Motion Photogrammetry Research Articles

Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs

Structure from motion (SfM) photogrammetry is an increasingly common technique for measuring landscape change over time by deriving 3D point clouds and surface models from overlapping photographs. Traditional change detection approaches require photos that are geotagged with a differential GPS (DGPS) location, which requires expensive equipment that can limit the ability of communities and researchers to perform frequent (i.e. daily, weekly, and/or monthly) surveys. Crowd-sourced photos can lower the barrier to entry and substantially increase the frequency of surveys, although such photos often lack accurate location information and can vary in quality. This paper presents a SfM approach for monitoring environmental change in high relief coastal environments that does not require all photos have DGPS location information and does not require field survey data. A 1.5 km section of coastal bluffs near the Elwha River Delta (Washington state) is used to demonstrate the efficacy of this approach. Photos of the bluff were collected with a digital SLR camera or phone camera while either on foot along the beach or from a boat as part of monitoring following removal of two large dams along the Elwha River during 2011–2013. Only 33% of photos had DGPS location information, whereas most photos had no location information or locations that were accurate to a couple of meters. All photos were processed using 3D, 4D, and fixed-floating (FF) SfM alignment methods and the resulting dense point clouds are used to compare the different alignment approaches with crowd-sourced photo sets. Results demonstrate that 4D and FF approaches are more likely to reconstruct and are more accurate than the 3D approach. While the 4D and FF have comparable accuracies, the FF approach is several orders of magnitude more efficient, as this method can leverage camera location information from relatively few photos to improve the accuracy of all aligned and derived products. Effectively utilizing crowd-sourced photos in SfM change detection can improve the frequency of surveying a landscape in a more cost-effective approach that also has potential for citizen-science engagement and communication. This is especially important for data-poor environments such as high-relief coastal cliffs and bluffs, where near-nadir imagery and LIDAR may fail to accurately capture near-vertical cliffs or bluff faces. Based on the analysis of different photo alignment and filtering approaches, we present suggested best practices for engaging citizen scientists in coastal cliff and bluff monitoring efforts through collecting photos amenable for SfM reconstruction.

Terrestrial and Airborne Structure from Motion Photogrammetry Applied for Change Detection within a Sinkhole in Thuringia, Germany

Detection of geomorphological changes based on structure from motion (SfM) photogrammetry is highly dependent on the quality of the 3D reconstruction from high-quality images and the correspondingly derived point precision estimates. For long-term monitoring, it is interesting to know if the resulting 3D point clouds and derived detectable changes over the years are comparable, even though different sensors and data collection methods were applied. Analyzing this, we took images of a sinkhole terrestrially with a Nikon D3000 and aerially with a DJI drone camera in 2017, 2018, and 2019 and computed 3D point clouds and precision maps using Agisoft PhotoScan and the SfM_Georef software. Applying the “multiscale model to model cloud comparison using precision maps” plugin (M3C2-PM) in CloudCompare, we analyzed the differences between the point clouds arising from the different sensors and data collection methods per year. Additionally, we were interested if the patterns of detectable change over the years were comparable between the data collection methods. Overall, we found that the spatial pattern of detectable changes of the sinkhole walls were generally similar between the aerial and terrestrial surveys, which were performed using different sensors and camera locations. Although the terrestrial data collection was easier to perform, there were often challenges due to terrain and vegetation around the sinkhole to safely acquire adequate viewing angles to cover the entire sinkhole, which the aerial survey was able to overcome. The local levels of detection were also considerably lower for point clouds resulting from aerial surveys, likely due to the ability to obtain closer-range imagery within the sinkhole.

Probabilistic hydro-geomorphological hazard assessment based on UAV-derived high-resolution topographic data: The case of Basento river (Southern Italy)

The combined use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) photogrammetry allows the collection and processing of high-resolution data on demand, which is key for the constant and detailed monitoring of the fluvial environment. In addition, through the ever-increasing development of new techniques of mapping and data processing (i.e., UAVs swarm, BVLOS flight missions, high-performance photogrammetry workflow), it is now possible to detect large areas at high-resolution, providing support for spatiotemporal insights into hydro-geomorphological processes and hazard assessment, in order to ensure an effective management and to prevent catastrophic phenomena (i.e., floods).The main goal of this paper is to use UAV-based high-resolution topographic data to constrain the probabilistic hazard assessment of extended reaches of Basento river (Basilicata, Italy). To demonstrate the influence of geomorphology and riverbed sediment on hazard assessment, a sensitivity analysis was carried out on the resolution of the UAV-derived DEMs; on the riverbed roughness coefficient resulting from photo-sieving analysis and on the morphological change detection over short-time ranges (2019–2021). We found that lower resolution DEMs lead to an increase of flooding probability (in several river cross-sections an increase even higher than 99 % resulted), and that a greater roughness coefficient involves an increase in the probability of flooding (with a maximum increase of about 9 %). Moreover, the multitemporal high-resolution outputs resulting from SfM allowed the identification of morphological changes, in short-times, caused by an anthropic modification of the river bank, which significantly affected the flooding hazard.

VERY HIGH-RESOLUTION 3D SURVEYING AND MODELLING EXPERIENCES IN CIVIL ENGINEERING APPLICATIONS

Abstract. In this paper some experiences in 3D modelling of objects with very high-resolution are described, carried out by the DICAM Geomatics group of the University of Bologna in multi-disciplinary contexts within the field of the Civil Engineering. In all the addressed case studies the main aim is the generation of a 3D model of the surface at a sub-millimetric scale, allowing a very accurate characterization of the surface geometry, useful for different purposes. 3D scanning and Structure from Motion photogrammetry have been used to generate the 3D models. In the paper the encountered problems and the adopted solutions in data surveying and processing are underlined, also discussing the added value of very high-resolution 3D modelling in multi-disciplinary activities.

Potential of mobile application based on structure from motion (SfM) photogrammetry to monitor slope fast erosion by runoff water

Runoff water may cause soil erosion, being this a concern affecting multiple areas. Monitoring tools can help design efficient solutions to prevent erosion. This is usually done using reliable tools such as terrestrial laser scanners (TLS). However, for very fast erosive processes, the rate at which changes occur is greater than the scanning time and this is a challenge. Structure from Motion (SfM) photogrammetry may solve this problem since it is possible to obtain 3D models from a few photographs, reducing the acquisition time to seconds. SfM technique was used in this paper to monitor ravine formation along a test carried out in the laboratory on a small slope (870 cm2) made of dry sand and subjected to a controlled water jet for 12 min. A mobile phone was used to take pictures at 2, 5, and 10 min of the test. All photos were taken at a distance of 80 cm from the slope. Photos were also taken before and after the test. In total, 5 sets of 9 photographs were taken. Photogrammetry-based Eyescloud3D application was used to obtain point clouds from the images taken with the mobile phone. These were later processed with CloudCompare software to analyse the geometry evolution of the erosion channel created by the runoff water. Because of the rapidly evolving system, it was not possible to control the lighting conditions when taking photographs. As a consequence, shadows prevent a good reconstruction where the erosion channel is deeper and narrower (less than 1 cm). Finally, a TLS was used to scan the final state of the slope and compare the result with that obtained using the SfM-based application. Similar results were obtained for 80% of the length of the erosion channel. However, deficiencies in the SfM reconstruction were found in the narrow areas mentioned above.

Improving UAV-SfM time-series accuracy by co-alignment and contributions of ground control or RTK positioning

Unmanned Aerial Vehicle Structure from Motion (UAV-SfM) photogrammetry is increasingly applied to topographic change detection, which requires multitemporal Digital Surface Models (DSMs) with high relative accuracy. Of these tools, Ground Control Points (GCPs) and an image processing method called co-alignment have so far shown promising results for change detection studies. However, there is still insufficient research on the extent of improving 3D model accuracy by combining these tools. In our study we assess absolute and relative accuracy of 120 DSMs generated through 24 workflows of UAV-SfM photogrammetry. Surveys were acquired with two different UAVs with Real Time Kinematic (RTK) or generic Global Navigation Satellite System (GNSS) positioning, and processed with varying combinations of survey co-alignment and GCPs. We show that co-alignment reduces relative errors to below 2 cm regardless of positioning quality. A single RTK survey in a co-aligned project is sufficient to obtain high absolute xy accuracy, but GCPs for at least one survey are still required to reduce absolute z error. We demonstrate that co-aligning RTK surveys with generic GNSS surveys results in RTK class accuracy for all surveys, even when mixed sensor grades are used. Our findings enable high-accuracy change detection with lower accuracy archived images when combined with RTK surveys. For future UAV-SfM change detection studies, we recommend to apply co-alignment for all studies, and where possible to include GCPs and RTK image coordinates in one survey to optimize absolute accuracy. Collecting and digitizing GCPs in multiple surveys has shown little additional benefit when co-alignment is applied and therefore may be omitted to save time, especially in challenging field conditions.

Estimation of Intertidal Oyster Reef Density Using Spectral and Structural Characteristics Derived from Unoccupied Aircraft Systems and Structure from Motion Photogrammetry

Eastern oysters (Crassostrea virginica) are an important component of the ecology and economy in coastal zones. Through the long-term consolidation of densely clustered shells, oyster reefs generate three-dimensional and complex structures that yield a suite of ecosystem services, such as nursery habitat, stabilizing shorelines, regulating nutrients, and increasing biological diversity. The decline of global oyster habitat has been well documented and can be attributed to factors, such as overharvesting, pollution, and disease. Monitoring oyster reefs is necessary to evaluate persistence and track changes in habitat conditions but can be time and labor intensive. In this present study, spectral and structural metrics of intertidal oyster reefs derived from Unoccupied Aircraft Systems (UAS) and Structure from Motion (SfM) outputs are used to estimate intertidal oyster density. This workflow provides a remote, rapid, nondestructive, and potentially standardizable method to assess large-scale intertidal oyster reef density that will significantly improve management strategies to protect this important coastal resource from habitat degradation.

Automatic Forest DBH Measurement Based on Structure from Motion Photogrammetry

Measuring diameter at breast height (DBH) is an essential but laborious task in the traditional forest inventory; it motivates people to develop alternative methods based on remote sensing technologies. In recent years, structure from motion (SfM) photogrammetry has drawn researchers’ attention in forest surveying for its economy and high precision as the light detection and ranging (LiDAR) methods are always expensive. This study explores an automatic DBH measurement method based on SfM. Firstly, we proposed a new image acquisition technique that could reduce the number of images for the high accuracy of DBH measurement. Secondly, we developed an automatic DBH estimation pipeline based on sample consensus (RANSAC) and cylinder fitting with the Least Median of Squares with impressive DBH estimation speed and high accuracy comparable to methods based on LiDAR. For the application of SfM on forest survey, a graphical interface software Auto-DBH integrated with SfM reconstruction and automatic DBH estimation pipeline was developed. We sampled four plots with different species to verify the performance of the proposed method. The result showed that the accuracy of the first two plots, where trees’ stems were of good roundness, was high with a root mean squared error (RMSE) of 1.41 cm and 1.118 cm and a mean relative error of 4.78% and 5.70%, respectively. The third plot’s damaged trunks and low roundness stems reduced the accuracy with an RMSE of 3.16 cm and a mean relative error of 10.74%. The average automatic detection rate of the trees in the four plots was 91%. Our automatic DBH estimation procedure is relatively fast and on average takes only 2 s to estimate the DBH of a tree, which is much more rapid than direct physical measurements of tree trunk diameters. The result proves that Auto-DBH could reach high accuracy, close to terrestrial laser scanning (TLS) in plot scale forest DBH measurement. Our successful application of automatic DBH measurement indicates that SfM is promising in forest inventory.

Influence of UAS Flight Altitude and Speed on Aboveground Biomass Prediction

The management of low-density savannah and woodland forests for carbon storage presents a mechanism to offset the expense of ecologically informed forest management strategies. However, existing carbon monitoring systems draw on vast amounts of either field observations or aerial light detection and ranging (LiDAR) collections, making them financially prohibitive in low productivity systems where forest management focuses on promoting resilience to disturbance and multiple uses. This study evaluates how UAS altitude and flight speed influence area-based aboveground forest biomass model predictions. The imagery was acquired across a range of UAS altitudes and flight speeds that influence the efficiency of data collection. Data were processed using common structures from motion photogrammetry algorithms and then modeled using Random Forest. These results are compared to LiDAR observations collected from fixed-wing manned aircraft and modeled using the same routine. Results show a strong positive relationship between flight altitude and plot-based aboveground biomass modeling accuracy. UAS predictions increasingly outperformed (2–24% increased variance explained) commercial airborne LiDAR strategies as acquisition altitude increased from 80–120 m. The reduced cost of UAS data collection and processing and improved biomass modeling accuracy over airborne LiDAR approaches could make carbon monitoring viable in low productivity forest systems.

Assessing the relative accuracy of coral heights reconstructed from drones and structure from motion photogrammetry on coral reefs

Low-altitude high-resolution aerial photographs allow for the reconstruction of structural properties of shallow coral reefs and the quantification of their topographic complexity. This study shows the scope and limitations of two-media (air/water) Structure from Motion—Multi-View Stereo reconstruction method using drone aerial photographs to reconstruct coral height. We apply this method in nine different sites covering a total area of about 7000 m2, and we examine the suitability of the method to obtain topographic complexity estimates (i.e., seafloor rugosity). A simple refraction correction and survey design allowed reaching a root mean square error of 0.1 m for the generated digital models of the seafloor (without the refraction correction the root mean square error was 0.2 m). We find that the complexity of the seafloor extracted from the drone digital models is slightly underestimated compared to the one measured with a traditional in situ survey method.

A remote field course implementing high-resolution topography acquisition with geomorphic applications

Abstract. Here we describe the curriculum and outcomes from a data-intensive geomorphic analysis course, “Geoscience Field Issues Using High-Resolution Topography to Understand Earth Surface Processes”, which pivoted to virtual in 2020 due to the COVID-19 pandemic. The curriculum covers technologies for manual and remotely sensed topographic data methods, including (1) Global Positioning Systems and Global Navigation Satellite System (GPS/GNSS) surveys, (2) Structure from Motion (SfM) photogrammetry, and (3) ground-based (terrestrial laser scanning, TLS) and airborne lidar. Course content focuses on Earth-surface process applications but could be adapted for other geoscience disciplines. Many other field courses were canceled in summer 2020, so this course served a broad range of undergraduate and graduate students in need of a field course as part of degree or research requirements. Resulting curricular materials are available freely within the National Association of Geoscience Teachers' (NAGT's) “Teaching with Online Field Experiences” collection. The authors pre-collected GNSS data, uncrewed-aerial-system-derived (UAS-derived) photographs, and ground-based lidar, which students then used in course assignments. The course was run over a 2-week period and had synchronous and asynchronous components. Students created SfM models that incorporated post-processed GNSS ground control points and created derivative SfM and TLS products, including classified point clouds and digital elevation models (DEMs). Students were successfully able to (1) evaluate the appropriateness of a given survey/data approach given site conditions, (2) assess pros and cons of different data collection and post-processing methods in light of field and time constraints and limitations of each, (3) conduct error and geomorphic change analysis, and (4) propose or implement a protocol to answer a geomorphic question. Overall, our analysis indicates the course had a successful implementation that met student needs as well as course-specific and NAGT learning outcomes, with 91 % of students receiving an A, B, or C grade. Unexpected outcomes of the course included student self-reflection and redirection and classmate support through a daily reflection and discussion post. Challenges included long hours in front of a computer, computing limitations, and burnout because of the condensed nature of the course. Recommended implementation improvements include spreading the course out over a longer period of time or adopting only part of the course and providing appropriate computers and technical assistance. This paper and published curricular materials should serve as an implementation and assessment guide for the geoscience community to use in virtual or in-person high-resolution topographic data courses that can be adapted for individual labs or for an entire field or data course.

Effects of gully control measures on sediment yield and connectivity in wooded rangelands

Gully rehabilitation is often applied as part of catchment management strategies aimed at reducing downstream sediment yields. However, the influences of gully control measures on the runoff and sediment transport processes in agroforestry systems have been seldom studied. In this paper, a thorough analysis of these processes was carried out in a valley-bottom gully located in a dehesa from SW Spain. The gully was monitored before and after implementation of different runoff and sediment control measures that included: gabion check-dams, brushwood check-dams and livestock exclusion through fencing. The aims of this work are: (1) to analyze the effect of the gully control measures on the hydrological dynamics and sediment load, and (2) to evaluate their effect on sediment connectivity at the catchment and channel scales. Changes in topography and connectivity were estimated using sequential Digital Elevation Models (DEMs) with a resolution of 0.02 m generated by Structure – from – Motion photogrammetry from aerial images acquired by an Unmanned Aerial Vehicle. Discharge and suspended sediment were monitored at the outlet. Results indicate that flood discharge was not influenced by the control measures, but suspended sediment concentration was reduced by 65%. The integration of the difference of connectivity index with topographic change maps highlighted the impact of the gully control measures on changes in sediment connectivity. A strong relationship between geomorphic dynamics and the spatial pattern of hydrological and sediment pathways were observed in the gully. The connectivity index (IC) increased in eroded areas, while deposition sites showed a decrease in the IC. Connectivity also decreased in the bank headcuts located within an area isolated from livestock. The implementation of runoff and sediment control measures in the channel was successful in stabilizing the expansion of the channel network and had beneficial effects in the short-term but further monitoring would be necessary to understand long-term effects.

Multi-temporal geomorphometric analysis to assess soil erosion under different tillage practices: A methodological case study

Soil erosion is one of the main environmental threats to sustainability and crop productivity in the agricultural sector. In agricultural fields, no-till management is considered a key approach for mitigating soil erosion. The measurement of soil erosion is particularly challenging, especially when surficial morphological changes are relatively small. Conventional experiments are commonly time-consuming and labour-intensive in terms of both field surveys and laboratory methods. On the other hand, the structure from motion (SfM) photogrammetry technique has enhanced the experimental activities by enabling the temporal evolution of soil erosion to be assessed through detailed micro-topography. This work presents a multitemporal quantification of soil erosion, using SfM through uncrewed aerial vehicles (UAV) survey for understanding the evolution of no-till (NT) and conventional tillage (CT) in experimental plots. Considering that morphological changes at the plot scale had millimetre orders of magnitude, it was necessary to minimise SfM errors (e.g., co-registration and interpolation) in volumetric estimates to reduce noise as much as possible. Therefore, a methodological workflow was developed to analyse and identify the effectiveness of multi-temporal SfMderived products, e.g., the conventional difference of digital terrain models (DoDs) and the less used differences of meshes (DoMs), for soil volume computations. We validated the erosion volumetric changes calculated from the SfM outputs with the amount of soil directly collected through conventional runoff and sediment measurements in the field. In this way, we recognised the most suitable estimation method. This study presents a novel approach for using DoMs instead of DoDs to describe the microtopography changes and sediment dynamics accurately. Another key and innovative aspect of this work often overlooked in soil erosion studies, was identifying the contributing sediment surface by delineating the channels potentially routing runoff directly to water collectors. The sediment paths and connected areas inside the plots were identified using a multi-temporal analysis of the sediment connectivity index for achieving the volumetric estimates, using DoMs (e.g., 2213 cm3 for no-till management system - NT and 38155 cm3 for conventional tillage regime - CT during September 2018-June 2020) that showed mild overestimation respect to field measurements results (e.g., 2359 cm3 for NT and 4525 cm3 for CT in the same period). This difference was attributable to other factors (e.g., the soil compaction processes) or variables rather than to photogrammetric or geometric ones. The developed workflow enabled low cos quantification of soil erosion dynamics for assessing the mitigation effects of no-till management that can also be extended in the future to different scales, based on SfM and UAV technologies.

A Digital Study of the Morphological and Stability Issues of a Delicate Wax-based Artwork

ABSTRACT Xenophanes is a figurine made of a waxy mixture and grey plasticine, created by Yannis Pappas at the end of the twentieth century. During its short period of existence, the figurine presented severe plastic deformation, structural, and stability issues, with detached or missing elements. The artwork’s earlier preserved states are documented by an archival photograph of 1994 and two casts dated to 2005. The physical treatment of its deformation is an irreversible intervention that may put the artwork in additional danger. The conservation of complex contemporary artworks comprises a challenging field of work, as the coexistence and aging of different and often pliable materials lead to multiple deformations. Their conservation treatments could be kept to a minimum for the preservation and understanding of the artworks, with the support of three-dimensional (3D) documentation and digital restoration. A digital restoration that simulates the physical treatment of an artwork aims to provide information that could assist with decisions made for its physical care by minimizing the risks. This paper examines the digital restoration of the small figurine Xenophanes following the steps of increased intervention of a probable physical treatment and how each step of this process may affect its stability. 3D documentation of the current condition of the artwork and its two casts was made utilizing optical laser scanning and structure from motion photogrammetry. The resulting 3D models facilitated the digital restoration of the artwork to its earlier states. The comparison and analysis of the 3D models and the digital restoration process provided information that could assist its physical treatment. The digital restoration of the complex plastic deformation of an artwork is a case that, to our knowledge, has not been addressed so far. The complexity of the progress, the ethical dilemmas that arise during the artwork’s restoration, and the reflection on the restoration of a cultural artifact only in the digital environment encourage the rethinking of conservation.

Virtual outcrop models: Digital techniques and an inventory of structural models from North-Northwest Iberia (Cantabrian Zone and Asturian Basin)

The first steps to study natural structures are data collection, their representation and their geological interpretation. There is no doubt that the development of digital techniques in recent times has facilitated these tasks. Here we present an inventory of virtual outcrop models from the Cantabrian Zone and Asturian Basin, North-Northwest Iberian Peninsula, and the procedure employed to obtain the data, construct the models and interpret them geologically. These models correspond to contractional folds and faults of Palaeozoic age, and to Mesozoic extensional structures affected by Cenozoic tectonic inversion in the form of folds and thrusts. The digital techniques and data employed are fieldwork, as well as Google Earth images, orthophotographs, stereoscopical pairs of photographs and virtual outcrop models, constructed using Structure from Motion photogrammetry based on images extracted from Google Earth or from photographs taken in the field using a tripod or unmanned aerial vehicles. The analysis of these models has provided us with geological information that would have been difficult to obtain using traditional techniques. Apart from their scientific interest, the examples shown may be helpful for structural geologists who wish to obtain 3D geological models, maps and sections, and additional structural information from field examples, as well as elements to prepare a virtual fieldtrip and/or for educational purposes.

A fast and practical method for determining particle size and shape by using smartphone photogrammetry

Over the past few decades, various image-based approaches for quantifying particle morphological indicators have been developed. But most of these methods are not applicable to field conditions. This study provides a fast and practical method for determining particle size and shape based on smartphone photogrammetry. Digital elevation models (DEMs) of the particles were created by using structure from motion photogrammetry and utilized to estimate the morphological characteristics of the particles. The size and shape of 110 coarse particles were determined by the proposed method and compared with the sieving method, hand measurement, and 2D image analysis method. The results show that the method is highly practical, with the measurement accuracies for particle length, width, and thickness being −2.7% ± 6.3%, −1.8% ± 9.9%, and 10.1% ± 11.5%, respectively. The proposed method has the potential to become a popular method for measuring particle size and shape in field conditions.

Drones, virtual reality, and modeling: communicating catastrophic dam failure

ABSTRACT Dam failures occur worldwide and can be economically and ecologically devastating. Communicating the scale of these risks to the general public and decision-makers is imperative. Two-dimensional (2D) dam failure hydraulic models inform owners and floodplain managers of flood regimes but have limitations when shared with non-specialists. This study addresses these limitations by constructing a 3D Virtual Reality (VR) environment to display the 1976 Teton Dam disaster case study using a pipeline composed of (1) 2D hydraulic model data (extrapolated into 3D), (2) a 3D reconstructed dam, and (3) a terrain model processed from UAS (Uncrewed Airborne System) imagery using Structure from Motion photogrammetry. This study validates the VR environment pipeline on the Oculus Quest 2 VR Headset with the criteria: immersion fidelity, movement, immersive soundscape, and agreement with historical observations and terrain. Through this VR environment, we develop an effective method to share historical events and, with future work, improve hazard awareness; applications of this method could improve citizen engagement with Early Warning Systems. This paper establishes a pipeline to produce a visualization tool for merging UAS imagery, Virtual Reality, digital scene creation, and sophisticated 2D hydraulic models to communicate catastrophic flooding events from natural or human-made levees or dams. Abbreviations: ASDSO: Association of State Dam Safety Officials; DEM: digitalelevation model; EWS: Early Warning System; HEC-RAS: Hydrologic EngineeringCenter-River Analysis System; HMD: Head-Mounted Display; NOAA: NationalOceanic and Atmospheric Administration; Reclamation: Bureau of Reclamation; United States Agency; SfM: Structure from Motion; 1D: one-dimensional; 2D:two-dimensional; 3D: three-dimensional; UAS: Uncrewed Aerial System (drone); US:United States; USACE: United States Army Corps of Engineers; VR: VirtualReality

On‐site geometric calibration of RPAS mounted sensors for SfM photogrammetric geomorphological surveys

AbstractThe application of structure from motion (SfM) photogrammetry for digital elevation model (DEM) and orthophoto generation from visible imagery enjoys ever‐growing popularity in geomorphological research. Photogrammetry experts, however, urge that a rigorous approach is a prerequisite for reliable results—a requirement that may conflict with real‐world survey. We present a method that unites the two disciplines, using the example of a challenging SfM photogrammetric survey at a Scottish river. Using simultaneous geometric pre‐calibration of a multi‐sensor remotely piloted aircraft system (RPAS), the method facilitates time‐efficient topography mapping and the integration of other wavelengths to create orthophotos providing additional surface information. The approach utilizes an on‐site 3D structure—for example, a building, as calibration object, by extracting coordinates of natural features from lidar scans and sensor imagery. We assess the workflow with specialized calibration software (VMS) and widely applied commercial SfM photogrammetric software (AM), using a DJI Phantom optical and a Workswell thermal sensor. We achieved calibration accuracies below one‐third (optical) and one‐quarter (thermal) of a pixel. Subsequently, we transfer the sensor parameters to pre‐calibrate the SfM application and compare the results to a self‐calibrated workflow. In a systematic experiment using the optical river survey dataset, we assess the effectiveness of pre‐calibration, oblique imagery, scale variation and masking to mitigate systematic DEM errors. Opposing trends show between the calibration strategies. Decreasing network complexity (i.e., flying heights/view angles) improves pre‐calibrated but compromises self‐calibrated scenarios. Pre‐calibrating (VMS) imagery from a single height (30 m nadir) yielded the best results. This finding could have implications for geomorphological surveys, in which single‐scale datasets are widespread practice, despite the literature's urge towards more complex imaging networks. The self‐calibrated results legitimise this insistence: The same dataset resulted in pronounced dome‐shaped DEM distortion, indicating systematic errors, whereas additional flying heights and angles significantly improved the results.

Estimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds

Urban forest is a crucial part of urban ecological environment. The accurate estimation of its tree aboveground biomass (AGB) is of significant value to evaluate urban ecological functions and estimate urban forest carbon storage. It has a high accuracy to estimate the forest AGB with field measured canopy structure parameters, but unsuitable for large-scale operations. Limited by low spatial resolution or spectral saturation, the estimated forest AGBs based on various satellite remotely sensed data have relatively low accuracies. In contrast, Unmanned Aerial Vehicle (UAV) remote sensing provides a promising way to accurately estimate the tree AGB of fragmented urban forest. In this study, taking an artificial urban forest in Ma'anxi Wetland Park in Chongqing City, China as an example, we used UAVs equipped with a digital camera and a LiDAR to acquire two point cloud data. One was produced from overlapping images using Structure from Motion (SfM) photogrammetry, and the other was resolved from laser scanned raw data. The dual point clouds were combined to extract individual tree height (H) and canopy radius (Rc), which were then input to the newly established allometric equation with tree H and Rc as predictor variables to obtain the AGBs of all dawn redwood trees in study area. In accuracy assessment, the coefficient of determination (R2) and Root Mean Square Error (RMSE) of extracted H were 0.9341 and 0.59 m; the R2 and RMSE of extracted Rc were 0.9006 and 0.28 m; the R2 and RMSE of estimated AGB were 0.9452 and 17.59 kg. These results proved the feasibility and effectiveness of applying dual-source UAV point cloud data and the new allometric equation on H and Rc to accurate AGB estimation of urban forest trees.

Quantifying spatial distribution of interrill and rill erosion in a loess at different slopes using structure from motion (SfM) photogrammetry

The spatial distribution of interrill and rill erosion is essential for unravelling soil erosion principles and the application of soil and water conservation practices. To quantify interrill and rill erosion and their spatial development, four 30-min rainfalls at 90 mm h−1 intensity were consecutively simulated on runoff plots packed with a loess at six slopes of 10°, 15°, 20°, 25°, 30° and 35°. The soil surface was measured using the structure from motion (SfM) photogrammetry upon each simulation run, and the runoff and sediment samples were collected and measured at every 10 min. Rills did not develop until the third simulation run. During the initial two runs, the lower third section was more severely eroded than the upper and middle thirds along the slope direction, yet the interrill erosion was statistically uniform from left to right. Rills tended to emerge by both sidewalls and in the lower portion in the third run. The corresponding rill erosion increased with slope from 10° to 20° and then decreased for the slopes steeper, which was consistent with the slope trend of the sediment yield directly measured. The rills expanded substantially primarily via head retreat and to a lesser extent via sideward erosion after receiving another 30-min rainfall. Rill erosion contributed 69.3% of the total erosion loss, and shifted the critical slope corresponding to the maximum loss from 20° to 25°. These findings demonstrate the significance of rill erosion not only in total soil loss but also in its relation to slope, as well as the effectiveness of SfM photogrammetry in quantifying interrill and rill erosion.