Terrestrial Close-range Photogrammetry Research Articles

Digitization of Built Heritage through Terrestrial Close Range Photogrammetry: Advantages and Limitations. Illustration of Ksar Kenadsa Southwest Algeria

The objective of this manuscript is to evaluate the efficacy of the methodology of terrestrial photogrammetry for the digitalization and three-dimensional modeling of the built heritage. This will be done by utilizing the case of Ksar Kenadsa as an exemplar and by contrasting the outcomes of three-dimensional modeling of the entities that arise from various alternatives of spatial and architectural arrangement.

Monitoring of the post-tensile structures camber using the terrestrial close-range photogrammetry

Post-Tensioned Structural Elements (PTSEs) are used in many modern constructions projects as a versatile form of the pre-stressed technique because of the efficiency of the durability properties and the highest resistance if compared with their counterparts. This paper presents an application of using digital measuring techniques in the field of deformation detection by using Digital Close Range Photogrammetry (DCRP), which is one of the most nowadays important sciences that are used in many engineering fields and applications. DCRP techniques have been developed by taking the advantage of the technological advances in the field of optics, laser devices, and the applied mathematical models of computer vision such as the Scale Invariant Feature Transform (SIFT) and the Direct Linear Transform (DLT). The scope of this paper is how to use the digital equipment to achieve the highest possible accuracy in a fraction of 1.00 mm of the PTSE camber monitoring through the commercial digital calibrated camera and Terrestrial Laser Scanner (TLS). The accuracy of the results of the DCRP technique has been proven by a laser total station. The final statistics indicate the deviation of the results compared to the coded designed models of the experimental PTSEs, deviations did not exceed 0.01 mm as a maximum difference.

Remarks on Geomatics Measurement Methods Focused on Forestry Inventory.

This contribution focuses on a comparison of modern geomatics technologies for the derivation of growth parameters in forest management. The present text summarizes the results of our measurements over the last five years. As a case project, a mountain spruce forest with planned forest logging was selected. In this locality, terrestrial laser scanning (TLS) and terrestrial and drone close-range photogrammetry were experimentally used, as was the use of PLS mobile technology (personal laser scanning) and ALS (aerial laser scanning). Results from the data joining, usability, and economics of all technologies for forest management and ecology were discussed. ALS is expensive for small areas and the results were not suitable for a detailed parameter derivation. The RPAS (remotely piloted aircraft systems, known as "drones") method of data acquisition combines the benefits of close-range and aerial photogrammetry. If the approximate height and number of the trees are known, one can approximately calculate the extracted cubage of wood mass before forest logging. The use of conventional terrestrial close-range photogrammetry and TLS proved to be inappropriate and practically unusable in our case, and also in standard forestry practice after consultation with forestry workers. On the other hand, the use of PLS is very simple and allows you to quickly define ordered parameters and further calculate, for example, the cubic volume of wood stockpiles. The results from our research into forestry show that drones can be used to estimate quantities (wood cubature) and inspect the health status of spruce forests, However, PLS seems, nowadays, to be the best solution in forest management for deriving forest parameters. Our results are mainly oriented to practice and in no way diminish the general research in this area.

3D simulation models for developing digital twins of heritage structures: challenges and strategies

Structural vulnerability assessment of heritage structures is a pivotal part of a risk mitigation strategy for preserving these valuable assets for the nations. For this purpose, developing digital twins has gained much attention lately to provide an accurate digital model for performing finite element (FE) analyses. Three-dimensional (3D) geometric documentation is the first step in developing the digital twin, and various equipment and methodologies have been developed to facilitate the procedure. Both aerial and terrestrial close-range photogrammetry can be combined with 3D laser scanning and geodetic methods for the accurate 3D geometric documentation. The data processing procedure in these cases mostly focuses on developing detailed, accurate 3D models that can be used for the FE modeling. The final 3D surface or volumes are produced mainly by combining the 3D point clouds obtained from the laser scanner and the photogrammetric methods. 3D FE models can be developed based on the geometries derived from the 3D models using FE software packages. As an alternative, developed 3D volumes provided in the previous step can be directly imported to some FE software packages. In this study, the challenges and strategies of each step are investigated by providing examples of surveyed heritage structures.

Terrestrial photogrammetry: a method to gather data on fractures for DFN modelling from exposed rock surfaces

Abstract. The stochastic generation of discrete fracture networks (DFN) is a method for modelling fracture patterns used to assess the in situ fragmentation in a volume of rock. The DFN modelling approach is based on the assumption that the natural fragmentation of rocks is a function of the length and connectivity of the fractures within the considered volume of rock. Thus, in order to generate a site-specific DFN, the primary geometric properties of the fracture surfaces within the rock volume (especially orientation, size and fracture intensity as well as the local spatial variability) must be defined as distribution functions (Elmo et al., 2014). The required base statistics are usually obtained from fracture analysis on boreholes, exposed rock surfaces or (to a limited extent) 3D seismics (e.g. Bisdom et al., 2014; Bemis et al., 2014). We adopted a terrestrial close-range photogrammetry approach to capture several outcrops and analyse fracture traces on the exposed rock surfaces, the chosen workflow is based around the use of free and open-source software. Images were acquired from several quarries in the Weschnitzpluton, a granodioritic to quartz monzodioritic pluton in the Bergstrasse Odenwald (e.g. Altherr et al., 1999) using a consumer-grade Nikon D5300 DSLR with fixed focal length instead of a drone or Lidar-system for legal reasons, partially tree-lined outcrops and cost efficiency. Since point clouds obtained from photogrammetry are inherently dimensionless, we used a spherical target with compass and bubble level for scale and proper spatial orientation (Froideval et al., 2019). The exact geolocation is not particularly important for the task, so the use of GPS, total station or georeferenced ground control points is not necessary. Dense point clouds were computed using the open source SfM photogrammetry suite Meshroom (AliceVision, 2021), which can be used for manual or semi-automatic detection of fracture surfaces and their orientation (Schnabel et al., 2007) and to generate orthorectified images of the rock surface to trace fracture lengths and nodes in a GIS (Nyberg et al., 2018). Our investigations proved terrestrial photogrammetry to be a valuable and easily accessible tool in the documentation of natural fracture patterns and a robust base for the generation of DFN networks.

Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R2) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m3, rBias was 18.73%, RMSE was 0.12369 m3, rRMSE was 32.78%. To better evaluate the accuracy of QSM’s reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m3, and the rBias was −13.44%, RMSE was 0.13267 m3, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds.

Mathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands

Terrestrial close-range photogrammetry offers a low-cost method of three-dimensional (3D) reconstruction of forest stands that provides automatically processable 3D data that can be used to evaluate inventory parameters of forest stands and individual trees. However, fundamental methodological problems in image acquisition and processing remain. This study enhances the methodology of photogrammetric Structure from Motion reconstruction of forest stands by determining the best photographer's trajectory for image acquisition. The study comprises 1) mathematical optimization of the route in a square grid using integer programming, 2) evaluation of point clouds derived from sequences of real photographs, simulating different trajectories, and 3) verification on real trajectories. In a forest research plot, we established a 1 m square grid of 625 (i.e., 25 × 25) photographic positions, and at each position, we captured 16 photographs in uniformly spaced directions. We adopted real tree positions and diameters, and the coordinates of the photographic positions, including orientation angles of captured images, were recorded. We then formulated an integer programming optimization model to find the most efficient trajectory that provided coverage of all sides of all trees with sufficient counts of images. Subsequently, we used the 10,000 captured images to produce image subsets simulating image sequences acquired during the photographer's movement along 84 different systematic trajectories of seven patterns based on either parallel lines or concentric orbits. 3D point clouds derived from the simulated image sequences were evaluated for their suitability for automatic tree detection and estimation of diameters at breast height. The results of the integer programming model indicated that the optimal trajectory consisted of parallel line segments if the camera is pointed forward – in the travel direction, or concentric orbits if the camera is pointed to a side – perpendicular to the travel direction. With point clouds derived from the images of the simulated trajectories, the best diameter estimates on automatically detected trees were achieved with trajectories consisting of parallel lines in two perpendicular directions where each line was passed in both opposite directions. For efficient image acquisition, resulting in point clouds of reasonable quality with low counts of images, a trajectory consisting of concentric orbits, including the plot perimeter with the camera pointed towards the plot center, proved to be the best. Results of simulated trajectories were verified with the photogrammetric reconstruction of the forest stand based on real trajectories for six patterns. The mathematical optimization was consistent with the results of the experiment, which indicated that mathematical optimization may represent a valid tool for planning trajectories for photogrammetric 3D reconstruction of scenes in general.

QUICK 3D WITH UAV AND TOF CAMERA FOR GEOMORPHOMETRIC ASSESSMENT

Abstract. Most of the high resolution topographic models are currently obtained either by means of Light Detection and Ranging (LiDAR) or photogrammetry: the former is usually preferred for producing very accurate models, whereas the latter is much more frequently used in low cost applications. In particular, the availability of more affordable Unmanned Aerial Vehicles (UAVs) equipped with high resolution cameras led to a dramatic worldwide increase of UAV photogrammetry-based 3D reconstructions. Nevertheless, accurate high resolution photogrammetric reconstructions typically require quite long data processing procedures, which make them less suitable for real-time applications.This work aims at investigating the use of a low cost Time of Flight (ToF) camera, combined with an Ultra-Wide Band (UWB) positioning system, mounted on a drone, in order to enable quasi real time 3D reconstructions of small to mid-size areas, even in locations where Global Navigation Satellite Systems (GNSSs) are not available.The proposed system, tested on a small area on the Italian Alps, provided high resolution mapping results, with an error of few centimeters with respect to a terrestrial close-range photogrammetry survey conducted on the same day.

Non-Deterministic Assessment of Surface Roughness as Bond Strength Parameters between Concrete Layers Cast at Different Ages.

The importance of surface roughness and its non-destructive examination has often been emphasised in structural rehabilitation. The presented innovative procedure enables the estimation of concrete-to-concrete strength based on a combination of low-cost, area-limited tests and geostatistical methods. The new method removes the shortcomings of the existing one, i.e., it is neither qualitative nor subjective. The interface strength factors, cohesion and friction, can be estimated accurately based on the collected data on a surface texture. The data acquisition needed to create digital models of the concrete surface can be performed by terrestrial close-range photogrammetry or other methods. In the presented procedure, limitations to the availability of concrete surfaces are overcome by the generation of subsequential Gaussian random fields (via height profiles) based on the semivariograms fitted to the digital surface models. In this way, the randomness of the surface texture is reproduced. The selected roughness parameters, such as mean valley depth and, most importantly, the geostatistical semivariogram parameter sill, were transformed into contact bond strength parameters based on the available strength tests. The proposed procedure estimates the interface bond strength based on the geostatistical methods applied to the numerical surface model and can be used in practical and theoretical applications.

Application of Terrestrial Close-Range Photogrammetry for Estimating Stem Volume of Tree Species in Subtropical Forest in Okinawa, Japan

Application of Terrestrial Close-Range Photogrammetry for Estimating Stem Volume of Tree Species in Subtropical Forest in Okinawa, Japan

Mapping Forest Structure Using UAS inside Flight Capabilities.

We evaluated two unmanned aerial systems (UASs), namely the DJI Phantom 4 Pro and DJI Mavic Pro, for 3D forest structure mapping of the forest stand interior with the use of close-range photogrammetry techniques. Assisted flights were performed within two research plots established in mature pure Norway spruce (Picea abies (L.) H. Karst.) and European beech (Fagus sylvatica L.) forest stands. Geotagged images were used to produce georeferenced 3D point clouds representing tree stem surfaces. With a flight height of 8 m above the ground, the stems were precisely modeled up to a height of 10 m, which represents a considerably larger portion of the stem when compared with terrestrial close-range photogrammetry. Accuracy of the point clouds was evaluated by comparing field-measured tree diameters at breast height (DBH) with diameter estimates derived from the point cloud using four different fitting methods, including the bounding circle, convex hull, least squares circle, and least squares ellipse methods. The accuracy of DBH estimation varied with the UAS model and the diameter fitting method utilized. With the Phantom 4 Pro and the least squares ellipse method to estimate diameter, the mean error of diameter estimates was −1.17 cm (−3.14%) and 0.27 cm (0.69%) for spruce and beech stands, respectively.

3D MODELLING OF A HISTORICAL BUILDING USING CLOSE-RANGE PHOTOGRAMMETRY AND REMOTELY PILOTED AIRCRAFT SYSTEM (RPAS)

Abstract. The photogrammetric survey of architectural Cultural Heritage is a very useful and standard process in order to obtain accurate 3D data for the documentation and visualization of historical buildings. In particular, the integration of terrestrial close-range photogrammetry and Remotely Piloted Aircraft Systems (RPASs) photogrammetry allows to create accurate and reliable 3D models of buildings and to monitor their state of conservation. The use of RPASs has indeed become more popular in Cultural Heritage survey to measure and detect areas that cannot normally be covered using terrestrial photogrammetry or terrestrial laser scanner. The paper presents the results of a photogrammetric survey executed to document the monumental complex of Villa Lampedusa ai Colli in Palermo (Italy), one of the most important historical buildings of the town. An integrated survey by close-range photogrammetry and RPAS photogrammetry was planned and carried out to reconstruct the 3D digital model of the monumental complex. Different images configurations (terrestrial, aerial nadiral, aerial parallel and oblique to the façades) have been acquired; data have been processed to verify the accuracy of the photogrammetric survey as regards the camera calibration parameters and the number of Ground Control Points (GCPs) measured on building façades. A very detailed 3D digital model and high-resolution ortho-images of the façades were obtained in order to carry out further analysis for historical studies, conservation and restoration project. The final 3D model of Villa Lampedusa ai Colli has been compared with a laser scanner 3D model to evaluate the quality of the photogrammetric approach. Beyond a purely metric assessment, 3D textured model has employed to generate 2D representations, useful for documentation purpose and to highlight the most significant damaged areas. 3D digital models and 2D representations can effectively contribute to monitor the state of conservation of historical buildings and become a very useful support for preliminary restoration works.

DEM GENERATION FROM CLOSE-RANGE PHOTOGRAMMETRY USING EXTENDED PYTHON PHOTOGRAMMETRY TOOLBOX

Abstract. Digital elevation models (DEMs) are widely used raster data for different applications concerning terrain, such as for flood modelling, viewshed analysis, mining, land development, engineering design projects, to name a few. DEMs can be obtained through various methods, including topographic survey, LiDAR or photogrammetry, and internet sources. Terrestrial close-range photogrammetry is one of the alternative methods to produce DEMs through the processing of images using photogrammetry software. There are already powerful photogrammetry software that are commercially-available and can produce high-accuracy DEMs. However, this entails corresponding cost. Although, some of these software have free or demo trials, these trials have limits in their usable features and usage time. One alternative is the use of free and open-source software (FOSS), such as the Python Photogrammetry Toolbox (PPT), which provides an interface for performing photogrammetric processes implemented through python script. For relatively small areas such as in mining or construction excavation, a relatively inexpensive, fast and accurate method would be advantageous. In this study, PPT was used to generate 3D point cloud data from images of an open pit excavation. The PPT was extended to add an algorithm converting the generated point cloud data into a usable DEM.

UAV oblique photogrammetry and lidar data acquisition for 3D documentation of the Hercules Fountain

This paper discusses some enhancements concerning 3D modelling, and the integration and comparison of 3D data from aerial and terrestrial sensors, developed by innovative geomatics techniques around the metric documentation of cultural heritage. In archaeology, it is interesting to deal with the considerable advantages of new multi-sensor approaches for the data acquisition and the management phases in terms of the sustainability (automated acquisition, quickness, precision, time and cost cutting). In particular, Unmanned Aerial Vehicles(UAVs)photogrammetry with the joint use of nadir and oblique cameras can be usefully combined with the large-scale details acquired by the terrestrial Light Detection and Ranging (LiDAR)in vast areas or complex objects, especially in mostly vertical sized objects. Here, we will report the results of an integrated 3D survey in an archaeological context in the Piedmont region of Italy. The Hercules Fountain is located in the gardens of the Venaria Reale (a Savoy Royal Palace included in the UNESCO heritage list) and has witnessed several events and historical phases during the past centuries–from its construction in the 16thcentury to its disuse and decline in the 17thcentury, right up to the 21stcentury when it was eventually brought back to light. The goal of the test is the creation of a3D continuous model of the site for documentation purposes, future consolidation, and enhancement projects finalised fora public promotion. To meet these strategic aims, a terrestrial laser scanning (TLS henceforth) survey has been designed together with multi-flights by a multi-rotor UAV and terrestrial close-range photogrammetry (CRP) acquisition to produce a highly detailed 3D textured model from which we have inferred standard 2D drawings, digital orthoimages, and further 3D products. In conclusion, the entire workflow and the outputs have been compared together to evaluate the effectiveness of each elaboration according to the different goals of the survey.

CLOSE RANGE UAV ACCURATE RECORDING AND MODELING OF ST-PIERRE-LE-JEUNE NEO-ROMANESQUE CHURCH IN STRASBOURG (FRANCE)

Abstract. Close-range photogrammetry is an image-based technique which has often been used for the 3D documentation of heritage objects. Recently, advances in the field of image processing and UAVs (Unmanned Aerial Vehicles) have resulted in a renewed interest in this technique. However, commercially ready-to-use UAVs are often equipped with smaller sensors in order to minimize payload and the quality of the documentation is still an issue. In this research, two commercial UAVs (the Sensefly Albris and DJI Phantom 3 Professional) were setup to record the 19th century St-Pierre-le-Jeune church in Strasbourg, France. Several software solutions (commercial and open source) were used to compare both UAVs’ images in terms of calibration, accuracy of external orientation, as well as dense matching. Results show some instability in regards to the calibration of Phantom 3, while the Albris had issues regarding its aerotriangulation results. Despite these shortcomings, both UAVs succeeded in producing dense point clouds of up to a few centimeters in accuracy, which is largely sufficient for the purposes of a city 3D GIS (Geographical Information System). The acquisition of close range images using UAVs also provides greater LoD flexibility in processing. These advantages over other methods such as the TLS (Terrestrial Laser Scanning) or terrestrial close range photogrammetry can be exploited in order for these techniques to complement each other.

Forest Stand Inventory Based on Combined Aerial and Terrestrial Close-Range Photogrammetry

In this article we introduce a new method for forest management inventories especially suitable for highly-valued timber where the precise estimation of stem parameters (diameter, form, and tapper) plays the key role for market purposes. The unmanned aerial system (UAS)-based photogrammetry is combined with terrestrial photogrammetry executed by walking inside the stand and the individual tree parameters are estimated. We compare two automatic methods for processing of the point clouds and the delineation of stem circumference at breast height. The error of the diameter estimation was observed to be under 1 cm root mean square error (RMSE) and the height estimation error was 1 m. Apart from the mentioned accuracy, the main advantage of the proposed work is shorter time demand for field measurement; we could complete both inventories of 1 hectare forest stand in less than 2 h of field work.

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Airborne laser scanning (ALS) allows for extensive coverage, but the accuracy of tree detection and form can be limited. Although terrestrial laser scanning (TLS) can improve on ALS accuracy, it is rather expensive and area coverage is limited. Multi-view stereopsis (MVS) techniques combining computer vision and photogrammetry may offer some of the coverage benefits of ALS and the improved accuracy of TLS; MVS combines computer vision research and automatic analysis of digital images from common commercial digital cameras with various algorithms to reconstruct three-dimensional (3D) objects with realistic shape and appearance. Despite the relative accuracy (relative geometrical distortion) of the reconstructions available in the processing software, the absolute accuracy is uncertain and difficult to evaluate. We evaluated the data collected by a common digital camera through the processing software (Agisoft PhotoScan ©) for photogrammetry by comparing those by direct measurement of the 3D magnetic motion tracker. Our analyses indicated that the error is mostly concentrated in the portions of the tree where visibility is lower, i.e., the bottom and upper parts of the stem. For each reference point from the digitizer we determined how many cameras could view this point. With a greater number of cameras we found increasing accuracy of the measured object space point positions (as expected), with a significant positive change in the trend beyond five cameras; when more than five cameras could view this point, the accuracy began to increase more abruptly, but eight cameras or more provided no increases in accuracy. This method allows for the retrieval of larger datasets from the measurements, which could improve the accuracy of estimates of 3D structure of trees at potentially reduced costs.

4D CITY TRANSFORMATIONS BY TIME SERIES OF AERIAL IMAGES

Abstract. Recent photogrammetric applications, based on dense image matching algorithms, allow to use not only images acquired by digital cameras, amateur or not, but also to recover the vast heritage of analogue photographs. This possibility opens up many possibilities in the use and enhancement of existing photos heritage. The research of the original figuration of old buildings, the virtual reconstruction of disappeared architectures and the study of urban development are some of the application areas that exploit the great cultural heritage of photography. Nevertheless there are some restrictions in the use of historical images for automatic reconstruction of buildings such as image quality, availability of camera parameters and ineffective geometry of image acquisition. These constrains are very hard to solve and it is difficult to discover good dataset in the case of terrestrial close range photogrammetry for the above reasons. Even the photographic archives of museums and superintendence, while retaining a wealth of documentation, have no dataset for a dense image matching approach. Compared to the vast collection of historical photos, the class of aerial photos meets both criteria stated above. In this paper historical aerial photographs are used with dense image matching algorithms to realize 3d models of a city in different years. The models can be used to study the urban development of the city and its changes through time. The application relates to the city centre of Verona, for which some time series of aerial photographs have been retrieved. The models obtained in this way allowed, right away, to observe the urban development of the city, the places of expansion and new urban areas. But a more interesting aspect emerged from the analytical comparison between models. The difference, as the Euclidean distance, between two models gives information about new buildings or demolitions. As considering accuracy it is necessary point out that the quality of final observations from model comparison depends on several aspects such as image quality, image scale and marker accuracy from cartography.