Multi-view Stereo Photogrammetry Research Articles

The IGCP 714 Project “3GEO – Geoclimbing & Geotrekking in Geoparks” – Selection of Geodiversity Sites Equipped for Climbing for Combining Outdoor and Multimedia Activities

The IGCP 714 project “3GEO – Geoclimbing & Geotrekking in Geoparks” is financed by the International Geoscience Programme (IGCP) and supported by the International Union of Geological Sciences (IUGS). In this paper, we report on the results of the first phase of the project focused on the criteria to be adopted to select geodiversity sites equipped for climbing or trekking. The selection of geoclimbing sites and geotrekking routes is aimed at combining multimedia tools and outdoor activities for Geosciences promotion and conservation in UNESCO Global Geoparks, aspiring geoparks or geoparks project, and also in protected areas featuring geoheritage sites. Indeed, both outdoor activities and multimedia tools favour the pursuing of many of the United Nations Sustainable Development Goals (e.g., 3, 4, 8, 11). An international consortium of geoscientists from 12 different countries selected, through the proposed procedure, 22 geoclimbing sites, and then they also detected 30 geotrekking routes mirroring Earth geodiversity. At some test sites (geoclimbing and geotrekking) multimedia tools and digital outcrop models have been developed through different methodological approaches (e.g., Structure from Motion and Multi-View Stereo photogrammetry), to open the way to the second part of the project still in progress. These sites and the relative virtual models are herein also shown. The final aim of the IGCP 714 project is indeed to create an open data repository (digital outcrop models, videos, virtual tours, photos, scientific information, and interpretations) to upload data of the selected sites to mirror Earth geodiversity for different users including tourists and school groups.

3D Modelling Approach to Enhance the Characterization of a Bronze Age Nuragic Site

Megalithism in Sardinia (Italy) had its highest expression during the Bronze Age with the creation of monumental complexes known as Nuraghes. These unique monuments have recently been the subject of in-depth investigations for their potential to be recognized as World Heritage Sites (by UNESCO). The main purpose of our research was to make a contribution to obtain a more in-depth characterization of these monuments by testing a 3D model of a complex Nuraghe, integrated with an analysis of the geolithological context. This work first focused on the geological and typological investigation of the materials used in its construction, which was then compared with the geolithological characteristics of the region. A survey of the outcropping remains was carried out by means of Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry with UAV ground and aerial acquisition using APS-C photo sensors, georeferenced with an RTK-GNSS ground survey. The level of accuracy of our digital models shows the potential of the proposed method, giving accurate and geometrically consistent 3D reconstructions in terms of georeferencing error, shape and surface. The survey method allows for the virtualization of the current state of conservation of the Nuraghe, giving a solid basis to set up further (future) archaeological excavations and to contribute to knowledge on the architecture of the structures. This study also provides useful information on the nature and origin of the construction materials and proposes a hypothesis on the original dimensions of the monument, which is often a topic of debate in the world of archaeology.

Spatial Analysis of Point Clouds Obtained by SfM Photogrammetry and the TLS Method—Study in Quarry Environment

Thanks to the development of geodetic methods and equipment, there has been a transition from conventional methods to modern technologies, which can efficiently and accurately acquire a large amount of data in a short time without the need for direct contact with the measured object. Combined technologies such as Structure from Motion (SfM), Multi-View Stereo (MVS) photogrammetry using Unmanned Aerial Systems (UAS), and terrestrial laser scanning (TLS) are often used for monitoring geohazards and documenting objects in quarries to obtain detailed and accurate information about their condition and changes. This article deals with the analysis of point clouds obtained with different settings in terms of average absolute point distance, average point density, and time range for surveying and office work. The numerical and graphical results of the research lead to conclusions for scientific and practical applications for activities in the mining industry.

Long-Term Volumetric Change Estimation of Red Ash Quarry Sites in the Afro-Alpine Ecosystem of Bale Mountains National Park in Ethiopia

The Bale Mountains National Park (BMNP) in Ethiopia comprises the largest fraction of the Afro-Alpine ecosystem in Africa, which provides vital mountain ecosystem services at local, regional, and global levels. However, the BMNP has been severely threatened by natural and anthropogenic disturbances in recent decades. In particular, landscape alteration due to human activities such as red ash quarrying has become a common practice in the BMNP, which poses a major environmental challenge by severely degrading the Afro-Alpine ecosystem. This study aims to quantify the long-term volumetric changes of two red ash quarry sites in the BMNP using historical aerial photographs and in situ data, and to assess their impact on the Afro-Alpine ecosystem. The Structure-from-Motion multi-view stereo photogrammetry algorithm was used to reconstruct the three-dimensional landscape for the year 1967 and 1984 while spatial interpolation techniques were applied to generate the current digital elevation models for 2023. To quantify the volumetric changes and landscape alteration of the quarry sites, differences in digital elevation models were computed. The result showed that the volume of resources extracted from the BMNP quarry sites increased significantly over the study period from 1984 to 2023 compared with the period from 1967 to 1984. In general, between 1967 and 2023, the total net surface volume of the quarry sites decreased by 503,721 ± 27,970 m3 and 368,523 ± 30,003 m3, respectively. The extent of the excavated area increased by 53,147 m2 and 45,297 m2 for Site 1 and 2, respectively. In terms of habitat loss, major gravel road construction inside the BMNP resulted in the reduction of Afro-Alpine vegetation by 476,860 m2, ericaceous vegetation by 403,806 m2 and Afromontane forest by 493,222 m2 with associated decline in species diversity and density. The excavation and gravel road construction have contributed to the degradation of the Afro-Alpine ecosystem, especially the endemic Lobelia rhynchopetalum on the quarry sites and roads. If excavation continues at the same rate as in the last half century, it can threaten the whole mountain ecosystem of the National Park and beyond, highlighting the importance of preventing these anthropogenic changes and conserving the remaining Afro-Alpine ecosystem.

High-resolution digital elevation models and orthomosaics generated from historical aerial photographs (since the 1960s) of the Bale Mountains in Ethiopia

Abstract. The natural resources of Ethiopian high-altitude ecosystems are commonly perceived as increasingly threatened by devastating land-use practices owing to decreasing lowland resources. Quantified time-series data of the course of land-use cover changes are still needed. Very-high-resolution digital data on the historical landscape over recent decades are needed to determine the impacts of changes in afro-alpine ecosystems. However, digital elevation models (DEMs) and orthomosaics do not exist for most afro-alpine ecosystems of Africa. We processed the only available and oldest historical aerial photographs for Ethiopia and any afro-alpine ecosystem. Here, we provide a DEM and an orthomosaic image for the years 1967 and 1984 for the Bale Mountains in Ethiopia, which comprise the largest afro-alpine ecosystem in Africa. We used 298 historical aerial photographs captured in 1967 and 1984 for generating DEMs and orthomosaics with a structure-from-motion multi-view stereo photogrammetry workflow along an elevation gradient from 977 to 4377 m above sea level (a.s.l.) at very high spatial resolutions of 0.84 m and 0.98 m for the years 1967 and 1984, respectively. The structure-from-motion multi-view stereo photogrammetry workflow, employed with Agisoft Metashape, represents a modern approach that combines computer vision and photogrammetry. This method proves useful for reconstructing DEMs and orthomosaics from historical aerial photographs, with a focus on high spatial resolution. To validate the accuracy of the reconstructed DEMs, ground control points gathered through GPS measurements were used, resulting in root mean square error (RMSE) values of 3.55 m for the year 1967 and 3.44 m for the year 1984. Our datasets can be used by researchers and policymakers for watershed management, as the area provides water for more than 30 million people, landscape management, detailed mapping, and analysis of geological and archaeological features as well as natural resources, analyses of geomorphological processes, and biodiversity research. All the datasets are available online at https://doi.org/10.5281/zenodo.7271617 (Muhammed et al., 2022a) for all the inputs used and at https://doi.org/10.5281/zenodo.7269999 (Muhammed et al., 2022b) for the results obtained (very-high-resolution DEMs and orthomosaics) for both the years 1967 and 1984.

Accuracy assessment of UAS photogrammetry and structure from motion in surveying and mapping

Rapid and accurate surveying has always attracted great interest in all scientific and industrial activities that require high-resolution topographic data. The latest automation and advancement in geomatics engineering are remote sensing solutions using Unmanned Aerial Systems (UAS) and Structure from Motion (SfM) with Multi-View Stereo (MVS) photogrammetry. This research aimed to find the influence of flight height, Ground Control Point (GCP), and software on the geometric accuracy of UAS-SfM-derived Digital Surface Models (DSMs) and orthoimages, as well as to analyze and evaluate the accuracy of UAS-SfM as a rapid and low-cost alternative to conventional survey methods. To achieve the aim of the study, aerial surveys using a fixed-wing UAS and field surveys using RTK GNSS and total station were conducted. A total of 16 photogrammetric projects were processed using different GCP configurations, and detailed statistical analysis was performed on the results. Moreover, the contribution of cross flight on bundle adjustment was investigated empirically by conducting a combined photogrammetric image processing. The analysis revealed that flight height, GCP number and distribution, and the processing software significantly affect products' quality and accuracy. Evaluation of the achieved accuracies was made based on the American Society for Photogrammetry and Remote Sensing (ASPRS) positional accuracy standard for digital geospatial data. The findings of this study revealed that using the optimal flight height and GCP configuration, 3D models, orthomosaics and DSMs can be rapidly reconstructed from 2D images with the quality and accuracy sufficient for most terrain analysis applications, including civil engineering projects.

Remote volcano monitoring using crowd-sourced imagery and Structure-from-Motion photogrammetry: A case study of Oldoinyo Lengai's active pit crater since the 2007–08 paroxysm

Active volcanic craters are highly dynamic geological features that undergo morphological changes on a broad range of spatial and temporal scales. Such changes have implications for the stability of the edifice, the eruptive style and the associated hazards. However, monitoring the morphological evolution of active craters at high spatial resolution and over long periods of time can be challenging, especially at remote volcanoes. In this study, we demonstrate the potential of Structure-from-Motion Multi-View Stereo photogrammetry technique based on crowd-sourced data, applied to the case study of Oldoinyo Lengai (OL) volcano in northern Tanzania. Following the 2007–08 paroxysm, OL volcano resumed its characteristic effusive activity and started to fill in with lava the newly-formed 300 m wide and 130 m deep pit crater. Monitoring capability is limited at OL due to its location in a remote non-urbanized area, therefore, the eruptive and morphological evolution is poorly constrained (e.g., lava emission rates, number of vents, location of unstable areas), with hazard implications for tourists visiting the summit area. Here we use crowd-sourced images, including Unoccupied Aircraft System (UAS) images, ground-based videos and pictures collected between October 2014 and June 2022, to reconstruct high-resolution topographic time-series of OL's summit crater. With these data, we have generated 7 Digital Elevation Models (DEMs) of OL's pit crater spanning the past 8 years, and estimated the emitted volume of lava and the corresponding time averaged discharge rates (TADR). From this we characterize the geomorphological evolution of OL pit crater since the 2007–08 paroxysm and perform a preliminary hazard assessment of the crater area. InSAR COSMO-SkyMed and Sentinel-1 data covering the periods 2013–2014 and 2018–2019 were also used in this study to complement our observations. Our results indicate that the main location of lava emission within the crater floor has repeatedly shifted over the years and that the 2008 cone has experienced a subsidence over time. OL's TADR has increased over the years, reaching values one order of magnitude higher in the period 2021–2022 compared to 2014–2018. Assuming similar TADR in the coming years, the crater could be filled in by lava within the next decade, leading to new lava overflows on the flanks of the volcano.

Vo-Norvana : Versatile Framework for Efficient Segmentation of Large Point Cloud Data Sets

Dense three-dimensional (3D) point clouds collected from rapidly evolving data acquisition techniques such as light detection and ranging (lidar) and structure from motion (SfM) multiview stereo (MVS) photogrammetry contain detailed geometric information of a scene suitable for a wide variety of applications. Among the many processes within a typical point cloud processing workflow, segmentation is often a crucial step to group points with similar attributes to support more advanced modeling and analysis. Segmenting large point cloud data sets (i.e., hundreds of millions to billions of points) can be extremely time consuming and tedious with current tools, which primarily rely on significant manual effort. While many automated methods have been proposed, the practicality, scalability, and versatility of these approaches remain a bottleneck stifling processing of large data sets. To overcome these challenges, this paper introduces a novel, generalized segmentation framework called Vo-Norvana, which incorporates a new voxelization technique, a normal variation analysis considering the positioning uncertainty of the point cloud, and a custom region growing process for clustering. The proposed framework was tested with several large-volume data sets collected in diverse scene types using several data acquisition platforms including terrestrial lidar, mobile lidar, airborne lidar, and drone-based SfM-MVS photogrammetry. In evaluating the accuracy of models generated from Vo-Norvana against manual segmentation, the average error of the position, orientation, and dimensions are 2.7 mm, 0.083°, and 0.9 mm, respectively. Over 0.2 million points per second and 36 thousand voxels per second can be achieved when segmenting an airborne lidar data set containing over 639 million points to about 1 million segments.

ITERATIVE REFRACTION-CORRECTION METHOD ON MVS-SFM FOR SHALLOW STREAM BATHYMETRY

Abstract. Extracting accurate bathymetric information from clear, shallow waters in complex riverine environments can be challenging, but it is crucial for many applications, such as hydraulic modeling, ecological monitoring, and sediment transport analysis. Multi-view stereo photogrammetry (MVS-SfM) has emerged as a promising technique for acquiring high-resolution bathymetric data from aerial imagery. However, the accuracy of MVS-SfM can be affected by various factors, including water refraction, which can distort the depth measurements. In this study, iterative Dietrich’s refraction-correction method is tested for extracting bathymetry from MVS-SfM in a complex riverine environment. Moreover, we proposed a workflow for applying the method using raster data files, which can be more readily available than point clouds. It also compared the obtained results with previous applications and evaluated them using statistical indices and ratios. For this case study, the multicamera refraction method produces bathymetric datasets with accuracies of ~0.019% of the flying height and precisions of ~0.07% of the flying height. This study contributes to increased confidence in exploiting aerial imagery for bathymetric mapping in photogrammetric procedures under field conditions and can facilitate the management and conservation of clear water systems.

3D geometric survey of cultural heritage by UAV in inaccessible coastal or shallow aquatic environments

AbstractCultural heritage in coastal or shallow aquatic environments is often located in areas where access is difficult or where accurate survey and documentation may not always be possible with terrestrial or aquatic equipment. The combination of photogrammetry and unmanned aerial vehicles (UAVs) generates a range of possibilities across multiple sectors, including history, ethnography and cultural heritage studies. Additionally, these methods can be used to prospect new archaeological sites. This article presents three case studies that use UAV techniques and Structure from Motion and Multiview Stereo (SfM‐MVS) photogrammetry to conduct topographic and geometric registrations of archaeological, historical and ethnographic sites (some of which are classified as cultural heritage sites). These examples are located in coastal or shallow aquatic environments that are difficult to survey with traditional methods. The results show that it is possible to carry out detailed geometric registration and heritage prospection over large coastal or shallow aquatic environments using a low‐cost UAV. Furthermore, the results of this work show great advantages in terms of cost and quality, even in cases where the seabed is below a shallow water column. Other particularities of SfM‐MVS application in aquatic environments are discussed. From an interdisciplinary perspective, this methodology will offer new possibilities for the study, restoration and conservation of archaeological, historical and ethnographic monuments.

Towards of multi-source data fusion framework of geo-referenced and non-georeferenced data: prospects for use in surface water bodies

This paper proposes an approach of fusion geo-referenced and non-georeferenced data. These data can be acquired by a) unmanned surface vehicles (USVs), b) unmanned aerial vehicles (UAVs), c) airborne and submersible optical sensors, d) acoustic sensors and e) aquatic sound profiling instruments. The test scenario consisted of monitoring and morphological characterisation of a confined water body. As part of the data integration and processing process, object segmentation modules were implemented for tracking and identification of underwater fauna, accompanied by Structure-from-Motion (SfM) and multi-view stereophotogrammetry (MVS) techniques for 3D reconstruction. The results obtained make it possible to recreate morphological models of the study/test areas by coupling all the existing information above and below the water mirror. The spatial resolution obtained is of centimetric order and the resulting data have the ideal quality to be used in underwater mapping and monitoring, as well as in 3D geomorphological measurements of surface water bodies Highlights Multi-source geo-referenced and non-georeferenced data fusion strategy Mapping of surface water bodies using unmanned aerial/aquatic vehicles. Application of segmentation techniques for monitoring and tracking of aquatic fauna. Three-dimensional reconstruction of underwater environments at high spatial resolution Robust framework for the integration of data from passive and active sensors

Rapid Photogrammetry with a 360-Degree Camera for Tunnel Mapping

Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry is a viable method to digitize underground spaces for inspection, documentation, or remote mapping. However, the conventional image acquisition process can be laborious and time-consuming. Previous studies confirmed that the acquisition time can be reduced when using a 360-degree camera to capture the images. This paper demonstrates a method for rapid photogrammetric reconstruction of tunnels using a 360-degree camera. The method is demonstrated in a field test executed in a tunnel section of the Underground Research Laboratory of Aalto University in Espoo, Finland. A 10 m-long tunnel section with exposed rock was photographed using the 360-degree camera from 27 locations and a 3D model was reconstructed using SfM-MVS photogrammetry. The resulting model was then compared with a reference laser scan and a more conventional digital single-lens reflex (DSLR) camera-based model. Image acquisition with a 360-degree camera was 3× faster than with a conventional DSLR camera and the workflow was easier and less prone to errors. The 360-degree camera-based model achieved a 0.0046 m distance accuracy error compared to the reference laser scan. In addition, the orientation of discontinuities was measured remotely from the 3D model and the digitally obtained values matched the manual compass measurements of the sub-vertical fracture sets, with an average error of 2–5°.

Estimating the attributes of urban trees using terrestrial photogrammetry.

Today, different methods are used to measure two-dimensional (2D) and three-dimensional (3D) attributes of trees. One of these methods, which is considered in recent years is using point clouds and a 3D model extracted from terrestrial photogrammetry (TP). This study aims to estimate the 2D and 3D attributes of urban trees at three levels of seedlings, single trees and sample plot using TP. Structure-from-Motion with Multi-View Stereo-photogrammetry (SfM-MVS) method was used to derive the point clouds and the 3D model. Comparing estimated values of diameter at the middle of trunk of seedlings and diameter at breast height (DBH) of trees, using TP with measured values showed that the values of RMSE% were < 2% at three levels of seedlings, single trees and sample plot. Furthermore, validation of the estimated values of total height and crown height attributes of seedlings and trees at three levels showed that the RMSE% did not exceed 4% and 5%, respectively. Considering the overlap of tree crowns with each other in the sample plot, the average diameter of the crown attribute was estimated only in seedlings and single tree levels with RMSE% = 6.51% and 9.34%, respectively. The validation of estimated values of stem volume of seedlings and trees at three levels showed that the lowest errors were returned from trees within a sample plot with RMSE% = 14.37%, whereas the highest rates of errors were achieved for seedlings with RMSE% = 20.99%. As an alternative to approaches such as employing laser scanners, this method is quick, inexpensive, non-destructive, and does not need specialized equipment.

THE USE OF CAPTURED IMAGES BY REMOTELY PILOTED AIRCRAFT (RPA) IN MEASURING THE STACKED LOG VOLUME IN A STOCKYARD

Quantifying wood in industrial yards quickly, accurately and at low costs is of great importance for stock management and decision making. In this work, the volume of wood logs stacked in an industrial yard was quantified using aerial images with high spatial resolution obtained by remotely piloted aircraft (RPA). The volumetric measurements were tested using the Structure from Motion with Multi-View Stereo (SfM-MVS) photogrammetry technique and compared with values obtained through the conventional manual measurement method. The aerial images were taken at three different flight heights of 60, 80 and 100 m installed at 10 ground control points using a GNSS RTK receptor. The aerial images were processed by digital photogrammetry software to generate digital surface models (DSM), which made it possible to obtain the volumetric measurements of the stacked wood. Thus, aerial images acquired at 60, 80 and 100 m altitude presented variations of 17.50%, 14.93% and 8.31%, respectively. After the statistical tests applied to the results of volumetric estimates, the SfM-MVS photogrammetry did not show significant differences for the conventional measurement method, indicating that the use of aerial images acquired by RPA can be a viable option to estimate the stacked wood volume in an industrial yard.

Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery

Abstract Quick clay is found across Scandinavia and is especially prominent in south-eastern and central Norway. Quick clay is prone to failure and can cause landslides with high velocities and large run-outs. The 1978 Rissa landslide is one of the best-known quick clay landslides to have occurred in the last century, both due to its size and the fact that it was captured on film. In this article, we utilise Structure from Motion Multi-View Stereo (SfM-MVS) photogrammetry to process historical aerial photography from 1964 to 1978 and derive the first geodetic volume of the Rissa landslide. We found that the landslide covered a total onshore area of 0.36 km2 and had a geodetic volume of 2.53 ± 0.52 × 106 m3 with up to 20 m of surface elevation changes. Our estimate differs profusely from previous estimates by 43–56% which can partly be accounted for our analysis not being able to measure the portion of the landslide that occurred underwater, nor account for the material deposited within the landslide area. Given the accuracy and precision of our analyses, we believe that the total volume of the Rissa landslide may have been less than originally reported. The use of modern image processing techniques such as SfM-MVS for processing historical aerial photography is recommended for understanding landscape changes related to landslides, volcanoes, glaciers, or river erosion over large spatial and temporal scales.

Automatic Extraction of Unmanned Aerial Vehicles (UAV)-based Cadastral Map: Case Study in AL-Shatrah District- Iraq

Cadastral map environment is directed, more than ever before, towards Artificial Intelligence use to produce fast and accurate maps and keep up with the huge population growth. The traditional approach currently in production of maps is expensive and effort-intensive in addition to be considered as highly time-consuming process. UAV-based cadastral mapping imagery that use automatic techniques are newly being exploited to accelerate the process of production or updating. The state-of-the-art intelligent algorithms are capable to extract land boundaries from images better than conventional techniques. This paper presents an automatic workflow of cadastral map production based on land boundary and automatic feature extraction from UAV-based imageries. The developed workflow involved four steps: (i) Flight planning and Ground Control Points (GCPs) observation, (ii) image pre-processing, (iii) image segmentation (iv) boundary detection and extraction (classification), (v) postprocessing, and (vi) accuracy assessment. The study area includes geometrical and affect spectral reflectivity (slums) covered by 206 images those captured using a quad-rotary UAV (DJI Phantom 4 pro). The mosaic image of the Area of Interest (AOI) was produced by following Structure from Motion /Multi-view Stereo (SfM-MVS) photogrammetry which covers 0.592 km2 ground area using pix4DMapper software. The Multi-Resolution Segmentation (MRS) algorithm was applied for object generation and later both spectral and geometrical information (area, brightness, border and the normalized digital surface model NDSM)) utilised to extract the boundaries by Object Based Image Analysis (OBIA) rule-based expert systems in eCognition software. The most exciting challenge in this AOI was buildings separation depending on number of buildings using the QGIS software. The accuracy assessment of the obtained results showed that 88% of the extracted boundaries were correct following automatic extraction routine when compared to manual digitizing. This approach can highly compensate time, efforts, and low accuracy outcomes from traditional surveying and manual registration approaches applied in Iraqi institutes nowadays. The presented approach can definitely help to speed up map production phase and keep pace up with population expansion and modern technologies.

Using virtual outcrop models and google earth to teach structural geology concepts

This paper presents two classroom activities which have students analyze, collect, and interpret geologic data. The material is targeted at distance learning, although it can function well in the classroom as pseudo-field trips. The activity is based around Virtual Outcrop Models (VOMs), created using Structure from Motion – Multi-view Stereo photogrammetry, of two outcrops: the first is a folded outcrop in the southern Death Valley region and the second is a fractured granite in the Santa Monica Mountains. In Activity 1 students begin by analyzing the folds using 2D field photographs. They then look at the same folds using the VOM and are provided strike and dip data. Students are prompted to think about and discuss their interpretations of the shortening directions and the deformation events recorded in the outcrop. After interpreting the outcrop, they then correlate their results with regional structures. In Activity 2, students take direct fracture measurements from the VOM and interpret various fracture characteristics. Their measurements are then compared to other fracture characterizations in the literature. Through the activities students are introduced to a number of key concepts in geology, including the importance of “thinking in 3D″, data collection, interpreting stereonets, and placing results in the context of previous work.

Assessment of the trueness and precision of smartphone photogrammetry for rock joint roughness measurement

The roughness of rock joint surfaces plays a vital role in the hydrological and mechanical properties of discontinuous rock masses. Applicable and reliable measurements are important for investigating the roughness characterization of rock joints. This research comprehensively evaluates the performance of smartphone photogrammetry for rock joints through a roughness characterization method. Five laboratory-sized rock joint specimens were selected and operated by 24 experimenters to assess the trueness and precision of smartphone photogrammetry based on Structure from Motion- Multi View Stereo (SfM-MVS) photogrammetry technique. Benchmark data from a structure light scanner were used to assess the usability of smartphone photogrammetry through the directional roughness metric method. The results show that it can be applied to achieve acceptable trueness and precision of joint roughness measurements for engraving rock and replica rock joints with no reflective or translucent materials. In addition, the roughness errors of the subsampled models with point intervals of 0.25 mm, 0.5 mm, and 1.0 mm are close to each other.

A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees

In recent decades, a considerable number of sensors have been developed to obtain 3D point clouds that have great potential in optimizing management in agriculture through the application of precision agriculture techniques. In order to use the data provided by these sensors, it is essential to know their measurement error. In this paper, a methodology is presented for obtaining a 3D point cloud of a central axis training system defoliated fruit tree (Malus domestica Bork.) obtained from stereophotogrammetry techniques based on structure-from-motion (SfM) and multi-view stereo-photogrammetry (MVS). The point cloud was made from a set of 288 photographs of the scene including the ground truth tree which was used to generate the digital 3D model. The resulting point cloud was validated and proven to faithfully represent reality. The bias of the resulting model is −0.15 mm and 0.05 mm, for diameters and lengths, respectively. In addition, the presented methodology allows small changes in the ground truth actual tree to be detected as a consequence of the wood dehydration process. Having an actual and a digital ground-truth is the basis for validating other sensing systems for 3D vegetation characterization which can be used to obtain data to make more informed management decisions.

Non-Intrusive Luminance Mapping via High Dynamic Range Imaging and 3-D Reconstruction

Continuous luminance monitoring is challenging because high-dynamic-range cameras are expensive, they need programming, and are intrusive when placed near the occupants’ field-of-view. A new semi-automated and non-intrusive framework is presented for monitoring occupant-perceived luminance using a low-cost camera sensor and Structure-from- Motion (SfM)-Multiview Stereo (MVS) photogrammetry pipeline. Using a short video and a few photos from the occupant position, the 3D space geometry is automatically reconstructed. Retrieved 3D context enables the back-projection of the camera-captured luminance distribution into 3D spaces that are in turn re-projected to occupant-FOVs. The framework was tested and validated in a testbed office. The re-projected luminance field showed with good agreement with luminance measured at the occupant position. The new method can be used for non-intrusive luminance monitoring integrated with daylighting control applications.