Photogrammetric Studies Research Articles

Spatial data collection in cadastral updating in Turkey

In the cadastral studies carried out in Turkey in the last century, cadastral maps were produced using different surveying methods. It is also constantly replacing or diversifying its surveying methods with new ones. Finally, it has started to produce spatial data for cadastral parcels with the photogrammetric method using UAV technology. The expected accuracy in spatial data generation is ±7 cm. This article includes all surveying methods used in cadastral studies to date. In addition, the contribution of photogrammetric studies to the cadastral updating activities was investigated, carried out using UAV in a study area of 18 thousand ha.

Use of Unmanned Aerial Vehicle Technology in the Protection of Goods of Cultural Interest (GCIs): The Case of the Castle of Cala (Huelva, Spain)

Currently, the use of modern technologies, such as UAVs, allows for a detailed analysis of the protection of Sites of Cultural Interest (BICs) in Spain. Cala Castle in Huelva is selected for this study, which is one of the most important medieval fortifications in the mountainous region and was rehabilitated between 2003 and 2011. After a decade of its architectural rehabilitation, the use of this new UAV technology will allow the creation of a database of the property and its surroundings, made up of a series of 3D models and photogrammetric studies of the territory. This analysis allows us two complementary readings to the original study: on the one hand, to characterize the natural and landscape context of Cala Castle, and on the other, to identify the pre-existence of a series of historic buildings, which have historically articulated this region. The 3D models obtained provide relevant graphic information. The current state of the BIC allows this space to be considered for reactivation as a social space at the regional level. The visuals of the regional environment allow us to identify that the most recent growth has been articulated longitudinally along the N-630 highway, this infrastructure being the backbone of the nucleus. As a pilot test, the beginning of this graphic and visual database (3D) at a regional level will provide a valuable tool for the conservation and registration of built heritage, given that it seeks to incorporate other fortifications that make up Banda Gallega with the aim of defining a sustainable development strategy at county level.

Deep learning-based vehicle detection from orthophoto and spatial accuracy analysis

Deep Learning algorithms are used by many different disciplines for various purposes, thanks to their ever-developing data processing skills. Convolutional neural network (CNN) are generally developed and used for this integration purpose. On the other hand, the widespread usage of Unmanned Aerial Vehicles (UAV) enables the collection of aerial photographs for Photogrammetric studies. In this study, these two fields were brought together and it was aimed to find the equivalents of the objects detected from the UAV images using deep learning in the global coordinate system and to evaluate their accuracy over these values. For these reasons, v3 and v4 versions of the YOLO algorithm, which prioritizes detecting the midpoint of the detected object, were trained in Google Colab’s virtual machine environment using the prepared data set. The coordinate values read from the orthophoto and the coordinate values of the midpoints of the objects, which were derived according to the estimations made by the YOLO-v3 and YOLOV4-CSP models, were compared and their spatial accuracy was calculated. Accuracy of 16.8 cm was obtained with the YOLO-v3 and 15.5 cm with the YOLOv4-CSP. In addition, the mAP value was obtained as 80% for YOLOv3 and 87% for YOLOv4-CSP. F1-score is 80% for YOLOv3 and 85% for YOLOv4-CSP.

METHODOLOGY TO IMPROVE THE ACCURACY OF DETERMINING THE POSITION OF UAVS EQUIPPED WITH SINGLE-FREQUENCY RECEIVERS FOR THE PURPOSES OF GATHERING DATA ON AVIATION OBSTACLES

Low-altitude photogrammetric studies are often applied in detection of aviation obstacles. The low altitude of the Unmanned Aerial Vehicle (UAV) flight guarantees high spatial resolution (X, Y) of the obtained data. At the same time, due to high temporal resolution, UAVs have become an appropriate tool for gathering data about such obstacles. In order to ensure the required accuracy of orientation of the photogrammetric block, Ground Control Points (GCPs) are measured. The recently introduced UAV positioning solutions that are based on Post-Processing Kinematic (PPK) and Real Time Kinematic (RTK) are known to effectively reduce, or, according to other sources, even completely eliminate the necessity to conduct GCP measurements. However, the RTK method involves multiple limitations that result from the need to ensure continuous communication between the reference station and the rover receiver. The main challenge lies in achieving accurate orientation of the block without the need to conduct time-consuming ground measurements that are connected to signalling and measuring the GCPs. Such solution is required if the SPP code method is applied to designation the position of the UAV. The paper presents a research experiment aimed at improving the accuracy of the determination of the coordinates of UAV for the SPP method, in real time. The algorithm of the SPP method was improved with the use of IGS products.

Evaluation of Errors Encountered in Photogrammetric Studies on Lower Extremities

Objective: The aim of our study is to reveal the errors that can be encountered during the shooting of photogrammetric studies on the lower extremities. Methods: We revealed the necessary tools that used during photogrammetry measurements of the lower limb. Also, the errors have been encountered of our two previous studies performed on photogrammetry of lower limbs. The technical errors or incorrect positioning of 20 from 220 volunteers were encountered. Results: The identified errors of 20 volunteers’ photographs related to lower limb were about the inadequate quality image, calibration, poor lightining, positioning error of trunk or parts of lower limb and clothes that cover the anatomical points affected the measurements. Conclusion: Photogrammetry is an important and useful tool for evaluation, diagnosis, treatment, and efficacy monitoring. In anatomy, it is frequently used as a time-saving method in terms of measurement and evaluation in the laboratory, which can be applied and repeated for research. For this reason, errors that occur during the lower extremity have been reported and we think that it will be useful for studies on this part of the body and can be a guide.

Optimising UAV Data Acquisition and Processing for Photogrammetry: A Review

Unmanned aerial vehicles (UAVs) are used to acquire measurement data for an increasing number of applications. Photogrammetric studies based on UAV data, thanks to the significant development of computer vision techniques, photogrammetry, and equipment miniaturization, allow sufficient accuracy for many engineering and non-engineering applications to be achieved. In addition to accuracy, development time and cost of data acquisition and processing are also important issues. The aim of this paper is to present potential limitations in the use of UAVs to acquire measurement data and to present measurement and processing techniques affecting the optimisation of work both in terms of accuracy and economy. Issues related to the type of drones used (multi-rotor, fixed-wing), type of shutter in the camera (rolling shutter, global shutter ), camera calibration method (pre-calibration, self-calibration), georeferencing method (direct, indirect), technique of measuring the external images orientation parameters (RTK, PPK, PPP), flight design methods and the type of software used were analysed.

Uso de un vehículo aéreo no tripulado como alternativa para evaluar el estado nutricional del cultivo de algodón

The use of unmanned aerial vehicles in photogrammetric studies allows obtaining spatial data in short periods of time and with high spatial resolution. In the research, multispectral images were processed for the study of nutritional conditions of the cotton crop (Gossypium hirsutum). An experimental design of the crop was developed, with different doses and nitrogen sources, in a factorial arrangement with 16 treatments and 4 repetitions in plots completely distributed at random. The EBEE SQ agricultural drone, equipped with the Parrot Sequoia camera, was used and a photogrammetric flight was planned, with the Emoticon AG software, which was synchronized with the drone to establish the flight parameters and capture the reflectance information of the visible spectrum, infrared and red border. The captured images were processed with the PIX4D Mapper software to generate the orthophoto and the 4 spectral bands used in the calculation of the chlorophyll index. Using map algebra tools from ArcGIS software on the results obtained, an analysis of variance was performed with the ANOVA model. With the calculated indices it was possible to show differences in the vigor of the crop depending on the treatments. The analysis of the results showed significant differences in the spectral response of the cotton crop fertilized with different sources (urea, pine nut cake, hen manure and bovine manure) and nitrogen doses (50, 100, 150 and 200 N kg.ha-1). Urea treatment at the 150 dose of N kg.ha-1 showed the best spectral response.

CALIBRATION OF THE LOW-COST UAV CAMERA ON A SPATIAL TEST FIELD

For several years, the widening range of applications of unmanned aerial vehicles can be noticed not only in the literature review but also in the market of services offered – also in the geodetic sector. While there is a wide range of professional UAVs for aerial mapping tasks, these platforms are expensive. In this study, it was checked whether the calibration of a low-cost drone camera allows for obtaining an accuracy acceptable for photogrammetric studies. For this purpose, a spatial test field was designed on which a multivariate calibration of the UAV camera and control of the obtained results were carried out. Using the elements of the camera’s internal orientation obtained during the calibration process, it was not possible to achieve high accuracy of photogrammetric measurements on control images. This may indicate a problem with the repeatability of determining the elements of internal orientation of the analyzed camera, and thus with the instability of the autofocus system. Nevertheless, the use of the obtained results from the camera calibration as precise approximations of the elements of the camera’s internal orientation had a positive effect on the solution of the image network using the bundle adjustment and the fitting of the spatial model to the ground control points. In addition, the UAV flight over the created spatial test field allowed for a reliable assessment of the possibilities and accuracy that can be obtained on the basis of images from a low-cost drone.

Simulated Photogrammetric Data for Testing the Performance of Photogrammetric Instruments and Systems

The generation of mathematical photograms (photos) as data is universally accepted as the basis for photogrammetric studies. New development in the field of computer technology has had a major influence on photogrammetry. This paper aims to describe the development of a computer system called SimuPhotos designed to produce simulated data in different forms for testing photogrammetric methodologies, software, and instruments. SimuPhotos is capable of generating photogrammetric blocks with different specifications. It generates the simulated data for the whole block, strips, or selected photos. The simulated free error data include the camera interior orientation parameters, ground coordinates of points, and for each photograph, camera exterior orientation parameters, and the photo coordinates of imaged points. To increase the capabilities of the developed system, it has a special error generator to get normally distributed error(s) with arbitrary mean(s) and standard deviation(s). The obtained errors are then, if required, applied to the error-free photo and ground coordinates of points. The developed system interfaces CAD technology to generate simulated photogrammetric data in DXF and raster formats which are suitable for testing the photogrammetric instruments and softcopy systems. SimuPhotos has been used for testing the analytical photogrammetric system PhotoMap. The results showed that PhotoMap is free of system error and is functional. Also, the results showed that SimuPhotos can effectively provide a convenient, economical, and accurate testing tool for photogrammetric systems. The developed system is quite versatile and affordable.

From the cave to the virtual museum: accessibility and democratisation of Franco-Cantabrian Palaeolithic art

Highlights: Despite being a transcendental cultural manifestation in the history of humanity, there are hardly any open-access virtual repertoires of Palaeolithic art. The numerous photogrammetric studies carried out in successive archaeological campaigns to answer scientific questions can be used in educational and dissemination projects. In the framework of the authors’ outreach project called "PaleoArt-3D: regreso al pasado" a virtual museum has been created to make Palaeolithic art a more accessible and democratic heritage. Abstract: Palaeolithic art is a cultural manifestation of great importance to understanding the early history of our species. Through this artistic phenomenon, one can study aspects such as long-distance contacts, evidence of learning or the perception with which Palaeolithic humans were able to execute and memorise such precise details. However, there are few virtual repertoires that offer collections of Palaeolithic art. Accessibility to this type of archaeological remains is even more difficult considering conservation is prioritised over tourist visits. For these reasons, Palaeolithic art is today a type of cultural asset that is largely unknown to the population. The project "PaleoArt-3D: regreso al pasado" was created with the aim of democratising this heritage and making it more accessible. To this end, a virtual museum has been developed to exhibit digital models of parietal and portable art with complementary annotations for each one. The methodology includes a first stage dedicated to digitising examples of Palaeolithic art in caves or open-air stations and exhibited in Spanish and French museums. Next, the necessary infrastructure was designed to house the exhibition using specific software such as Blender. Post-processing tasks were carried out to reducing the number of polygons without losing quality. Finally, the museum has been uploaded to the Sketchfab platform to make it freely available online. It is hoped that this virtual museum will contribute to promoting and creating a more significant number of digital resources related to Palaeolithic art that are easily accessible to the public.

Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up

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.

GNSS and RPAS Integration Techniques for Studying Landslide Dynamics: Application to the Areas of Victoria and Colinas Lojanas, (Loja, Ecuador)

This research tests the application of GNSS and RPAS techniques to the spatiotemporal analysis of landslide dynamics. Our method began by establishing non-permanent GNSS networks on the slope surfaces to perform periodic measurements by differential GNSS. Similarly, RPAS flights were made to acquire high-resolution images, which were oriented and georeferenced using ground control points and structure-from-motion algorithms to ultimately obtain digital surface models and orthophotos. Based on GNSS measurements, the direction and velocity of displacements were accurately calculated, and orthophotos and DSMs were used to calculate horizontal and vertical displacements in a set of significant points throughout the study area, reaching accuracies higher than 0.035 m in the GNSS data and 0.10 m in the RPAS data. These values were within the accuracy required for such studies. Based on the field observations and the results from the photogrammetric studies, the two studied landslides were classified as very slow flows. These techniques are the basis for establishing early warning systems in areas of natural hazards based on the calculation of displacement speeds of the surface of slopes.

ENVIRONMENTAL CHALLENGES, TECHNICAL SOLUTIONS AND STANDARD OPERATING PROCEDURES FOR DATA COLLECTION IN PHOTOGRAMMETRIC STUDIES TOWARD A UNIFIED DATABASE OF OBJECTS AND FEATURES IN UNDERWATER CAVES IN MEXICO

Abstract. Mexico’s Yucatan Peninsula is predominantly formed as a karstic terrain on limestone substrates where hundreds of kilometres of now submerged caves constitute extended networks of galleries partially accessible through cenotes, or karstic windows. These cenotes and underwater caves contain numerous objects of great biological, historical, cultural and/or paleontological significance: human and animal remains, ancient Maya artifacts, ancient mines and traces of early human activities. Photogrammetric studies by technical divers allow researchers to access a vast array of data pertaining to objects or features which would otherwise remain inaccessible. However, the harshness of the study environment poses technical acquisition challenges which must be specifically addressed. This paper introduces these environmental challenges, including the geological properties of local caves, bottom composition, ceiling percolation and topography, as well as the intrinsic difficulties linked to the absence of light and the limited time available in an underwater work setting. Technical acquisition solutions, setups and standard operating procedures are then proposed to overcome these challenges. A further consideration is added pertaining to the overall goal of creating a global database for the study objects, thus requiring a unified format for all data: unique identifier, geolocation, minimum resolution, and the like. The authors, focusing on the fieldwork and the data-collection aspect of the photogrammetric study, rather than the data processing and metrological steps, define a new image acquisition methodology built around a compact and replicable setup which will allow the documenting of objects previously out of reach of traditional setups.

Photogrammetric analysis of multispectral and thermal close-range images

Sensors capable of multispectral and thermal imaging beyond visible bands offer many analysis possibilities for environmental monitoring. Different sensor images constitute an important source of information especially in the fields of agriculture, forestry, geology and energy. Photogrammetric studies have been affected by this development in recent years and have been used in the production of multispectral and thermal models besides the RGB model. However, due to geometric and radiometric resolution differences, it is difficult to combine or evaluate models produced from different types of sensors. In this study, the three-dimensional test field images obtained with RGB, multispectral and thermal sensors were oriented and modeled photogrammetrically. The accuracies of the control points on the produced models were compared and discussed. When the results are examined, control point accuracy was obtained as almost similar as in the RGB model after the orientation based on automatic feature matching. Automatic feature detection and matching in thermal images were not robustly produced due to low geometric resolution. For this reason, manual measurements were performed in thermal images, and the photogrammetric orientation and adjustment process was done accordingly. The fused evaluation approach considering RGB, multispectral and thermal images in one photogrammetric model was also implemented and discussed.

Accuracy assessment of kinematic PPP versus PPK for GNSS flights data processing

The integration of survey-grade Global Navigation Satellite Systems (GNSS) with photogrammetric measurement studies conducted with an aircraft has the potential to meet the need for the use of ground control points (GCP). In photogrammetric studies, there are different GNSS techniques to provide the precise positioning of the aircraft. The precise point positioning (PPP) technique has become an alternative method to post-processing kinematic (PPK) methods in the evaluation of GNSS data gathered with an aircraft at high speed. In this study, GNSS data gathered from two different flights conducted for photogrammetric surveys in Izmir, Turkey were processed with different software (RTKLIB, gLAB, CSRS-PPP, and GRAFNAV) through PPP technique with the ambiguity resolution (PPP-AR) method to analyse the performance of this method versus PPK. Three-dimensional (3D) positioning analyses of coordinate differences obtained from mapping flights demonstrated a variation pattern mainly between 0 and 6 cm for both kinematic PPP and PPK results.

Rapid photogrammetry of morphological traits of free‐ranging moths

Photogrammetric studies of free‐ranging animals are limited to mammals and birds. Recent advances in insect photogrammetry, including 3D imaging, are entirely associated with museum specimens. We present a rapid, simple, accurate, and inexpensive morphometric method targeting thousands of free‐ranging insects attracted to light screens using images taken without collecting a specimen or even constraining the individual in any manner. A reference grid printed on the screen is used to calibrate the images for shape and size without prior knowledge of the camera‐subject configuration. The method requires only inexpensive, off‐the‐shelf, consumer equipment, and freely available programming (R statistical language) and image processing (ImageMagick) tools. We demonstrate the efficacy of the method using a dataset of 3675 images of free‐ranging hawkmoths (Lepidoptera:Sphingidae) imaged in natural repose on a screen. We show that this method introduces no bias and has a high degree of correspondence with traditional morphometry using collected specimens. We also propose error metrics, which quantify the calibration quality and identify images with poor data. Although this method is particularly suited for the hyperdiverse moth community, which dominates the dynamics of many terrestrial ecosystems, it can be used for other phototropic taxa identifiable on an image to (morpho)‐species. It will help in accumulating reliable trait data from hundreds of thousands of individual insects without any expenditure on specimen collection. It is particularly suited for studies which require multi‐epoch, multi‐locate sampling like investigations into ecosystem stability, climate change, and community assembly.

Mission Flight Planning of RPAS for Photogrammetric Studies in Complex Scenes

This study describes a new approach to Remotely Piloted Aerial Systems (RPAS) photogrammetric mission flight planning. In this context, we have identified different issues appearing in complex scenes or difficulties caused by the project requirements in order to establish those functions or tools useful for resolving them. This approach includes the improvement of some common photogrammetric flight operations and the proposal of new flight schemas for some scenarios and practical cases. Some examples of these specific schemas are the combined flight (which includes characteristics of a classical block flight and a corridor flight in only one mission) and a polygon extrusion mode to be used for buildings and vertical objects, according to the International Committee of Architectural Photogrammetry (CIPA) recommendations. In all cases, it is very important to allow a detailed control of the flight and image parameters, such as the ground sample distance (GSD) variation, scale, footprints, coverage, and overlaps, according to the Digital Elevation Models (DEMs) available for the area. In addition, the application could be useful for quality control of other flights (or flight planning). All these new functions and improvements have been implemented in a software developed in order to make RPAS photogrammetric mission planning easier. The inclusion of new flight typologies supposes a novelty with respect to other available applications. The application has been tested using several cases including different types of flights. The results obtained in the quality parameters of flights (coverage and GSD variation) have demonstrated the viability of our new approach in supporting other photogrammetric procedures.

Drones and convolutional neural networks facilitate automated and accurate cetacean species identification and photogrammetry

Abstract The flourishing application of drones within marine science provides more opportunity to conduct photogrammetric studies on large and varied populations of many different species. While these new platforms are increasing the size and availability of imagery datasets, established photogrammetry methods require considerable manual input, allowing individual bias in techniques to influence measurements, increasing error and magnifying the time required to apply these techniques. Here, we introduce the next generation of photogrammetry methods utilizing a convolutional neural network to demonstrate the potential of a deep learning‐based photogrammetry system for automatic species identification and measurement. We then present the same data analysed using conventional techniques to validate our automatic methods. Our results compare favorably across both techniques, correctly predicting whale species with 98% accuracy (57/58) for humpback whales, minke whales, and blue whales. Ninety percent of automated length measurements were within 5% of manual measurements, providing sufficient resolution to inform morphometric studies and establish size classes of whales automatically. The results of this study indicate that deep learning techniques applied to survey programs that collect large archives of imagery may help researchers and managers move quickly past analytical bottlenecks and provide more time for abundance estimation, distributional research, and ecological assessments.

Photogrammetric studies of inaccessible sites in archaeology: Case study of burial chambers in Qubbet el-Hawa (Aswan, Egypt)

This study describes a new procedure for acquiring images and developing photogrammetric studies of inaccessible spaces in archaeology. The approach is based on the acquisition of photographs using a system mounted on a mast, with a length of up to 4 m. The camera is handled using a remote control assisted with a real-time viewer. After the acquisition of images, a photogrammetric process is developed. As a result, we can obtain photogrammetric products such as orthoimages that can be used for several purposes, such as the documentation of the initial status of the scene, the identification of elements, the planning of future work, etc. The procedure has been applied successfully to several burial chambers discovered in the Qubbet el-Hawa site (Aswan, Egypt). Among other results, we can highlight the identification of the deceased buried in a narrow intact chamber, which was opened for a short period, and the determination of the geometric measurements of the coffin that were usable in subsequent work. Thanks to the orthoimage obtained in this study the deceased of the QH34bb tomb was identified as Shemai, brother of governor Sarenput II. The obtaining of metric products of inaccessible spaces provides an important base of documentation to be used by other researchers with the great advantage of not affecting the scene and allowing them to design appropriate methods of conservation.

Quality Assessment of the Bidirectional Reflectance Distribution Function for NIR Imagery Sequences from UAV

Imaging from low altitudes is nowadays commonly used in remote sensing and photogrammetry. More and more often, in addition to acquiring images in the visible range, images in other spectral ranges, e.g., near infrared (NIR), are also recorded. During low-altitude photogrammetric studies, small-format images of large coverage along and across the flight route are acquired that provide information about the imaged objects. The novelty presented in this research is the use of the modified method of the dark-object subtraction technique correction with a modified Walthall’s model for correction of images obtained from a low altitude. The basic versions of these models have often been used to radiometric correction of satellite imagery and classic aerial images. However, with the increasing popularity of imaging from low altitude (in particular in the NIR range), it has also become necessary to perform radiometric correction for this type of images. The radiometric correction of images acquired from low altitudes is important from the point of view of eliminating disturbances which might reduce the capabilities of image interpretation. The radiometric correction of images acquired from low altitudes should take into account the influence of the atmosphere but also the geometry of illumination, which is described by the bidirectional reflectance distribution function (BRDF). This paper presents a method of radiometric correction for unmanned aerial vehicle (UAV) NIR images. The study presents a method of low-altitude image acquisition and a fusion of the method of the dark-object subtraction technique correction with a modified Walthall’s model. The proposed solution performs the radiometric correction of images acquired in the NIR range with the root mean square error (RMSE) value not exceeding 10% with respect to the original images. The obtained results confirm that the proposed method will provide effective compensation of radiometric disturbances in UAV images.