying height on Structure from Motion (SfM) processing completeness, discrepancies in outputs based on software package choice, and the effects caused by processing parameter settings. For flying heights of 50 m, 100 m, and 120 m above the forest canopy, key quality indicators within the software demonstrated the superior performance of the 100-m flying height. These indicators included, among others, image alignment success, the average number of tie points per image, and planimetric model ground sampling distance. We also compared the output results of two leading SfM software packages: Agisoft PhotoScan and Pix4D Mapper Pro. Agisoft PhotoScan maintained an 11.8% greater image alignment success and a 9.91% finer planimetric model resolution. Lastly, we compared the “high” and “medium” resolution processing workflows in Agisoft PhotoScan. The high-resolution processing setting achieved a 371% increase in point cloud density, with a 3.1% coarser planimetric model resolution, over a considerably longer processing time. As UAS continue to expand their sphere of influence and develop technologically, best-use practices based on aerial photogrammetry principles must remain apparent to achieve optimal results.

Comparison between point cloud processing techniques

Photomodelling is an innovative, economical and fast technique based on the same principles of photogrammetry, which leads to the creation of 3-dimensional models starting from the simple acquisition of photographs. The aim of this paper is to define performances and metrological characteristics of this new technique and to understand the full potential offered by point cloud processing software. The analytical comparison considers a structured light 3D scanning system Creaform Go Scan 50 with metrological certification as a reference, in order to verify the accuracy and precision of photomodelling, using a modified function of the ICP algorithm and spatial, volumetric and superficial comparison criteria.

Best Practices in Low Altitude UAV Mapping for GIS Applications

Aerial data collection for use in GIS has, in the past, been an expensive undertaking and required significant capital expenditures for metric aerial cameras, aircraft purchase, maintenance, fuel, insurance, and not to mention a significant cost for specialized labour. The advent of Unmanned Aerial Vehicles (UAV’s), and their increasing mainstream use, has created an alternative to conventional aerial photography for the creation of Digital Surface Models (DSMs) and orthophotos. The standards of traditional aerial data collection have been spelt out in long-established guidelines by the American Society of Photogrammetry and Remote Sensing. UAV operators, often non-specialist newcomers to the field, have side-stepped these standards and have no means to ensure the quality and reproducibility of their data. I propose a set of simple best-practices that can be adopted both by UAV operators and their clients to establish some measure of Quality Assurance and Quality Control while maintaining the cost-advantage afforded by UAVs. These practices can be grouped into five main areas: 1) proper camera and lens selection, 2) pre-calibration of cameras used for photogrammetric mapping, 3) establishing accurate ground-control across the area of mapping and not relying on consumer-grade GNSS for air stations, 4) pre-flight calculation of flight parameters based on a clear accuracy requirement, 5) flying at a sufficient height to minimize relief displacement so as to create artifact-free orthophotos. It is hoped that a better understanding of the underlying principles of photogrammetry by both UAV operators and their clients will guarantee the proper implementation of UAVs for high-accuracy GIS data collection in the future.

PHOTOGRAMMETRY IN 3D MODELLING OF HUMAN BONE STRUCTURES FROM RADIOGRAPHS

Abstract. Photogrammetry can have great impact on the success of medical processes for diagnosis, treatment and surgeries. Precise 3D models which can be achieved by photogrammetry improve considerably the results of orthopedic surgeries and processes. Usual 3D imaging techniques, computed tomography (CT) and magnetic resonance imaging (MRI), have some limitations such as being used only in non-weight-bearing positions, costs and high radiation dose(for CT) and limitations of MRI for patients with ferromagnetic implants or objects in their bodies. 3D reconstruction of bony structures from biplanar X-ray images is a reliable and accepted alternative for achieving accurate 3D information with low dose radiation in weight-bearing positions. The information can be obtained from multi-view radiographs by using photogrammetry. The primary step for 3D reconstruction of human bone structure from medical X-ray images is calibration which is done by applying principles of photogrammetry. After the calibration step, 3D reconstruction can be done using efficient methods with different levels of automation. Because of the different nature of X-ray images from optical images, there are distinct challenges in medical applications for calibration step of stereoradiography. In this paper, after demonstrating the general steps and principles of 3D reconstruction from X-ray images, a comparison will be done on calibration methods for 3D reconstruction from radiographs and they are assessed from photogrammetry point of view by considering various metrics such as their camera models, calibration objects, accuracy, availability, patient-friendly and cost.

A critical evaluation of the use of an inexpensive camera mounted on a recreational unmanned aerial vehicle as a tool for landslide research

This letter offers a critical evaluation of the use of an inexpensive camera mounted on a recreational unmanned aerial vehicle as a tool for landslide research. The constructed 3D surface models are compared to those generated using a DSLR camera, Total Station and Terrestrial Laser Scanning. It is shown that the investigated approach has considerable potential despite the fact that its performance was slightly inferior to the other methods. This was demonstrated also in a real case study of a small shallow landslide. Nonetheless, in order to assess the real accuracy and precision of the constructed models, it is emphasised that the operator should still have a basic knowledge of the principles of photogrammetry.

Tracking Navigation System Based on Photogrammetry Principles

An approach to implementation of spatial navigation based on photogrammetry principles is proposed. A prototype of a tracking navigation system implementing the abovementioned approach is developed; experimental research of developed system is conducted.