Photogrammetric Reconstruction Research Articles

Wounded to death. Holistic, multimodal reconstruction of the dynamics in a case of multiple perimortem cranial injuries from a medieval site in northern Italy

The current study focuses on the remains of an adult male individual unearthed during archaeological excavations inside the church of San Biagio in Cittiglio (Northern Italy). The skull displayed four lesions in the form of defects in the cranium that involved the occipital squama, the right nuchal portion, the right parietal, and the right occipito-mastoid area. At macroscopic observation, the lesions showed polished surfaces, sharp margins, V-shaped cross-sections, and evidence of parallel microstriations.The investigation required a multi-analytical approach, which combined macroscopic assessment, computed tomography, photogrammetric three-dimensional reconstruction, and 3D digital microscopy that allowed us to obtain a morphometric characterization of the evidence. Our objective was to reconstruct the dynamics of an ancient violent event by applying a modern scientific approach to the analysis of the injuries observed in the skull of an osteoarchaeological individual.Digital microscopy allowed us to evaluate the micromorphometric aspect of the lesions, and to obtain microscopic quantitative data such as linear and angular measurements in the three dimensions. The complete absence of bone reaction at the site of the lesions revealed the perimortem nature of the injuries. Through the holistic, combined approach employed in the current study it was concluded that this individual was most likely struck four times in rapid succession from behind with a straight bladed implement, consistent in form with a long sword of the time. At the end of our study, it was possible to reconstruct the dynamics for each lesion and to hypothesize the reconstructive sequence of the violent event.

Concrete dam damage detection and localisation based on YOLOv5s-HSC and photogrammetric 3D reconstruction

This paper presents a system for detecting damages in concrete dams that combines the proposed YOLOv5s-HSC algorithm and a three-dimensional (3D) photogrammetric reconstruction method to accurately identify and locate objects. Since the damages usually have complex background and blurred boundaries, Swin transformer blocks and coordinate attention modules were introduced to improve the ability of feature extraction. The mean average precision (mAP) value of the improved algorithm increased by 3.8% and exhibited a reasonably robust performance for both small objects and a considerable detection effect. Subsequently, to realize the localization of the detected damages and mapped to the corresponding positions, the projecting method was proposed by calculating the intersection of the ray from camera center and 3D photogrammetric reconstruction model generated from the same images as for detection. The results confirmed that the proposed method is appropriate for detecting damages and recording locations for intuitively exhibiting concrete dam damages.

Combination of close-range and aerial photogrammetry with terrestrial laser scanning to answer microbiological and climatological questions in connection with lava caves

Abstract Combining photogrammetric reconstruction (close-range photogrammetry, CRP) and airborne photogrammetry through the structure from motion method (SFM) with terrestrial three-dimensional (3D) laser scanning (TLS), Maelstrom Cave on Big Island, Hawaii (USA), was mapped in three dimensions. The complementary properties of the two methods generated an overall model that depicted significant features of the cave both spatially and visually. Through various processes, the complex geometric quantities were derived from the model that can be used to answer microbiological and climatological questions. In this report, the procedure for the three-dimensional acquisition of the terrain surface above Maelstrom Cave as well as the interior of the cave with TLS and SFM is described. It is shown how the different data sets were combined and contrasted, including a comparison of geometries from the different survey operations. Finally, the editing processes used to quantify and simplify the cave geometry are presented, as well as the analysis of the ellipses generated accordingly to determine the geometric quantities. Through the analysis of the cave geometry, important geometric properties of the Maelstrom Cave could be quantified and categorized. In this way, an effective tool was developed to directly correlate the structure of the cave system with climatological and microbiological parameters in order to answer the corresponding questions.

Low-cost photogrammetric reconstruction of a panel with palaeolithic engravings of Siega Verde (Salamanca, Spain): From the rocky outcrop to the details

The goal of this work is the photogrammetric reconstruction of a rocky outcrop with a panel decorated with palaeolithic engravings of the Siega Verde archaeological site (Salamanca, Spain) using photographs obtained with mobile phone cameras.The engravings present in this panel have been previously studied and published. The main objective of this work is the generation of 3D models by low-cost photogrammetry that allow the diffusion and study of the panel.The processing is approached at different quality levels with different photosets to provide the reconstruction of the complete rocky outcrop, the decorated wall, and the details of the engravings. The reconstruction of the rocky outcrop provides interactive 3D models useful to appreciate the morphology and the context of the engraved wall. The reconstruction of the decorated wall, after referencing, permits measurements with errors in the millimetre range and was used to obtain objective and subjective tracings of the engraved motifs. The highest quality level of photogrammetric processing makes it possible to determine the morphology, direction, and dimensions of the pecks and even depths and widths of the individual pecks.

THE USE OF OPEN SOURCE SOFTWARE FOR MONITORING BEE DIVERSITY IN NATURAL SYSTEMS: THE BEEMS PROJECT

Abstract. This work wants to highlight the results obtained during the BEEMS (Monitoring Bee Diversity in Natural System) project, which the main goal was to answer the following question: Which biotic and abiotic indicators of floral and nesting resources best reflect the diversity of bee species and community composition in the Israeli natural environment? The research was oriented towards the cost-effectiveness analysis of new aerial geomatics techniques and classical ground-based methods for collecting the indicators described above, based only on open-source software for data analysis. Two complementary study systems in central Israel have been considered: the Alexander Stream National Park, an area undergoing an ecological restoration project in a sandy ecosystem, and the Judean foothills area, to the South of Tel Aviv. In each study system, different surveys of bees, flowers, nesting substrates and soil, using classical field measurement methods have been conducted. Simultaneously, an integrated aero photogrammetric survey, acquiring different spectral responses of the land surface by means of Uncrewed Aerial Vehicle (UAV) imaging systems have been performed. The multispectral sensors have provided surface spectral response out of the visible spectrum, while the photogrammetric reconstruction has provided three-dimensional information. Thanks to Artificial Intelligence algorithms and the richness of the data acquired, a methodology for Land Cover Classification has been developed. The results obtained by ground surveys and advanced geomatics tools have been compared and overlapped. The results are promising and show a good fit between the two approaches, and high performance of the geomatics tools in providing valuable ecological data.

Photogrammetric reconstruction of 3D carpological collection in high resolution for plants authentication and species discovery.

This study provides an accurate and efficient method to reconstruct detailed and high-resolution digital 3D models of carpological materials by photogrammetric method, in which only about 100 to 150 images are required for each model reconstruction. The 3D models reflect the realistic morphology and genuine color of the carpological materials. The 3D models are scaled to represent the true size of the materials even as small as 3 mm in diameter. The interfaces are interactive, in which the 3D models can be rotated in 360° to observe the structures and be zoomed to inspect the macroscopic details. This new platform is beneficial for developing a virtual herbarium of carpological collection which is thus the most important to botanical authentication and education.

The Influence of Image Properties on High-Detail SfM Photogrammetric Surveys of Complex Geometric Landforms: The Application of a Consumer-Grade UAV Camera in a Rock Glacier Survey

The detailed description of processing workflows in Structure from Motion (SfM) surveys using unmanned aerial vehicles (UAVs) is not common in geomorphological research. One of the aspects frequently overlooked in photogrammetric reconstruction is image characteristics. In this context, the present study aims to determine whether the format or properties (e.g., exposure, sharpening, lens corrections) of the images used in the SfM process can affect high-detail surveys of complex geometric landforms such as rock glaciers. For this purpose, images generated (DNG and JPEG) and derived (TIFF) from low-cost UAV systems widely used by the scientific community are applied. The case study is carried out through a comprehensive flight plan with ground control and differences among surveys are assessed visually and geometrically. Thus, geometric evaluation is based on 2.5D and 3D perspectives and a ground-based LiDAR benchmark. The results show that the lens profiles applied by some low-cost UAV cameras to the images can significantly alter the geometry among photo-reconstructions, to the extent that they can influence monitoring activities with variations of around ±5 cm in areas with close control and over ±20 cm (10 times the ground sample distance) on surfaces outside the ground control surroundings. The terrestrial position of the laser scanner measurements and the scene changing topography results in uneven surface sampling, which makes it challenging to determine which set of images best fit the LiDAR benchmark. Other effects of the image properties are found in minor variations scattered throughout the survey or modifications to the RGB values of the point clouds or orthomosaics, with no critical impact on geomorphological studies.

Fast and Accurate Registration of Terrestrial Point Clouds Using a Planar Approximation of Roof Features

3D reconstructed models are becoming more diffused daily, especially in the Cultural Heritage field. These geometric models are typically obtained from elaborating a 3D point cloud. A significant limit in using these methods is the realignment of different point clouds acquired from different acquisitions, particularly for those whose dimensions are millions of points. Although several methodologies have tried to propose a solution for this necessity, none of these seems to solve definitively the problems related to the realignment of large point clouds. This paper presents a new and innovative procedure for the fine registration of large point clouds. The method performs an alignment by using planar approximations of roof features, taking the roof’s extension into account. It looks particularly suitable for the alignment of large point clouds acquired in urban and archaeological environments. The proposed methodology is compared in terms of accuracy and time with a standard photogrammetric reconstruction based on Ground Control Points (GCPs) and other ones, aligned by the Iterative Closest Point method (ICP) and markers. The results evidence the excellent performance of the methodology, which could represent an alternative for aligning extensive photogrammetric reconstructions without the use of GCPs.

LANDSLIDE SURVEYS USING LOW-COST UAV AND FOSS PHOTOGRAMMETRIC WORKFLOW

Abstract. Unmanned Aerial Vehicle have found their usage in various academic and industry domains, mainly due to the versatility of options that one aircraft can offer from onboard sensors for data acquisition and positioning, through different weight and size categories allowing different applications, including landslide mapping and surveying. Survey-grade UAVs can provide very precise flight and data but usually are very costly, and their use can be further bounded by many regulations. In this work, we have adopted a low-cost consumer-grade UAV to do multitemporal monitoring of an active landslide (Ruinon) in Northern Italy to evaluate the applicability of such setup in the landslide hazard domain. Moreover, for flight planning, photogrammetric reconstruction, and comparative analyses we have adopted free and open-source software solutions. The resulted dense point clouds and orthophotos yielded very satisfactory results from accuracies of few meters and even sub-meter level when reconstructed with field-surveyed ground control points. As a result, from the two surveys comparisons, July and October 2021, several displaced boulders and debris were detected where no significant reactivations were detected from our surveys. Such low-cost setup can be used also from non-professionals and in citizen science campaigns which can significantly contribute to additional landslide mapping and analyses by providing valuable datasets.

INTEGRATION OF UAV-LIDAR AND UAV-PHOTOGRAMMETRY FOR INFRASTRUCTURE MONITORING AND BRIDGE ASSESSMENT

Abstract. The health assessment of strategic infrastructures and bridges represents a critical variable for planning appropriate maintenance operations. The high costs and complexity of traditional periodical monitoring with elevating platforms have driven the search for more efficient and flexible methods. Indeed, recent years have seen the growing diffusion and adoption of non-invasive approaches consisting in the use of Unmanned Aerial Vehicles (UAVs) for applications that range from visual inspection with optical sensors to LiDAR technologies for rapid mapping of the territory. This study defines two different methodologies for bridge inspection. A first approach involving the integration of traditional topographic and GNSS techniques with TLS and photogrammetry with cameras mounted on UAV was compared with a UAV-LiDAR method based on the use of a DJI Matrice 300 equipped with a LiDAR DJI Zenmuse L1 sensor for a manual flight and an automatic one. While the first workflow resulted in a centimetric accurate but time-consuming model, the UAV-LiDAR resulting point cloud’s georeferencing accuracy resulted to be less accurate in the case of the manual flight under the bridge for GNSS signal obstruction. However, a photogrammetric model reconstruction phase made with Ground Control Points and photos taken by the L1-embedded camera improved the overall accuracy of the workflow, that could be employed for flexible low-cost mapping of bridges when medium level accuracy (5–10 cm) is accepted. In conclusion, a solution for integrating interactively final 3D products in a Bridge Management System environment is presented.

REMOTE SURVEY OF TRADITIONAL DWELLINGS USING ADVANCED PHOTOGRAMMETRY INTEGRATED WITH ARCHIVAL DATA: THE CASE OF LISBON

Abstract. The application of advanced photogrammetry and the integration of cross-sourced maps of historic cityscapes contribute to a thorough understanding of our surrounding, enabling the comparison between present physical layout/use of the built environment and its changes over time. Remote surveys integrated with the analysis of building dossiers, stored in municipal archives, and onsite surveys are carried out in this work for providing insight into a traditional building typology in Portugal, which is so far overlooked in heritage studies. Two examples of humble multi-family dwellings with overhanging timber-framed façades (16th century) are virtually reconstructed using structure-from-Motion (SfM) of selected historic photographs. During a first phase, a photogrammetric reconstruction of the state of the buildings, as conceived originally, was implemented by reconstructing two parts (due to the number of images available for each case study), and then a metric evaluation of the models was conducted comparing past and current state of the buildings. This research shows the importance of integrating distinct tools and databases to foster truly tourists' perception of authenticity in cultural heritage sites and towards a more sensitive heritage management. Potential interactive applications capable of increasing the visibility and impact of these virtual reconstructions, such as GIS data enrichment or digital travel apps, are also briefly discussed.

CONTRIBUTION OF SUPER RESOLUTION TO 3D RECONSTRUCTION FROM PAIRS OF SATELLITE IMAGES

Abstract. The photogrammetric 3D stereo reconstruction from pairs of strereo images is rising interest in the past few years in space field downstream. Nowadays, it is conceivable that a large production of DSMs from satellite images can become the primary source of 3D information on a global scale. However, in urban areas, DSMs produced with current technology suffer from poor quality. Indeed, even using very high resolution (VHR) images, there is too little information to generate disparity maps that reproduce very well defined shaped objects such as buildings.To address this issue, one solution may be to artificially increase image resolution beyond the sensor limits. Super resolution (SR) algorithms are designed to recover high frequencies, introducing significant information in a scene characterized by strong and frequent discontinuities such as a city. State-of-the-art methods relying on Deep Learning have shown remarkable results in this sense. The aim of this work is therefore to assess the contribution of single image SR Deep Learning techniques to the stereo matching and DSMs generation in an urban context, highlighting potential advantages and limitations that can show up when introducing such a technology in a multi-view stereo pipeline. The proposed contributions are: a methodology for super resolution of VHR data that takes into account realistic simulation of a satellite product; a testbed for the evaluation of the impact of super resolution on 3D photogrammetric reconstruction; a local analysis of the consequences of deep learning SR of VHR images on stereo matching.

ODYN: AN ONLINE DYNAMIC NETWORK SOLVER FOR PHOTOGRAMMETRY AND LIDAR GEO-REFERENCING

Abstract. In recent years, many methods have been proposed to improve the quality of the estimated trajectories for airborne or terrestrial mapping platforms leveraging multi-sensor fusion. One of the motivating applications is, for example, the use laser scanners on small unmanned aerial vehicles, where the typically employed low-cost MEMS inertial sensors do not allow for satisfactory direct geo-referencing of the laser points. In this work we introduce ODyN, an online Dynamic Network solver that can fuses information from cameras, GNSS and inertial sensors in a single adjustment. It can be employed to estimate a high-frequency trajectory for precise direct geo-referencing, to improve photogrammetric reconstructions in challenging scenarios or to determine several types of system calibration parameters. The presented solver is hosted by the University of Geneva and is free for anybody to use. In this work we present a use case in airborne mapping where the obtained trajectory estimates are improved with respect to the recursive smoothing approaches conventionally used in direct geo-referencing.

Integration and Comparison Methods for Multitemporal Image-Based 2D Annotations in Linked 3D Building Documentation

Data acquisition systems and methods to capture high-resolution images or reconstruct 3D point clouds of existing structures are an effective way to document their as-is condition. These methods enable a detailed analysis of building surfaces, providing precise 3D representations. However, for the condition assessment and documentation, damages are mainly annotated in 2D representations, such as images, orthophotos, or technical drawings, which do not allow for the application of a 3D workflow or automated comparisons of multitemporal datasets. In the available software for building heritage data management and analysis, a wide range of annotation and evaluation functions are available, but they also lack integrated post-processing methods and systematic workflows. The article presents novel methods developed to facilitate such automated 3D workflows and validates them on a small historic church building in Thuringia, Germany. Post-processing steps using photogrammetric 3D reconstruction data along with imagery were implemented, which show the possibilities of integrating 2D annotations into 3D documentations. Further, the application of voxel-based methods on the dataset enables the evaluation of geometrical changes of multitemporal annotations in different states and the assignment to elements of scans or building models. The proposed workflow also highlights the potential of these methods for condition assessment and planning of restoration work, as well as the possibility to represent the analysis results in standardised building model formats.

Exploiting Light Directionality for Image‐Based 3D Reconstruction of Non‐Collaborative Surfaces

AbstractThree‐dimensional (3D) measurement of non‐collaborative surfaces is still an open research topic. This paper investigates and quantifies for the first time the effect of light directionality and fusion of multiple images as a method to improve the quality of photogrammetric 3D reconstruction. For this aim, an image acquisition system that employs multiple light sources was developed to highlight the roughness and microstructures of the object under investigation. Images were captured at various grazing angles to highlight the local surface roughness and microstructures. Individual point clouds, created using images taken at different grazing angles, were produced using dense image‐matching techniques. These point clouds were then compared against different 3D photogrammetric reconstructions obtained from a pre‐processing of the acquired images based on diffuse lighting, median and average images. Experiments showed that exploiting light directionality significantly improves image‐matching quality. Furthermore, depending on the light direction, the root mean square (RMS) error of the 3D surfaces obtained using the proposed system were up to 50% less than those created by traditional diffuse lighting.

Probabilistic assessment of slope stability using photogrammetric 3D reconstruction: a novel approach

Probabilistic assessment of slope stability using photogrammetric 3D reconstruction: a novel approach

Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites’ average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of closing the scale gap between discrete point measurements and regional-scale remote sensing and complements large-scale remote sensing data and snow model output with an adequate validation source.

A Comparative Analysis of Unmanned Aircraft Systems in Low Altitude Photogrammetric Surveys

Comparing photogrammetric performances of four user-grade unmanned aircraft systems (UAS) is the main aim of this paper. This study investigates what is the more suitable UAS for specific applications considering the required scale factor, such as for architectural, environmental and restoration purposes. Some photogrammetric surveys were conducted in a 5 ha area using a Phantom 4 Adv, Mavic 2 Pro, Mavic Air 2 and Mavic Mini 2. These unmanned aircrafts are commercial systems used mainly by private professionals. Some photogrammetric reconstructions were carried out by varying flight altitude and camera settings of the 4 UAS. Structure-from-motion (SfM) algorithms were applied to the images taken from the UASs. The surveys’ quality was analyzed by comparing the ground targets’ coordinates measured on the field with indirect georeferencing through global navigation satellite system (GNSS). Fifty targets were installed and arranged following a kind of regular grid. For each photogrammetric flight, the boundary conditions were maintained the same, as well as the flight trajectories and the ground control point distribution. Altimetric and planimetric residuals were reported and compared for each photogrammetric survey. Using a regular grid of ground targets, the result obtained from Phantom 4 is one order of magnitude better than the ones obtained from the other UASs. Mavic Mini 2 leads to an error average of about 5 cm. Remembering that the Mavic Mini 2 is an ultralight drone (it does not require a pilot’s license), it could significantly reduce costs compared to all the others.

Insights into seafloor litter spatiotemporal dynamics in urbanized shallow Mediterranean bays. An optimized monitoring protocol using towed underwater cameras

Monitoring of marine litter at the sea surface, the beaches and the seafloor is essential to understanding their sources, pathways and sinks and design effective clean-up programs or increase public awareness for reducing litter waste. Up until today, seafloor litter is the least exploited component of marine litter. Although the protocols for recording and assessing seafloor litter in the deep-sea environments are currently being actively defined and practiced, shallow seafloor litter survey protocols are still notably under-developed. Moreover, trawling for fishing, which is the main means for collecting seafloor litter data, needs to be phased out in the coming years due to its high environmental footprint and be replaced by less destructive ways based on underwater imagery. In this paper we propose an integrated approach for assessing in detail the spatiotemporal distribution and composition of seafloor litter in shallow coastal environments, using common towed underwater cameras. Effort has been put to correctly estimating spatial litter densities regarding the true coverage of the visualized area, which was efficiently extracted through photogrammetric reconstruction of the seafloor. Interpretation of the spatial distribution of litter was aided by auxiliary bathymetric and swath sonar backscatter datasets, to determine the seabed geomorphological features that control their dispersion and composition. Local geo-morphology, along with any reported coastal anthropogenic activity, are correlated to seafloor litter densities to investigate the temporal and spatial dynamics that control their distribution and temporal trends in Syros Island, Cyclades, Greece. There, in the context of LIFE DEBAG project, monitoring of an urbanized shallow bay for 3 consecutive years has been performed to assess the impact of an intensive local awareness raising campaign to the local environment. A significant reduction of litter densities under the impact of this campaign has been documented, while links between the seafloor litter transport dynamics and the seabed micro- and macro-topography were made evident. Monitoring litter densities on the seafloor of urbanized shallow bays proved to be a prospective way of tracking marine litter pressures on the local marine environment.

Performing low-altitude photogrammetric surveys, a comparative analysis of user-grade unmanned aircraft systems

This paper shows results of comparing performances of four unmanned aircraft systems (UAS) in terms of photogrammetric survey’s quality. This study aims to investigate what is the more suitable UAS for specific applications considering the required scale factor, such as for architectural, environmental, and restoration purposes. A series of photogrammetric surveys were conducted in a hilly area of about 5 ha using Phantom 4 Adv, Mavic 2 Pro, Mavic Air 2, and Mavic Mini 2. These unmanned aircrafts are commercial user–grade systems used mainly by private professionals. Several photogrammetric reconstructions were performed by varying essential parameters, such as flight altitude and cameras of remotely piloted aircraft systems (RPAS), applying structure-from-motion (SfM) algorithms to the images taken from the UAS. The surveys’ quality was analyzed by comparing the ground targets’ coordinates extrapolated from the point clouds to those measured on the field with indirect georeferencing through GNSS technology. Fifty targets were installed and arranged following a reasonably regular mesh. The boundary conditions were maintained the same for each flight mission, flight trajectories, and the ground control point distribution on the ground. For each survey made by each of the four UAS, altimetric and planimetric residuals were reported and compared. Average residuals from Phantom 4 Adv, about 15 mm, almost disappear compared to the other UASs; the discrepancy is one order of magnitude. With a regular grid geometry of ground targets, the Mavic Mini 2 led to an error average of about 5 cm. Remembering that the Mavic Mini 2 is an ultralight drone (does not require a pilot's license), it could significantly reduce cost compared to the other systems.