Structure From Motion Photogrammetry Research Articles

Creating a Digital 3D Model of the Dental Cast Using Structure-from-Motion Photogrammetry Technique

Photogrammetry is a technique used to obtain a reliable database of any physical object, by creating a digital 3d model using multiple photos taken at different angles around the object. Recently, several fields have used this technique to build digital 3D models, such as topography, architecture, engineering, and medicine. Many recent dentistry studies have used the Structure-from-motion (SfM) Photogrammetry technique to reconstruct a digital three-dimensional (3D) model of a dental cast as an alternative to conventional scanning. In this research, the dental casts are constructed by applying the SfM Photogrammetry technique in which a guide to stepwise workflow is provided by utilizing simple tools which are: a smartphone camera, homemade photo studio setup, and Agisoft Metashape software. The agreements between the generated models and the reference dental casts are assessed using the Bland Altman method by calculating the mean value differences. All the calculated differences are not statistically significant (P-value >0.05), and they are also clinically accepted as the range of the mean differences (-0.042 to 0.355) is less than 0.5mm. this demonstrates that the resulted 3D models closely approximate the overall geometry of the dental casts.

THE APPLICATION OF SMARTPHONE BASED STRUCTURE FROM MOTION (SFM) PHOTOGRAMMETRY IN GROUND VOLUME MEASUREMENT

Abstract. The purpose of this research study is to assess the potential using smartphone camera captured images for 3D model reconstruction by using Structure from Motion (SFM) photogrammetry technique, specifically in term of volumetric measurement. In past, the volumetric measurement of surface or object is by using Imaging Station or by professional Terrestrial Laser Scanner (TLS), however such approach is expensive in labour fees and instruments fee respectively. A cheaper alternative is necessary for researcher and industrial to construct 3D model with greater cost efficiency. The improvement of photography and computer vision has introduced the technique of SFM photogrammetry, an alternative in 3D model reconstruction other than TLS. Non-metric camera sensor mounted inside budget smartphone are used to capture images of stockpile and processed by Agisoft Metashape Professional (AMP) software to construct a 3D model. The volumetric measurement is executed and compare with the benchmark which is the model constructed from TLS. Statistics and tables are used to indicate the accuracy of Smartphone based SFM photogrammetry in intuitive manner. The result shows that the volumetric measurement by using smartphone SFM method has significant difference when compared with the benchmark, TLS solution.

Semi-automated discrete-element modelling of arch structures incorporating SfM photogrammetry

This paper presents Image2DEM, a framework for the semi-automated structural analysis of arches. Numerical models of arch specimens were semi-automatically developed from structure-from-motion (SfM) photogrammetry, by employing image-processing techniques, to bypass laborious computer-aided design (Cad)-based processes. Then, the numerical models of the proposed framework were assessed by comparison with a conventional Cad-based framework in terms of (a) geometrical agreement (i.e. joint and block properties) and (b) structural capacity agreement (i.e. stiffness, load multipliers and normal forces between joints at each hinge formation). The results firstly demonstrated SfM photogrammetry as an effective avenue of structural surveying for numerical modelling. Afterwards, the numerical models developed from the proposed and conventional frameworks were demonstrated to have good agreement in terms of geometry. Furthermore, good agreement was also found in the predicted structural capacity, with differences in structural capacity of less than 7%. Although only the potential to capture both the geometry and structural capacity of small-scale arch structures was demonstrated here, this study lays the foundation for automated geometry acquisition for arches for their structural analysis.

Expeditious Low-Cost SfM Photogrammetry and a TLS Survey for the Structural Analysis of Illasi Castle (Italy)

The structural analysis of degraded historical buildings requires an adequate 3D model of the object. Structure from motion (SfM) photogrammetry and laser scanning geomatics techniques can satisfy this request by providing geometrically affordable data. The accuracy and resolution depend on the instruments and procedures used to extract the 3D models. This work focused on a 3D survey of Illasi Castle, a strongly degraded historical building located in northern Italy, aimed at structural analysis in the prevision of a static recovery. A low-cost drone, a single-lens reflex (SLR) camera, and a smartphone were used in the survey. From each acquired dataset, using the integration between the images acquired by the drone and the SLR camera, a 3D model of the building was extracted by means of the SfM technique. The data were compared with high-precision and high-resolution terrestrial laser scanning (TLS) acquisitions to evaluate the accuracy and performance of the fast and low-cost SfM approach. The results showed a standard deviation value for the point cloud comparisons in the order of 2–3 cm for the best solution (integrating drone and SLR images) and 4–7 cm using smartphone images. Finally, the integration of the best SfM model of the external walls and the TLS model of the internal portion of the building was used in finite element (FE) analysis to provide a safety assessment of the structure.

An Open-Source Photogrammetry Workflow for Reconstructing 3D Models.

Acquiring accurate 3D biological models efficiently and economically is important for morphological data collection and analysis in organismal biology. In recent years, structure-from-motion (SFM) photogrammetry has become increasingly popular in biological research due to its flexibility and being relatively low cost. SFM photogrammetry registers 2D images for reconstructing camera positions as the basis for 3D modeling and texturing. However, most studies of organismal biology still relied on commercial software to reconstruct the 3D model from photographs, which impeded the adoption of this workflow in our field due the blocking issues such as cost and affordability. Also, prior investigations in photogrammetry did not sufficiently assess the geometric accuracy of the models reconstructed. Consequently, this study has two goals. First, we presented an affordable and highly flexible SFM photogrammetry pipeline based on the open-source package OpenDroneMap (ODM) and its user interface WebODM. Second, we assessed the geometric accuracy of the photogrammetric models acquired from the ODM pipeline by comparing them to the models acquired via microCT scanning, the de facto method to image skeleton. Our sample comprised 15 Aplodontia rufa (mountain beaver) skulls. Using models derived from microCT scans of the samples as reference, our results showed that the geometry of the models derived from ODM was sufficiently accurate for gross metric and morphometric analysis as the measurement errors are usually around or below 2%, and morphometric analysis captured consistent patterns of shape variations in both modalities. However, subtle but distinct differences between the photogrammetric and microCT-derived 3D models could affect the landmark placement, which in return affected the downstream shape analysis, especially when the variance within a sample is relatively small. At the minimum, we strongly advise not combining 3D models derived from these two modalities for geometric morphometric analysis. Our findings can be indictive of similar issues in other SFM photogrammetry tools since the underlying pipelines are similar. We recommend that users run a pilot test of geometric accuracy before using photogrammetric models for morphometric analysis. For the research community, we provide detailed guidance on using our pipeline for building 3D models from photographs.

Rapid tunnel scanning using a 360-degree camera and SfM photogrammetry

Photogrammetric scanning can be employed for the digitization of underground spaces, for example for remote mapping, visualization, or training purposes. However, such a technique requires capturing many photos, which can be laborious and time-consuming. Previous research has demonstrated that the acquisition time can be reduced by capturing the data with multiple lenses or devices at the same time. Therefore, this paper demonstrates a method for rapid scanning of hard rock tunnels using Structure-from-Motion (SfM) photogrammetry and a 360-degree camera. The test was performed in the Underground Research Laboratory of Aalto University (URLA). The tunnel is located in granitic rocks at a depth of 20 m below the Otaniemi campus in Espoo, Finland. A 10 m long and 3.5 m high tunnel section with exposed rock was selected for this study. Photos were captured using the 360-degree camera from 27 locations and 3D models were reconstructed using SfM photogrammetry. The accuracy, speed, and resolution of the 3D models were measured and compared with models scanned with a digital single-lens reflex (DSLR) camera. The results show that the data capture process with a 360-degree camera is 6x faster compared to a conventional camera. In addition, the orientation of discontinuities was measured remotely from the 3D model and the digitally obtained values matched the manual compass measurements. Even though the quality of the 360-degree camerabased 3D model was visually inferior compared to the DSLR model, the point cloud had sufficient accuracy and resolution for semi-automatic discontinuity measurements. The quality of the models can be improved by combining 360-degree and DSLR photos which result in a point cloud with 3x higher resolution and 2x higher accuracy. The results demonstrated that 360-degree cameras can be used for the rapid digitization of underground tunnels.

A comparison of three surface roughness characterization techniques: photogrammetry, pin profiler, and smartphone-based LiDAR

ABSTRACT Surface roughness plays an important role in microwave remote sensing. In the agricultural domain, surface roughness is crucial for soil moisture retrieval methods that use electromagnetic surface scattering or microwave radiative transfer models. Therefore, improved characterization of Soil Surface Roughness (SSR) is of considerable importance. In this study, three approaches, including a standard pin profiler, a LiDAR point cloud generated from an iPhone 12 Pro, and a Structure from Motion (SfM) photogrammetric point cloud, were applied over 24 surface profiles with different roughness variations to measure surface roughness. The objective of this study was to evaluate the capability of smartphone-based LiDAR technology to measure surface roughness parameters and compare the results of this technique with the more common approaches. Results showed that the iPhone LiDAR technology, when point cloud data is captured in a fine-resolution mode, has a significant correlation with SfM photogrammetry (R 2 = 0.70) and a relatively close agreement with pin profiler (R 2 = 0.60). However, this accuracy tends to be greater for random surfaces and rough profiles with row structure orientations. The results of this study confirm that smartphone-based LiDAR can be used as a cost-effective, fast, and time-efficient alternative tool for measuring surface roughness, especially for rough, wide, and inaccessible areas.

Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain

Abstract. Dynamic natural processes govern snow distribution in mountainous environments throughout the world. Interactions between these different processes create spatially variable patterns of snow depth across a landscape. Variations in accumulation and redistribution occur at a variety of spatial scales, which are well established for moderate mountain terrain. However, spatial patterns of snow depth variability in steep, complex mountain terrain have not been fully explored due to insufficient spatial resolutions of snow depth measurement. Recent advances in uncrewed aerial systems (UASs) and structure from motion (SfM) photogrammetry provide an opportunity to map spatially continuous snow depths at high resolutions in these environments. Using UASs and SfM photogrammetry, we produced 11 snow depth maps at a steep couloir site in the Bridger Range of Montana, USA, during the 2019–2020 winter. We quantified the spatial scales of snow depth variability in this complex mountain terrain at a variety of resolutions over 2 orders of magnitude (0.02 to 20 m) and time steps (4 to 58 d) using variogram analysis in a high-performance computing environment. We found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability within complex mountain terrain and that snow depths are autocorrelated within horizontal distances of 15 m at our study site. The results of this research have the potential to reduce uncertainty currently associated with snowpack and snow water resource analysis by documenting and quantifying snow depth variability and snowpack evolution on relatively inaccessible slopes in complex terrain at high spatial and temporal resolutions.

Detection of discontinuity pattern and orientation for tunnel faces by using 2D and 3D image analysis techniques

This study proposes a new measurement system based on Structure from Motion (SfM) photogrammetry to evaluate tunnel faces. The main goal is to determine the tunnel face discontinuity patterns and orientations for the tunnel face stability evaluation. A 3D point cloud model is generated from overlapping images of the tunnel face 3D polystyrene model through SfM photogrammetry. The discontinuity patterns and orientations are determined through facet extraction of the K-D tree plugin in CloudCompare. The same sets of overlapping images were analyzed in four different quality settings (low, medium, high, and ultra-high) with various sets of point cloud number that control the accuracy of the discontinuity's measurement. In this study, the high-quality setting shows the consistent measurement of the discontinuity patterns and orientations compared with the real 3D polystyrene tunnel face model. Validation of the pattern results from CloudCompare was carried out using JudGeo. Cluster analysis shows two sets of discontinuity with means of dip and dip direction of 82°/164° and 84°/307°, respectively. Both orientations were manually verified with a geological compass. The high-quality point cloud and manual compass measurement of the orientation highlight the similarity of the concentration for both discontinuity sets for the replica tunnel face. This tunnel face proposed method has the advantages of evaluating inaccessible areas and avoiding professional bias.

Assessing Through-Water Structure-from-Motion Photogrammetry in Gravel-Bed Rivers under Controlled Conditions

Structure-from-Motion (SfM) photogrammetry has become a popular solution for three-dimensional topographic data collection in geosciences and can be used for measuring submerged bed surfaces in shallow and clear water systems. However, the performance of through-water SfM photogrammetry has not been fully evaluated for gravel-bed surfaces, which limits its application to the morphodynamics of gravel-bed rivers in both field investigations and flume experiments. In order to evaluate the influence of bed texture, flow rate, ground control point (GCP) layout, and refraction correction (RC) on the measurement quality of through-water SfM photogrammetry, we conducted a series of experiments in a 70 m-long and 7 m-wide flume with a straight artificial channel. Bed surfaces with strongly contrasting textures in two 4 m-long reaches were measured under five constant flow regimes with three GCP layouts, including both dry and underwater GCPs. All the submerged surface models with/without RC were compared with the corresponding dry bed surfaces to quantify their elevation errors. The results illustrated that the poorly sorted gravel-bed led to the better performance of through-water SfM photogrammetry than the bed covered by fine sand. Fine sediment transport caused significant elevation errors, while the static sand dunes and grain clusters did not lead to noticeable errors in the corrected models with dry GCPs. The elevation errors of the submerged models linearly increased with water depth for all the tested conditions of bed textures, GCP layouts, and discharges in the uncorrected models, but the slopes of the increasing relations varied with texture. The use of underwater GCPs made significant improvements to the performance of direct through-water SfM photogrammetry, but counteracted with RC. The corrected models with dry GCPs outperformed the uncorrected ones with underwater GCPs, which could still be used to correct the underestimation in surface elevation caused by RC. Based on the new findings, recommendations for through-water SfM photogrammetry in measuring submerged gravel-bed surfaces were provided.

A simplified structure-from-motion photogrammetry approach for urban development analysis

Despite the increasing availability of remote sensing imagery, spatial data of adequate spatio-temporal resolution for urban development analysis and urban planning remains inadequate in some places. Structure-from-Motion (SfM) photogrammetry provides a low-cost option to generate such data at the desired spatial resolution. This study thus presents a simplified approach for mapping and performing urban development analysis in a suburban area (Kuje) in Abuja, Federal Capital Territory, Nigeria. Here, we compared a Google Earth® historical imagery of 2005 (baseline data) with SfM-derived imagery of 2019 (recent data) to quantify the rate and magnitude of urban development in the area. The Ground Control Points (GCPs) survey achieved a Root Mean Square Error (RMSE) of 31.01 mm and 24.34 mm in planimetry and elevation respectively while the SFM survey achieved an RMSE of 21.11 mm, 25.35 mm and 96.06 mm in the X, Y & Z coordinate axes respectively, which are within the acceptable limit (<10 cm). The urban development analysis revealed that over the past 14 years, an average of 8 buildings were constructed per year. The area also witnessed an increase in the construction of roads and an associated decline in the green areas. In addition, the building height assessment revealed that land is not being used parsimoniously. The findings in this study demonstrate the viability of SfM photogrammetry in creating digital maps for small suburban areas and in performing urban development analysis. Furthermore, the results obtained can aid town planners and development authorities to make informed decisions about urban development issues in the area.

Quantification of Coastal Change and Preliminary Sediment Budget Calculation Using SfM Photogrammetry and Archival Aerial Imagery

A preliminary sediment budget for the sandy shores flanking the entrance to Western Port, a large bay in Australia, was formulated using a comparison between two Digital Surface Models (DSMs) with a 30-year interval and auxiliary shoreline data. The 1977 DSM was generated from ten aerial photographs using Structure-from-Motion (SfM) photogrammetry. Assessment of its accuracy obtained an RMSE of 0.48 m with most of the independent points overpredicting or underpredicting elevations by less than 0.5 m following manual point cloud cleaning. This technique created a 7.5 km2 surface with a Ground Sampling Distance of 34.3 cm between two coastal towns separated by a narrow channel. Comparison of the 1977 DSM to a second, light detection and ranging (LiDAR)-derived DSM from 2007 showed that a volume of ~200,000 m3 of sediment (above Mean Sea Level) was deposited at Newhaven Beach on Phillip Island, while, during the same period, ~40,000 m3 of sediment was lost from the mainland beaches of San Remo, on the eastern side of the channel. Shoreline positions extracted from aerial photographs taken in 1960 and a nautical chart published one century earlier indicate that the progradation experienced at Newhaven Beach has been possible due to provision of sediment via destabilisation of the vegetation covering the updrift Woolamai isthmus on the southeast coast of Phillip Island, whereas the retreat observed at San Remo Beach since 1960 can be attributed to the natural dynamics of the entrance, which appears to favour flood-dominance on the western side and ebb-dominance on the eastern side. While a more comprehensive balance of volumes entering and exiting the area would specifically benefit from volumetric assessments of the subaqueous part of the entrance, the general usefulness of quantifying coastal change using SfM and historical photographs is demonstrated.

Mid- and Short-Term Monitoring of Sea Cliff Erosion based on Structure-from-Motion (SfM) Photogrammetry: Application of Two Differing Camera Systems for 3D Point Cloud Construction

Yu, J.J.; Kim, D.W.; Lee, E.J., and Son, S.W., 2022. Mid- and short-term monitoring of sea cliff erosion based on structure-from-motion (SfM) photogrammetry: Application of two differing camera systems for 3D point cloud construction. Journal of Coastal Research, 38(5), 1021–1036. Coconut Creek (Florida), ISSN 0749-0208. Sea-level rise due to climate change is influencing coastal areas globally, which represent an important food and recreational resource for humanity. Accordingly, coastal monitoring is of vital importance. Recently, coastal erosion monitoring has been performed using various methods related to structure-from-motion (SfM) photogrammetry. In coastal topography, sea cliffs can have high elevations and uneven surfaces, making them challenging to model using SfM photogrammetry when capturing images using a single device from one direction owing to occluded areas during the construction of a three-dimensional point cloud (3D PCD). Therefore, in this study, two types of cameras were used to construct an appropriate 3D PCD of sea cliffs. Sea cliffs were photographed by an unmanned aerial vehicle (UAV) and by terrestrial cameras, and the resulting 3D PCD was constructed using fusion and integration methods during image processing. Sea cliff monitoring was performed separately for mid- (9 mo) and short-term (pre- and posttyphoon) periods, during which geomorphological changes could be monitored using the multiscale model-to-model cloud comparison (M3C2) technique. The proposed method effectively reduced the occluded area while sufficiently detecting geomorphological changes in the sea cliffs.

Diver-generated photomosaics as a tool for monitoring temperate rocky reef ecosystems

Robust monitoring data provides important information on ecosystem responses to anthropogenic stressors; however, traditional monitoring methodologies, which rely heavily on time in the field, are resource intensive. Consequently, trade-offs between data metrics captured and overall spatial and temporal coverage are necessary to fit within realistic monitoring budgets and timeframes. Recent advances in remote sensing technology have reduced the severity of these trade-offs by providing cost-effective, high-quality data at greatly increased temporal and spatial scales. Structure-from-motion (SfM) photogrammetry, a form of remote sensing utilising numerous overlapping images, is well established in terrestrial applications and can be a key tool for monitoring changes in marine benthic ecosystems, which are particularly vulnerable to anthropogenic stressors. Diver-generated photomosaics, an output of SfM photogrammetry, are increasingly being used as a benthic monitoring tool in clear tropical waters, but their utility within temperate rocky reef ecosystems has received less attention. Here we compared benthic monitoring data collected from virtual quadrats placed on photomosaics with traditional diver-based field quadrats to understand the strengths and weaknesses of using photomosaics for monitoring temperate rocky reef ecosystems. In north-eastern New Zealand, we evaluated these methods at three sites where sea urchin barrens were prevalent. We found key metrics (sea urchin densities, macroalgae canopy cover and benthic community cover) were similar between the two methods, but data collected via photogrammetry were quicker, requiring significantly less field time and resources, and allowed greater spatial coverage than diver-based field quadrats. However, the use of photomosaics was limited by high macroalgal canopy cover, shallow water and rough sea state which reduced stitching success and obscured substratum and understory species. The results demonstrate that photomosaics can be used as a resource efficient and robust method for effectively assessing and monitoring key metrics on temperate rocky reef ecosystems.

A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors

Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.

UAV Video-Based Approach to Identify Damaged Trees in Windthrow Areas

Disturbances in forest ecosystems are expected to increase by the end of the twenty-first century. An understanding of these disturbed areas is critical to defining management measures to improve forest resilience. While some studies emphasize the importance of quick salvage logging, others emphasize the importance of the deadwood for biodiversity. Unmanned aerial vehicle (UAV) remote sensing is playing an important role to acquire information in these areas through the structure-from-motion (SfM) photogrammetry process. However, the technique faces challenges due to the fundamental principle of SfM photogrammetry as a passive optical method. In this study, we investigated a UAV video-based technology called full motion video (FMV) to identify fallen and snapped trees in a windthrow area. We compared the performance of FMV and an orthomosaic, created by the SfM photogrammetry process, to manually identify fallen and snapped trees, using a ground survey as a reference. The results showed that FMV was able to identify both types of damaged trees due to the ability of video to deliver better context awareness compared to the orthomosaic, although providing lower position accuracy. In addition to its processing being simpler, FMV technology showed great potential to support the interpretation of conventional UAV remote sensing analysis and ground surveys, providing forest managers with fast and reliable information about damaged trees in windthrow areas.

COMBINING UNMANNED AERIAL SYSTEMS AND STRUCTURE FROM MOTION PHOTOGRAMMETRY TO RECONSTRUCT THE GEOMETRY OF GROINS

Abstract. In the context of coastal environment, the combined use of Unmanned Aerial Systems (UAS) with Structure-from-Motion (SfM) photogrammetry has been demonstrated to be a suitable tool to collect accurate geoinformation. This work aims at investigating the effectiveness of UAS survey to accurately map the geometry of rouble mound groins for monitoring the structural integrity. A set of nadiral images was processed through SfM photogrammetry to obtain the Digital Surface Model (DSM) of the groin. The DSM accuracy was evaluated through the comparison of five profiles measured by the traditional GNSS technique. Overall, vertical accuracy returned a root mean square error of 2.6 cm. The results suggest that UAS combined with SfM photogrammetry can improve the current monitoring of coastal engineering structures by providing high accurate geospatial products.

Developing a Guideline of Unmanned Aerial Vehicle’s Acquisition Geometry for Landslide Mapping and Monitoring

Remote sensing data and techniques are widely used for monitoring and managing natural or man-made disasters, due to their timeliness and their satisfactory accuracy. A key stage in disaster research is the detailed and precise mapping of an affected area. The current work examines the relationship that may exist between the acquisition geometry of Unmanned Aerial Vehicle (UAV) campaigns and the topographic characteristics of an investigated area, toward landslide mapping and monitoring that is as accurate as possible. In fact, this work, concerning the systematic research of the acquisition geometry of UAV flights over multiple active landslides, is conducted for the first time and is focused on creating a guideline for any researcher trying to follow the UAV photogrammetric survey during landslide mapping and monitoring. In particular, UAV flights were executed over landslide areas with different characteristics (land cover, slope, etc.) and the collected data from each area were classified into three groups depending on UAV acquisition geometry, i.e., nadir imagery, oblique imagery, and an integration of nadir and oblique imagery. High-resolution orthophotos and Digital Surface Models (DSMs) emerged from the processing of the UAV imagery of each group through structure-from-motion photogrammetry (SfM). Accuracy assessment was carried out using quantitative and qualitative comparative approaches, such as root mean square error calculation, length comparison, and mean center estimation. The evaluation of the results revealed that there is a strong relationship between UAV acquisition geometry and landslide characteristics, which is evident in the accuracy of the generated photogrammetric products (orthophotos, DSMs). In addition, it was proved that the synergistic processing of nadir and oblique imagery increased overall centimeter accuracy.

Monitoring Campsite Soil Erosion by Structure-from-Motion Photogrammetry: A Case Study of Kuro-dake Campsites in Daisetsuzan National Park, Japan

Camping in the mountain regions has several negative impacts, including soil erosion in the campsites. In many national parks, efforts to monitor and manage campsite soil erosion are insufficient or even lacking. Owing to the lack of implementation of formal management practices, the current and former Kuro-dake campsites in Daisetsuzan National Park (DNP) have suffered serious soil erosion. To gain more insights into campsite soil erosion, we investigated these two campsites by short-term monitoring through structure-from-motion (SfM) photogrammetry surveys with ground control points (GCPs). These surveys were conducted three times consecutively in the current (2017, 2018, and 2019) and former Kuro-dake campsites (2018, 2019, and 2020). Two sets of digital elevation models (DEMs) of the current and former campsites were produced with the resolutions of 0.015 and 0.025 m, respectively. We detected that the elevation changes exceeded by 0.03–0.04 m, using the DEMs of difference (DoDs) maps. Soil loss around the gullies was observed at each campsite. In the current campsite, soil losses of 2.20 and 0.30 m3 were identified in the periods of 2017–2018 and 2018–2019, respectively. In the former campsite, soil losses of 1.55 and 22.27 m3 were identified during 2018–2019 and 2019–2020, respectively. In addition, a large amount of exposed mineral soil with exposed rocks was observed at each campsite. Various erosion rates obtained in the short-term study indicated the importance of continuous monitoring. High-resolution and high-accuracy topographic products generated from the SfM photogrammetry survey enabled the detection of a small amount of campsite soil erosion and provided a new method to monitor campsite degradation. This study demonstrated that a simple closure of the former campsite in 1992 failed to reduce the impact of soil erosion. In the case of the current and former Kuro-dake campsites, burying the gullies with boulders and setting up boulders or wood fences at the termini of the gullies would be a potential solution to stop or mitigate further erosion. Thus, formal management including monitoring and maintenance of site conditions should be introduced to Kuro-dake as well as other unmanaged campsites in DNP.

Estimating Tree Defects with Point Clouds Developed from Active and Passive Sensors

Traditional inventories require large investments of resources and a trained workforce to measure tree sizes and characteristics that affect wood quality and value, such as the presence of defects and damages. Handheld light detection and ranging (LiDAR) and photogrammetric point clouds developed using Structure from Motion (SfM) algorithms achieved promising results in tree detection and dimensional measurements. However, few studies have utilized handheld LiDAR or SfM to assess tree defects or damages. We used a Samsung Galaxy S7 smartphone camera to photograph trees and create digital models using SfM, and a handheld GeoSLAM Zeb Horizon to create LiDAR point cloud models of some of the main tree species from the Pacific Northwest. We compared measurements of damage count and damage length obtained from handheld LiDAR, SfM photogrammetry, and traditional field methods using linear mixed-effects models. The field method recorded nearly twice as many damages per tree as the handheld LiDAR and SfM methods, but there was no evidence that damage length measurements varied between the three survey methods. Lower damage counts derived from LiDAR and SfM were likely driven by the limited point cloud reconstructions of the upper stems, as usable tree heights were achieved, on average, at 13.6 m for LiDAR and 9.3 m for SfM, even though mean field-measured tree heights was 31.2 m. Our results suggest that handheld LiDAR and SfM approaches show potential for detection and measurement of tree damages, at least on the lower stem.