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Emerging technology has immense potential to increase the scale and efficiency of marine conservation. One such technology is large-area imaging (LAI), which relies on structure-from-motion photogrammetry to create composite products, including 3-dimensional (3-D) environmental models, that are larger in spatial extent than the individual images used to create them. Use of LAI has become widespread in certain fields of marine science, primarily to measure the 3D structure of benthic ecosystems and track change over time. However, the use of LAI in the field of marine conservation appears limited. We conducted a review of the coral reef literature on the use of LAI to identify research themes and regional trends in applications of this technology. We also surveyed 135 coral reef scientists and conservation practitioners to determine community familiarity with LAI, evaluate barriers practitioners face in using LAI, and identify applications of LAI believed to be most exciting or relevant to coral conservation. Adoption of LAI was limited primarily to researchers at institutions based in advanced economies and was applied infrequently to conservation, although conservation practitioners and survey respondents from emerging economies indicated they expect to use LAI in the future. Our results revealed disconnect between current LAI research topics and conservation priorities identified by practitioners, highlighting the need for more diverse, conservation-relevant research using LAI. We provide recommendations for how early adopters of LAI (typically Global North scientists from well-resourced institutions) can facilitate access to this conservation technology. These recommendations include developing training resources, creating partnerships for data storage and analysis, publishing standard operating procedures for LAI workflows, standardizing methods, developing tools for efficient data extraction from LAI products, and conducting conservation-relevant research using LAI.

Measuring grain sizes in gravel‐bed rivers is crucial when studying river dynamics and sediment transport. Automated methodologies have been developed in recent years for detecting individual grains and measuring their size on digital imagery. These object‐based methodologies have mainly been applied to handheld imagery. Low‐cost and high‐resolution orthoimages covering long river reaches are nowadays accessible with the improvements in uncrewed aerial vehicles (UAV) and structure‐from‐motion (SfM) photogrammetry. Applying object‐based grain‐sizing methodologies to such orthoimages may provide wide‐scale information about the grain size spatial distribution along streambeds. We examined how accurate three object‐based models (BASEGRAIN, PebbleCountsAuto and GALET) were, by comparing their outcomes to in‐field manual measurements of grain sizes and manual grain labelling. We found that BASEGRAIN and PebbleCountsAuto underestimated grain sizes on average, whereas GALET generally overestimated grain size percentiles. Grain size measurements obtained by manually labelling grain features were consistent with in‐field measurements. [ABSTRACT FROM AUTHOR]

Emerging technology has immense potential to increase the scale and efficiency of marine conservation. One such technology is large‐area imaging (LAI), which relies on structure‐from‐motion photogrammetry to create composite products, including 3‐dimensional (3‐D) environmental models, that are larger in spatial extent than the individual images used to create them. Use of LAI has become widespread in certain fields of marine science, primarily to measure the 3D structure of benthic ecosystems and track change over time. However, the use of LAI in the field of marine conservation appears limited. We conducted a review of the coral reef literature on the use of LAI to identify research themes and regional trends in applications of this technology. We also surveyed 135 coral reef scientists and conservation practitioners to determine community familiarity with LAI, evaluate barriers practitioners face in using LAI, and identify applications of LAI believed to be most exciting or relevant to coral conservation. Adoption of LAI was limited primarily to researchers at institutions based in advanced economies and was applied infrequently to conservation, although conservation practitioners and survey respondents from emerging economies indicated they expect to use LAI in the future. Our results revealed disconnect between current LAI research topics and conservation priorities identified by practitioners, highlighting the need for more diverse, conservation‐relevant research using LAI. We provide recommendations for how early adopters of LAI (typically Global North scientists from well‐resourced institutions) can facilitate access to this conservation technology. These recommendations include developing training resources, creating partnerships for data storage and analysis, publishing standard operating procedures for LAI workflows, standardizing methods, developing tools for efficient data extraction from LAI products, and conducting conservation‐relevant research using LAI. [ABSTRACT FROM AUTHOR]

Accurately quantifying rates of soil erosion requires capturing both the volumetric nature of the visible, convergent fluvial pathways (also known as rills) and the subtle nature of the less-visible, diffuse pathways (interrill areas). The aim of this study was to use Rare Earth Oxide (REO) tracers and Structure-from-Motion (SfM) photogrammetry to elucidate retrospective information about soil erosion rates and sediment sources during different soil erosion conditions, within a controlled laboratory environment. The experimental conditions created erosion events consistent with diffuse and convergent erosion processes. REO tracers allowed the sediment transport distances of over 2 m to be described, and helped resolved the relative contribution of diffuse and convergent soil erosion; interrill areas were also identified as a significant sediment sources soil loss under convergent erosion conditions. While the potential for SfM photogrammetry to resolve sub-millimetre elevations changes was demonstrated, under some conditions non-erosional changes in surface elevation, such as compaction, exceeded volumes of soil loss via diffuse erosion. The discrepancies between SfM Photogrammetry calculations and REO tagged sediment export were beneficial, identifying that during soil erosion events sediment in both aggregate and particle form is deposited within the convergent features, even when the rill extended the full length of the soil surface. The combination of SfM photogrammetry and REO tracers has provided a novel platform for building a spatial understanding of patterns of soil loss and source apportionment between rill and interrill erosion.

Remote sensing enables us to measure fluvial systems without disrupting their dynamics. Small‐scale physical models of rivers allow us to observe their geomorphic evolution, but we need remote sensing methods to monitor these laboratory landscapes without altering their flow or topography, just as with field‐scale rivers. In this paper, we review how experimental geomorphologists have adapted remote sensing for the laboratory. We consider how remote methods to monitor model topography, flow depth, velocity and planform have been employed, enabling uninterrupted experimental evolution. We also explore the transfer of techniques between field‐scale and experimental remote sensing; the controlled conditions in the lab aided the development of some methods, while others benefited from airborne deployment. We consider recent developments offered by laboratory remote sensing, including through‐water laser scanning and adaptations of structure‐from‐motion photogrammetry; we also consider new challenges associated with these developments, such as computational power. Finally, we discuss new research problems that laboratory remote sensing is opening up to geomorphology. We hope this review will be useful for experimentalists seeking to collect data remotely, continuously and/or cost‐effectively. [ABSTRACT FROM AUTHOR]

Regular monitoring is essential for vulnerable coastal locations such as areas of landward retreat. However, for coastal practitioners, surveying is limited by budget, specialist personnel/equipment and weather. In combination structure-from-motion and multi-view stereo (SfM-MVS) has helped to improve accessibility to topographic data acquisition. Pole-mounted cameras with SfM-MVS have gained traction but to guarantee coverage and reconstruction quality, greater understanding of camera position and interaction is required. This study uses a multi-camera array for image acquisition and reviews processing procedures in Agisoft Photoscan (Metashape). The camera rig was deployed at three sites and results were verified against a terrestrial laser scanner (TLS) and independent precision estimates. The multi-camera approach provided effective image acquisition ~11 times faster than the TLS. Reconstruction quality equalled (>92% similarity) the TLS, subject to processing parameters. A change in the image alignment parameter demonstrated a significant influence on deformation, reducing reprojection error by~94%. A lower densification parameter ('High') offered results ~4.39% dissimilar from the TLS at 1/8th of the processing time of other parameters. Independent precision estimates were <8.2 mm for x, y and z dimensions. These findings illustrate the potential of multi-camera systems and the influence of processing on point cloud quality and computation time. [ABSTRACT FROM AUTHOR]

Abstract Non‐forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non‐forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low‐stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave‐one‐out cross‐validation of 3.9%. Biomass per‐unit‐of‐height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much‐needed information required to calibrate and validate the vegetation models and satellite‐derived biomass products that are essential to understand vulnerable and understudied non‐forested ecosystems around the globe.

Three-dimensional (3D) habitat complexity is a primary driver of organism distribution and community structure across ecosystems. Identifying the specific metrics and spatial scales at which complexity is functionally important for communities is therefore a critical component in forecasting ecosystem function. Here we pair fish species traits with multiple metrics from habitat photogrammetry to evaluate the most important measures and scales of 3D complexity driving ecological functions within one of the most structurally diverse ecosystems on the planet: coral reefs. From May to July 2019, we collected high-resolution (1 cm) large- and small-scale intra-habitat (25 m2) structural complexity data across eight reefscapes (∼2500 m2) and conducted co-located fish functional group surveys in the Florida Keys, FL, USA. We used a hierarchical clustering analysis to group 80 observed fish species by four traits related to habitat use (social level, body size, crypsis, activity period) and feeding guild to generate mechanistic predictions about fish-habitat relationships. Evaluating relationships between the resulting trait-based functional groups (k = 9) and four metrics of intra-habitat complexity (large-scale vertical relief, and small-scale vector ruggedness [VRM], VRM deviation, and profile curvature) revealed that trait groups respond independently to the various measures and scales of reef complexity. While large-scale complexity (relief) is strongly related to the presence of solitary, cryptic, nocturnal carnivores, likely due to prey availability as well as day-time refuge opportunities, herbivore abundance is unaffected by increasing vertical relief, potentially due to predator avoidance. Instead, gregarious (i.e., schooling) herbivores increase with small-scale complexity measured by VRM and VRM deviation across reefscapes, while less gregarious herbivores only respond to small-scale complexity when these same measures occur in low-relief habitat, possibly due to a tradeoff between grazing resource availability and predator visibility. Our results reveal how unique elements of complexity provided by both biotic benthic communities as well as large-scale habitat features like vertical relief are differentially important to fish functional groups. The general relationships we identified using traits provide a framework for predicting fish community responses to changes in specific measures of structural complexity on coral reefs globally. Our work illustrates how preserving 3D habitat complexity by protecting or augmenting (e.g., via restoration) structure-forming organisms can support diverse organismal communities and overall ecosystem productivity.

USS Emmons is an American Second World War battleship of that sunk off Kouri Island in Okinawa, Japan, as a result of participating in the Battle of Okinawa in 1945. It was attacked by Kamikaze Special Attack Units and became inoperable. A high-quality 3D Structure-from-Motion (SfM) model was created that served to plan diver-based investigations and record the current state of the site. Together with the war-related documents from US and Japan, this research has revealed scientific evidence that has been used to reconstruct the battle of Emmons and the kamikaze planes. [ABSTRACT FROM AUTHOR]

Lava domes form by the effusive eruption of high-viscosity lava and are inherently unstable and prone to collapse, representing a significant volcanic hazard. Many processes contribute to instability in lava domes and can generally be grouped into two categories: active and passive. Active collapses are driven directly by lava effusion. In contrast, passive collapses are not correlated with effusion rate, and thus represent a hazard that is more difficult to assess and forecast. We demonstrate a new workflow for assessing and forecasting passive dome collapse by examining a case study at Sinabung Volcano (North Sumatra, Indonesia). We captured visual images from the ground in 2014 and from unoccupied aerial systems (UAS) in 2018 and used structure-from-motion photogrammetry to generate digital elevation models (DEMs) of Sinabung’s evolving lava dome. By comparing our DEMs to a pre-eruption DEM, we estimate volume changes associated with the eruption. As of June 2018, the total erupted volume since the eruption began is 162 × 106 m3. Between 2014 and 2018, 10 × 106 m3 of material collapsed from the lava flow due to passive processes. We evaluate lava dome stability using the Scoops3D numerical model and the DEMs. We assess the passive collapse hazard and analyze the effect of lava material properties on dome stability. Scoops3D is able to hindcast the location and volume of passive collapses at Sinabung that occurred during 2014 and 2015, and we use the same material properties to demonstrate that significant portions of the erupted lava potentially remain unstable and prone to collapse as of late 2018, despite a pause in effusive activity earlier that year. This workflow offers a means of quantitatively assessing passive collapse hazards at active or recently active volcanoes.

Regular monitoring is essential for vulnerable coastal locations such as areas of landward retreat. However, for coastal practitioners, surveying is limited by budget, specialist personnel/equipment and weather. In combination structure-from-motion and multi-view stereo (SfM-MVS) has helped to improve accessibility to topographic data acquisition. Pole-mounted cameras with SfM-MVS have gained traction but to guarantee coverage and reconstruction quality, greater understanding of camera position and interaction is required. This study uses a multi-camera array for image acquisition and reviews processing procedures in Agisoft Photoscan (Metashape). The camera rig was deployed at three sites and results were verified against a terrestrial laser scanner (TLS) and independent precision estimates. The multi-camera approach provided effective image acquisition ~11 times faster than the TLS. Reconstruction quality equalled (>92% similarity) the TLS, subject to processing parameters. A change in the image alignment parameter demonstrated a significant influence on deformation, reducing reprojection error by~94%. A lower densification parameter (‘High’) offered results ~4.39% dissimilar from the TLS at 1/8th of the processing time of other parameters. Independent precision estimates were x, y and z dimensions. These findings illustrate the potential of multi-camera systems and the influence of processing on point cloud quality and computation time.

Advances in image-based remote sensing using unmanned aerial vehicles (UAV) and structure-from-motion (SfM) photogrammetry continue to improve our ability to monitor complex landforms over representative spatial and temporal scales. As with other water-worked environments, coastal sediments respond to shaping processes through the formation of multi-scale topographic roughness. Although this topographic complexity can be an important marker of hydrodynamic forces and sediment transport, it is seldom characterized in typical beach surveys due to environmental and technical constraints. In this study, we explore the feasibility of using SfM photogrammetry augmented with an RTK quadcopter for monitoring the coastal topographic complexity at the beach-scale in a macrotidal environment. The method had to respond to resolution and time constraints for a realistic representation of the topo-morphological features from submeter dimensions and survey completion in two hours around low tide to fully cover the intertidal zone. Different tests were performed at two coastal field sites with varied dimensions and morphologies to assess the photogrammetric performance and eventual means for optimization. Our results show that, with precise image positioning, the addition of a single ground control point (GCP) enabled a global precision (RMSE) equivalent to that of traditional GCP-based photogrammetry using numerous and well-distributed GCPs. The optimal model quality that minimized vertical bias and random errors was achieved from 5 GCPs, with a two-fold reduction in RMSE. The image resolution for tie point detection was found to be an important control on the measurement quality, with the best results obtained using images at their original scale. Using these findings enabled designing an efficient and effective workflow for monitoring coastal topographic complexity at a large scale. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) structure of living coral communities provides frictional resistance to waves and currents. Coral bleaching events can lead to a shift in coral assemblages toward stress-tolerant colonies, potentially reducing reef structural complexity and, in turn, wave attenuation. This is a particular concern in low-lying coastal regions at risk from sea-level rise. In this study, we examined trade-offs between reef resilience and reef structural complexity (defined into three distinct variables, i.e., surface rugosity, standard deviation of elevation, and terrain ruggedness) in Kiribati's Tarawa and Abaiang Atolls, which are subject to frequent El Niño-driven heat stress. Analysis of benthic cover data and 3D reconstructions of the fore reefs indicate that structural complexity increases with coral cover, rather than coral diversity, although the relationship depends on the metric used and on the morphology of the dominant coral species. Contrary to expectations, surface rugosity and standard deviation of elevation were not significantly different between the bleaching-resistant reefs of South Tarawa, dominated by the encrusting species Porites rus, and the more diverse sites in Abaiang and North Tarawa; terrain ruggedness was significantly greater at South Tarawa sites. A wave attenuation model, however, suggested that wave energy may nonetheless be higher in South Tarawa due to years of local mining of reef rock from the reef flat. Taken together, the results suggest that the survival of stress-tolerant corals could mitigate against losses of structural complexity from repeated bleaching events. These findings illustrate the need for more research bridging ecology and geology to establish how wave attenuation is altered by climate-driven regime shifts on coral reefs. [ABSTRACT FROM AUTHOR]

Flood events are the agents of change on alluvial fans. However, most alluvial fan experiments have used constant flows to model fans and the channels upon them. Here, we present results from a series of alluvial fan experiments with different patterns of flow variation (i.e., different hydrograph shapes). We conducted experiments with (a) constant flow, (b) alternating high and low flows, (c) a moderate flood peak that decayed slowly, alternating with a constant low flow, and (d) a high flood peak that decayed rapidly, alternating with a constant low flow. We found that different hydrographs generated fans with different slopes, even though all experiments had the same mean flow and sediment supply. In addition, higher peak flows led to increased lateral migration rates and increased erosion and deposition. These results challenge the notion that a single representative flow can be used to approximate the geomorphic effects of a range of flows in a natural stream. Moreover, our findings indicate that hydrograph shape can govern the geomorphic impact of a flood event. This means that altered basin hydrology (for instance, through land cover change) likely exerts an important impact on geomorphic change and natural hazards on alluvial fans. Plain Language Summary: The steep streams that flow down alluvial fans experience a wide range of high and low flows. Here, we use a series of experiments with a small‐scale model of a fan to explore the importance of this flow variability. We show how the type of flow variability influences hazards such as stream bank erosion, or the rapid inundation of areas that were previously dry. Our results suggest that when high flows occur in these steep streams, their size and duration control their impact on the stream channel. Anything that changes the size and duration of high flows (for instance, a change to the landscape upstream) could alter the severity of future flood impacts. Key Points: Experiments with the same mean flow but different hydrograph shapes generated alluvial fans with different slopesLateral migration and geomorphic change increased non‐linearly with flow, so that small changes to hydrographs impacted flood responseA single, constant flow is inappropriate to represent the wide range of flows on natural fans [ABSTRACT FROM AUTHOR]

Non‐forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non‐forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low‐stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave‐one‐out cross‐validation of 3.9%. Biomass per‐unit‐of‐height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much‐needed information required to calibrate and validate the vegetation models and satellite‐derived biomass products that are essential to understand vulnerable and understudied non‐forested ecosystems around the globe. [ABSTRACT FROM AUTHOR]

The Upper Rhone Valley (Valais, Switzerland) has been heavily modified over the past 200 years by human activity and natural processes. A qualitative analysis of the morphological and land-use evolution of the Rhone River floodplain since the end of the eighteenth century was carried out using historical maps from 1780 to 1860 processed with Structure-from-Motion (SfM) and Geographical Information System (GIS) tools. This study aims to produce a long-term analysis of river management and land-use change in a stretch of the Upper Rhone Valley around the town of Sion based on a time series of maps, realised in the years 1780–1802, 1820–1845, 1847, 1850s, 1852–1857, 1859–1860. The historical maps were digitised, and for each of the corresponding periods, a map was produced within a GIS. The comparison of the maps was completed by using documentary sources or subsequent studies. With the intention to identify the fluvial landscape changes and past river management, six multitemporal maps were produced. Finally, this research aims to provide helpful diachronic information for planning a future sustainable landscape development in Valais.

The complex stratification of tropical forests is a key feature that directly contributes to high aboveground biomass (AGB) and species diversity. This study aimed to explore the vertical patterns of AGB and tree species diversity in the tropical forest of Pasoh Forest Reserve, Malaysia. To achieve this goal, we used a combination of field surveys and drone technology to gather data on species diversity, tree height ( H ), and tree diameter at breast height ( D ). As all trees in the 6 ha plot were tagged and identified, we used the data to classify the taxonomy and calculate species diversity indices. We used unmanned aerial vehicle-based structure-from-motion photogrammetry to develop a Digital Canopy Height Model to accurately estimate H . The collected data and previous datasets were then used to develop Bayesian height–diameter (HD) models that incorporate taxonomic effects into conventional allometric and statistical models. The best models were selected based on their performance in cross-validation and then used to estimate AGB per tree and the total AGB in the plot. Results showed that taxonomic effects at the family and genus level improved the HD models and consequent AGB estimates. The AGB was the highest in the higher layers of the forest, and AGB was largely contributed by larger trees, especially specific families such as Dipterocarpaceae, Euphorbiaceae, and Fabaceae. In contrast, species diversity was the highest in the lower layers, whereas functional diversity was the highest in the middle layers. These contrasting patterns of AGB and species diversity indicate different roles of forest stratification and layer-specific mechanisms in maintaining species diversity. This study highlights the importance of considering taxonomic effects when estimating AGB and species diversity in tropical forests. These findings underscore the need for a more comprehensive understanding of the complex stratification of tropical forests and its impact on the forest ecosystem.

Rural-urban migration often triggers additional demand for housing and infrastructural development to cater for the growing population in urban areas. Consequently, town planners and urban development authorities need to understand the urban development trend to make sustainable urban planning decisions. Yet, methods to analyse changes and trends in urban spatial development are often complex and require costly data collection. This article thus presents a simplified method to analyse the urban development trend in an area. The method integrates Google Earth (GE) historical imagery (baseline data) and unmanned aerial vehicle (UAV) photogrammetry (recent data) to quantify the changes over time. This approach can be applied to study the urban development trends in low-income countries with budget constraints. The method is discussed under four main headings: (1) background, (2) method details, (3) limitations, and (4) conclusion.•Google Earth historical image can be extracted with its associated world file.•The population of an area can be estimated by using average household size data and the number of residential buildings in the area.•The building height ratio can be used to ascertain if the land is being used parsimoniously., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Uncrewed aerial systems (UAS), combined with structure‐from‐motion photogrammetry, has already proven to be very powerful for a wide range of geoscience applications and different types of UAS are used for scientific and commercial purposes. However, the impact of the UAS used on the accuracy of the point clouds derived is not fully understood, especially for the quantitative analysis of geomorphic changes in complex terrain. Therefore, in this study, we aim to quantify the magnitude of systematic and random error in digital elevation models derived from four commonly used UAS (XR6/Sony α6000, Inspire 2/X4s, Phantom 4 Pro+, Mavic Pro) following different flight patterns. The vertical error of each elevation model is evaluated through comparison with 156 GNSS reference points and the normal distribution and spatial correlation of errors are analysed. Differences in mean errors (−0.4 to −1.8 cm) for the XR6, Inspire 2 and Phantom 4 Pro are significant but not relevant for most geomorphological applications. The Mavic Pro shows lower accuracies with mean errors up to 4.3 cm, thus showing a higher influence of random errors. QQ plots revealed a deviation of errors from a normal distribution in almost all data. All UAS data except Mavic Pro exhibit a pure nugget semivariogram, suggesting spatially uncorrelated errors. Compared to the other UAS, the Mavic Pro data show trends (i.e. differences increase with distance across the survey—doming) and the range of semivariances is 10 times greater. The lower accuracy of Mavic Pro can be attributed to the lower GSD at the same flight altitude and most likely, the rolling shutter sensor has an effect on the accuracy of the camera calibration. Overall, our study shows that accuracies depend highly on the chosen data sampling strategy and that the survey design used here is not suitable for calibrating all types of UAS camera equally. [ABSTRACT FROM AUTHOR]

The dynamics of Mediterranean ephemeral channels (MEC) is an interesting geomorphological topic as the extrinsic and intrinsic factors influencing this geomorphic system have been exposed to important and recent changes. It is crucial to carry out studies of these systems at suitable temporal scales (e.g. decades) to understand the dynamics of the model and the adaptation to different perturbations. In this work, we test the suitability of archival aerial imagery and structure-from-motion photogrammetry (SfM) to produce 3D models and orthophotographs of MEC for different dates and to quantify morphological changes. Several reaches were selected from two representative MEC in the Segura River Catchment (Rambla de Algeciras y Rambla de Valdelentisco) and three from a MEC in the Ebro River Catchment (Barranco de Tudela). Archival aerial photographs from 1956 (dataset known as "vuelo americano B") and 1973-1986 (dataset known as "vuelo interministerial") together with natural ground control points (GCPs) surveyed by a Global Navigation Satellite System to fed SfM and produce point clouds, digital elevation models and orthophotographs. The classical SfM workflow was adapted to work with the archival aerial imagery, i.e. adding fiducial markers, masking the photographs, using of natural permanent GCPs, etc. The results showed a root mean square error in the cartographic products that varied from 0,62 to 0,85 m with volumetric point densities in the resulting point clouds from 1,03 to 4,47 pts·m-3. Hence, the proposed methodological approach may be used to quantify important geomorphic changes (>1 m), to characterize the morphology of MEC in the past and to include the resulting cartographic products with today spatial information for a better understanding of the dynamics. [ABSTRACT FROM AUTHOR]

Avulsion is a key process in building alluvial fans, but it is also a formidable natural hazard. Based on laboratory experiments monitored with novel high‐frequency photogrammetry, we present a new model for avulsion on widely graded gravel fans. Previous experimental studies of alluvial fans have suggested that avulsion occurs in a periodic autogenic cycle, that is thought to be mediated by the gradient of the fan and fan‐channel. However, those studies measured gradients at low spatial or temporal resolutions, which capture temporally or spatially averaged topographic evolution. Here, we present high‐resolution (1 mm), high‐frequency (1‐minute) topographic data and orthophotos from an alluvial fan experiment. Avulsions in the experiment were rapid and, in contrast to some previous experimental studies, avulsion occurrence was aperiodic. Moreover, we found little evidence of the back‐filling observed at coarser temporal and spatial resolutions. Our observations suggest that avulsion is disproportionately affected by sediment accumulation in the channel, particularly around larger, less mobile grains. Such in‐channel deposition can cause channel shifting that interrupts the autogenic avulsion cycle, so that avulsions are aperiodic and their timing is more difficult to predict. [ABSTRACT FROM AUTHOR]

• Cost-effective photogrammetry-based methodology for surveying historical structures. • Application of the technique to build the FEM model of an historical structure. • The 3D model considers 7 types of materials, including adobe and brick/stone masonry. • Non-linear pushover analysis and N2 method to evaluate the seismic response. • The results of the seismic assessment can pave the way for informed preservation. This research presents a cost-effective surveying methodology to assist the seismic assessment of complex heritage buildings, based on terrestrial structure-from-motion (SfM) photogrammetry. The method was applied to the study of the seismic performance of the church of San Juan Bautista – Inca temple of Huaytará, Peru, an emblematic case study due to its complex architecture and coexistence of different construction materials. The geometrical model for the seismic assessment was developed with an error of less than 2 % using SfM photogrammetry. Non-linear static pushover analyses were performed on 3D FEM models of the nave and the towers to evaluate their individual response under seismic loading. Mechanical properties of different structural materials of the church were evaluated based on laboratory experimental tests on mortar and adobe, contemporary and ancient fired brick, Inca stone, colonial stone and rubble stone units. Non-linear pushover analyses were conducted in four directions perpendicular to the perimeter walls, and the response of the structure was compared with the seismic demand specified in Peruvian Standards. The simulations show that damage-prone areas are the western and eastern facades, with cracking at the connections between orthogonal walls, as well as at the interface of adobe masonry with Inca stone masonry. The towers exhibit similar seismic response, with lower strength capacities compared to the main nave. In this case, flexural overturning mechanisms and cracking at the interface between stone and adobe masonry were observed. The displacement-based seismic assessment using the N2 method shows that a peak ground acceleration of 0.21 g could lead to the collapse of the north and south facades of the main nave. The towers showed a much smaller capacity with PGA leading to collapse of approximately 0.09 g. Overall, this study contributes to the understanding of the seismic performance of the Huaytará-Huancavelica church, highlighting vulnerabilities and providing valuable information for its preservation and future interventions. Future investigations should focus on on-site tests that will allow the estimation of the effect of existing damage on the structural response and their incorporation in the numerical model. [ABSTRACT FROM AUTHOR]

Advances in image-based remote sensing using unmanned aerial vehicles (UAV) and structure-from-motion (SfM) photogrammetry continue to improve our ability to monitor complex landforms over representative spatial and temporal scales. As with other water-worked environments, coastal sediments respond to shaping processes through the formation of multi-scale topographic roughness. Although this topographic complexity can be an important marker of hydrodynamic forces and sediment transport, it is seldom characterized in typical beach surveys due to environmental and technical constraints. In this study, we explore the feasibility of using SfM photogrammetry augmented with an RTK quadcopter for monitoring the coastal topographic complexity at the beach-scale in a macrotidal environment. The method had to respond to resolution and time constraints for a realistic representation of the topo-morphological features from submeter dimensions and survey completion in two hours around low tide to fully cover the intertidal zone. Different tests were performed at two coastal field sites with varied dimensions and morphologies to assess the photogrammetric performance and eventual means for optimization. Our results show that, with precise image positioning, the addition of a single ground control point (GCP) enabled a global precision (RMSE) equivalent to that of traditional GCP-based photogrammetry using numerous and well-distributed GCPs. The optimal model quality that minimized vertical bias and random errors was achieved from 5 GCPs, with a two-fold reduction in RMSE. The image resolution for tie point detection was found to be an important control on the measurement quality, with the best results obtained using images at their original scale. Using these findings enabled designing an efficient and effective workflow for monitoring coastal topographic complexity at a large scale.

The combination of structure‐from‐motion with multi‐view stereo (SfM‐MVS) photogrammetry has become an increasingly popular method for the monitoring and three‐dimensional (3D) reconstruction of coastal environments. Climate change is driving the potential for increased coastal landward retreat meaning geomorphological monitoring using methods such as SfM‐MVS has become essential for detecting and tracking impacts. SfM‐MVS has been well‐researched with a variety of platforms and spatial and temporal resolutions using mainly rectilinear digital cameras in coastal settings. However, there has been no assessment of the potential of fixed multi‐camera arrays to monitor landward retreat or on the significance of camera placement in relation to the scene. This study presents an innovative method of image acquisition using a purpose‐built camera grid and GoPro© action camera to evaluate the combined effects of camera height, obliqueness and overlap at a site of known landward retreat. This approach examines the effect of camera placement on scene reconstruction to aid the design of a multi‐camera array. SfM‐MVS dense point clouds display millimetre accuracy when compared to equivalent terrestrial laser scans and strong image network geometry with internal precision estimates of < 3 mm. Comparable point cloud reconstruction can be achieved with a small number of images stationed in appropriate positions. Initial results show as few as five images positioned at a cliff to camera ratio of 3:4.18 and camera obliqueness of 40° can provide reconstruction in the range of millimetres (mean error of 4.79 mm). These findings illustrate the importance of camera placement when using multiple cameras and aid the design of a low‐cost, fixed multi‐camera array for use at sites of small‐scale landward retreat. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd [ABSTRACT FROM AUTHOR]

The Upper Rhone Valley (Valais, Switzerland) has been heavily modified over the past 200 years by human activity and natural processes. A qualitative analysis of the morphological and land-use evolution of the Rhone River floodplain since the end of the eighteenth century was carried out using historical maps from 1780 to 1860 processed with Structure-from-Motion (SfM) and Geographical Information System (GIS) tools. This study aims to produce a long-term analysis of river management and land-use change in a stretch of the Upper Rhone Valley around the town of Sion based on a time series of maps, realised in the years 1780–1802, 1820–1845, 1847, 1850s, 1852–1857, 1859–1860. The historical maps were digitised, and for each of the corresponding periods, a map was produced within a GIS. The comparison of the maps was completed by using documentary sources or subsequent studies. With the intention to identify the fluvial landscape changes and past river management, six multitemporal maps were produced. Finally, this research aims to provide helpful diachronic information for planning a future sustainable landscape development in Valais. [ABSTRACT FROM AUTHOR]

Ecological processes occur over multiple spatial, temporal and thematic scales in three-dimensional (3D) ecosystems. Characterizing and monitoring change in 3D structure at multiple scales is challenging within the practical constraints of conventional ecological tools. Remote sensing from satellites and crewed aircraft has revolutionized broad-scale spatial ecology, but fine-scale patterns and processes operating at sub-metre resolution have remained understudied over continuous extents. We introduce two high-resolution remote sensing tools for rapid and accurate 3D mapping in ecology—terrestrial laser scanning and structure-from-motion photogrammetry. These technologies are likely to become standard sampling tools for mapping and monitoring 3D ecosystem structure across currently under-sampled scales. We present practical guidance in the use of the tools and address barriers to widespread adoption, including testing the accuracy of structure-from-motion models for ecologists. We aim to highlight a new era in spatial ecology that uses high-resolution remote sensing to interrogate 3D digital ecosystems. [ABSTRACT FROM AUTHOR]

Natural sediment regimes of fluvial systems are variable and important to the biological and physical structures of rivers, yet watershed degradation has led to increased fine sediments entering and aggrading in rivers. As a result, quantifying substrate composition is important for targeting and monitoring restoration. Conventional methods for assessing substrate composition (e.g., pebble counts) can be time‐consuming and biased. We examined the use of the photogrammetric technique, structure‐from‐motion (SfM), as an alternative method by measuring streambed roughness. We expanded its application to submerged substrates in an artificial streambed to assess if roughness could predict pebble count substrate size percentiles across a range of manipulated levels of fine sediment aggradation. We then assessed the use of SfM in a free‐flowing river streambed. Results from the artificial streambed with coarse substrates (≤31% added fine sediment) revealed that repeated SfM models of the same streambed had a high degree of similarity (mean difference = 1 mm) and a strong relationship between SfM‐derived roughness and pebble counts (r2 >.95). This relationship was weaker (r2 <.66) and violated regression variance assumptions when substrates had up to 47% (55.7 kg) fines added, possibly due to SfM characterizing details not captured by pebble counts. In the natural streambed, there was a strong relationship between percentiles from the SfM model roughness and pebble count diameter (r2 =.96). SfM appears to be an efficient and appropriate alternative to direct substrate measurements across a broad range of streambed substrate compositions and thus a useful tool to model streambed morphology. [ABSTRACT FROM AUTHOR]

Abstract

Unmanned aerial vehicle (UAV) photogrammetry has become an important tool for generating multi-temporal, high-resolution ortho-images and digital elevation models (DEMs) to study glaciers and their dynamics. In polar regions, the roughness of the terrain, strong katabatic winds, unreliability of compass readings, and inaccessibility due to lack of infrastructure pose unique challenges for UAV surveying. To overcome these issues, we developed an open-source, low-cost, high-endurance, fixed-wing UAV equipped with GPS post-processed kinematic for the monitoring of ice dynamics and calving activity at several remote tidewater glaciers located in Greenland. Our custom-built UAV is capable of flying for up to 3 h or 180 km and is able to produce high spatial resolution (0.25–0.5 m per pixel), accurately geo-referenced (1–2 pixels) ortho-images and DEMs. We used our UAV to perform repeat surveys of six calving glacier termini in north-west in July 2017 and of Eqip Sermia glacier, west Greenland, in July 2018. The endurance of our UAV enabled us to map the termini of up to four tidewater glaciers in one flight and to infer the displacement and calving activity of Eqip Sermia at short (105 min) timescale. Our study sheds light on the potential of long-range UAVs for continuously monitoring marine-terminating glaciers, enabling short-term processes, such as the tidal effects on the ice dynamics, short-lived speed-up events, and the ice fracturing responsible for calving to be investigated at unprecedented resolution.

Flow resistance in mountain streams is important for assessing flooding hazard and quantifying sediment transport and bedrock incision in upland landscapes. In such settings, flow resistance is sensitive to grain‐scale roughness, which has traditionally been characterized by particle size distributions derived from laborious point counts of streambed sediment. Developing a general framework for rapid quantification of resistance in mountain streams is still a challenge. Here we present a semi‐automated workflow that combines millimeter‐ to centimeter‐scale structure‐from‐motion (SfM) photogrammetry surveys of bed topography and computational fluid dynamics (CFD) simulations to better evaluate surface roughness and rapidly quantify flow resistance in mountain streams. The workflow was applied to three field sites of gravel, cobble, and boulder‐bedded channels with a wide range of grain size, sorting, and shape. Large‐eddy simulations with body‐fitted meshes generated from SfM photogrammetry‐derived surfaces were performed to quantify flow resistance. The analysis of bed microtopography using a second‐order structure function identified three scaling regimes that corresponded to important roughness length scales and surface complexity contributing to flow resistance. The standard deviation σz of detrended streambed elevation normalized by water depth, as a proxy for the vertical roughness length scale, emerges as the primary control on flow resistance and is furthermore tied to the characteristic length scale of rough surface‐generated vortices. Horizontal length scales and surface complexity are secondary controls on flow resistance. A new resistance predictor linking water depth and vertical roughness scale, i.e.  H/σz, is proposed based on the comparison between σz and the characteristic length scale of vortex shedding. In addition, representing streambeds using digital elevation models (DEM) is appropriate for well‐sorted streambeds, but not for poorly sorted ones under shallow and medium flow depth conditions due to the missing local overhanging features captured by fully 3D meshes which modulate local pressure gradient and thus bulk flow separation and pressure distribution. An appraisal of the mesh resolution effect on flow resistance shows that the SfM photogrammetry data resolution and the optimal CFD mesh size should be about 1/7 to 1/14 of the standard deviation of bed elevation. © 2019 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

As a topographic modelling technique, structure‐from‐motion (SfM) photogrammetry combines the utility of digital photogrammetry with a flexibility and ease of use derived from multi‐view computer vision methods. In conjunction with the rapidly increasing availability of imagery, particularly from unmanned aerial vehicles, SfM photogrammetry represents a powerful tool for geomorphological research. However, to fully realize this potential, its application must be carefully underpinned by photogrammetric considerations, surveys should be reported in sufficient detail to be repeatable (if practical) and results appropriately assessed to understand fully the potential errors involved. To deliver these goals, robust survey and reporting must be supported through (i) using appropriate survey design, (ii) applying suitable statistics to identify systematic error (bias) and to estimate precision within results, and (iii) propagating uncertainty estimates into the final data products. © 2019 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Globally, many ecosystems are being challenged and transformed by anthropogenic climate change. Future ecosystem configurations will be heavily influenced by the critical ecological functions that affect resilience. Robust measures of these functions will thus be essential for understanding and responding to ecological change.Coral reefs are experiencing unprecedented ecological change due to global mass coral bleaching. After bleaching events and other disturbances, herbivorous fishes provide functions that are critical for reef resilience by controlling harmful proliferation of algae. Identifying functional diversity amongst herbivorous fishes has been a mainstay of reef fish research, but it has remained unclear how, and to what extent, functional diversity translates to functional impacts on reefs.Rather than assessing the functional potential of the herbivorous fish community, we explicitly considered the delivery of herbivory to the reef by quantifying, in unprecedented detail, the spatial extent and overlap of feeding areas across different functional groups. Core feeding areas were highly concentrated and consistently covered just 14% of available reef space. Overlap across functional groups was limited, showing high spatial complementarity as functional groups tended to feed next to one another. Thus, the delivery of critical ecosystem processes was patchy, effectively reducing functional redundancy, even in the presence of a diverse fish assemblage.Our findings caution against assumptions of spatial homogeneity in the delivery of critical ecosystem functions. The functional impact of local herbivorous fish assemblages in current approaches may be overestimated, potentially leading to skewed assessments of reef resilience. Our results highlight the need to incorporate collective animal behaviour and spatio‐temporal scales into future assessments of ecosystem functions and ultimately ecological resilience. A plain language summary is available for this article. [ABSTRACT FROM AUTHOR]

Along the rugged coast of Big Sur, California, the Mud Creek landslide failed catastrophically on May 20, 2017, and destroyed over 400 m of scenic California State Highway 1. We collected structure-from-motion (SfM) photogrammetry data using airborne platforms that, when combined with existing airborne lidar data, revealed that the area exhibited significant topographic change and displacement before, during, and after the catastrophic failure. Before the catastrophic failure, we document two areas of elevated change in the zone of depletion, which aligned with the double-peaked head scarp produced by the catastrophic failure. The catastrophic failure extended from 337-m elevation to at least 8 m below sea level, was 490 m wide, displaced ~ 3 million m3 of earth and rock, and deposited landslide debris at least 175 m seaward of the original shoreline. The failure was not a complete slope-clearing event, however, and several upslope and lateral regions that did not slip into the ocean exhibited significant displacement and topographic change during the days and months after the catastrophic failure. Additionally, we use the post-slide data to quantify several other processes, including the time-varying rates of talus accumulation and coastal erosion of the landslide toe. We conclude that repeat SfM surveys from aerial imagery can provide valuable information about landslide evolution and the potential for deep-seated landslide hazards—especially in the lead up to catastrophic failure—if photos are collected and processed regularly. [ABSTRACT FROM AUTHOR]

The Jurassic Coast World Heritage Site is a landscape defined by change and process. As such, the approach to its heritage must be similarly flexible and active. A balance must be found between celebrating these processes of change, whilst also conserving those invaluable discoveries and features that so define this coast, as well as encouraging ongoing research and public engagement. This delicate task can be aided firstly by thinking about this geologically defined World Heritage Site as a landscape. In this way it is possible to develop rich and nuanced narratives between the human and geological. Secondly, by embracing new technologies and methodologies to record, archive and communicate features and finds, as well as the process of change itself. Here, we explore these ideas through two unique sites of geological and palaeontological interest discovered in the process of quarrying. To balance keeping the sites open to the public with the risk of natural and human damage to the sites, Structure-from-Motion photogrammetry was used to create accurate, high-resolution, georeferenced 3D models. The process and potentials of the technique are discussed, alongside a discussion of the broader ideas of heritage and approaches already at play on this coastline. [ABSTRACT FROM AUTHOR]

Topographic surveys inevitably contain error, introducing uncertainty into estimates of volumetric or mean change based on the differencing of repeated surveys. In the geomorphic community, uncertainty has often been framed as a problem of separating out real change from apparent change due purely to error, and addressed by removing measured change considered indistinguishable from random noise from analyses (thresholding). Thresholding is important when quantifying gross changes (i.e. total erosion or total deposition), which are systematically biased by random errors in stable parts of a landscape. However, net change estimates are not substantially influenced by those same random errors, and the use of thresholds results in inherently biased, and potentially misleading, estimates of net change and uncertainty. More generally, thresholding is unrelated to the important process of propagating uncertainty in order to place uncertainty bounds around final estimates. Error propagation methods for uncorrelated, correlated, and systematic errors are presented. Those equations demonstrate that uncertainties in modern net change analyses, as well as in gross change analyses using reasonable thresholds, are likely to be dominated by low‐magnitude but highly correlated or systematic errors, even after careful attempts to reduce those errors. In contrast, random errors with little to no correlation largely cancel to negligible levels when averaged or summed. Propagated uncertainty is then typically insensitive to the precision of individual measurements, and is instead defined by the relative mean error (accuracy) over the area of interest. Given that real‐world mean elevation changes in many landscape settings are often similar in magnitude to potential mean errors in repeat topographic analyses, reducing highly correlated or systematic errors will be central to obtaining accurate change estimates, while placing uncertainty bounds around those results provides essential context for their interpretation. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. The analysis of landscape change based on repeat topographic surveys is becoming an increasingly practical and powerful tool across many earth surface disciplines. This paper re‐iterates the importance of accounting for survey error through error propagation, including subtle systematic errors, and presents statistical methods for doing so. The common practice of removing change measurements below some limit of detection ("thresholding") is shown to provide biased and potentially misleading results when used to assess net volumetric or mean change. [ABSTRACT FROM AUTHOR]

Grasslands deliver a range of ecosystem services, including the provision of food and biodiversity, and regulation of soil carbon storage and hydrology. Monitoring schemes are needed to quantify spatial changes in these multiple functions alongside ecosystem degradation. Sward height is widely recognised as a key spatial variable in the provision of these services. Current manual monitoring approaches are labour intensive, and often fail to capture spatial patterns of important features, including sward height.Proximal sensing from small aerial drones carrying lightweight cameras can be transformed into surface height models using image‐based structure‐from‐motion and Multi‐View Stereo‐based approaches; this presents a new opportunity for monitoring the spatial structure of grassland sward height. We combined aerial photographs with field survey data and an open‐source image‐based modelling‐processing workflow to generate sward height measurements for a field comprising mainly Lolium perenne (perennial ryegrass) and Trifolium pratense (red clover). We compared the derived measurements with in situ data captured on the same day using traditional agronomic sward height techniques to determine the quality of the drone‐derived surface model product for sward characterisation.The SfM and Multi‐View Stereo‐based surface model had a mean absolute sward height measurement error of between 3.7 and 4.2 cm. To produce field observations with equivalent quality would require up to 550 sward height measurements for the study site (area: 8,059 m2), which is not feasible over larger extents required for conservation of key species or agronomic purposes.Synthesis and applications. We demonstrate how the collection of precise and detailed information on the spatial structure of grasslands can be made over management‐relevant extents. Aerial digital photographs can be transformed into surface models using an image‐based modelling approach: structure‐from‐motion and Multi‐View Stereo techniques. Image‐based measurements of sward heights were compared with manual sward height data captured on the same day. This novel source of vegetation spatial information could improve sward management for conservation and agronomy applications. The approach supports frequent surveys, at user‐controlled revisit times, and delivers data for spatial monitoring of key grassland functions and services. We demonstrate how the collection of precise and detailed information on the spatial structure of grasslands can be made over management‐relevant extents. Aerial digital photographs can be transformed into surface models using an image‐based modelling approach: structure‐from‐motion and Multi‐View Stereo techniques. Image‐based measurements of sward heights were compared with manual sward height data captured on the same day. This novel source of vegetation spatial information could improve sward management for conservation and agronomy applications. The approach supports frequent surveys, at user‐controlled revisit times, and delivers data for spatial monitoring of key grassland functions and services. [ABSTRACT FROM AUTHOR]

Abstract The subglacial hydrology of tidewater glaciers is a key but poorly understood component of the complex ice-ocean system, which affects sea level rise. As it is extremely difficult to access the interior of a glacier, our knowledge relies mostly on the observation of input variables such as air temperature, and output variables such as the ice flow velocities reflecting the englacial water pressure, and the dynamics of plumes reflecting the discharge of meltwater into the ocean. In this study we use a cost-effective Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) to monitor the daily movements of Bowdoin Glacier, north-west Greenland, and the dynamics of its main plume. Using Structure-from-Motion photogrammetry and feature-tracking techniques, we obtained 22 high-resolution ortho-images and 19 velocity fields at the calving front for 12 days in July 2016. Our results show a two-day-long speed-up event (up to 170%) – caused by an increase in buoyant subglacial forces – with a strong spatial variability revealing that enhanced acceleration is an indication of shallow bedrock. Further, we used the Particle Image Velocimetry (PIV) method to analyze water flow from successive UAV images taken while flying over the main plume of the glacier. We found that PIV successfully captures the area of radially diverging flow of the plume, and provides information on spatial and time variability as no other remote sensing technique can. Most interestingly, the active part of the plume features pulsating water jets at the time scale of seconds, and is 1 to 5 times smaller than its visual footprint defined by the iceberg-free area. Combined with an ice flow model or a non-steady plume model, our approach has the potential to generate a novel set of input data to gather information about the depth of the bedrock, the discharge of meltwater, or the subglacial melting rate of tidewater glaciers. Highlights • First use of a VTOL UAV for glacier monitoring • First use of Particle Image Velocimetry (PIV) to infer meltwater plume flow • A major short-lived ice speed-up event of a calving glacier is captured. • PIV results evidence of the unsteady nature of the plume dynamics. • Ice and plume flows give insights into subglacial hydrological system. [ABSTRACT FROM AUTHOR]

The alluvial channel of the Langgriesgraben (Austria) is a highly active geomorphic riverine subcatchment of the Johnsbach River with intermittent discharge and braided river structures. The high sediment yield entails both issues and opportunities. For decades, the riverbed was exploited as a gravel pit. Today, as part of the Gesäuse National Park and after renaturation, the sediment yield endangers a locally important bridge located at the outlet of the subcatchment. High-resolution geospatial investigations are vital for the quantification of sediment redistribution, which is relevant in terms of river management. Based on unmanned aerial system (UAS) surveys in 2015 (July, September, and October) and 2019 (August and October), high-resolution digital elevation models (DEMs) were generated, which enable us to quantify intra- and multiannual sediment changes. As surface runoff at the subcatchment occurs on only a few days per year with flash floods and debris flows that are not predictable and thus hardly observable, the subsurface water conditions were assessed based on electrical resistivity tomography (ERT) measurements, which were conducted in 2019 (November) and 2020 (May, June). Results of the UAS-based surveys showed that, considering the data quality, intra-annual sediment changes affected only small subareas, whereas multiannual changes occurred in the entire study area and amount to net sediment deposition of ≈0.3–0.4 m3m−2, depending on the channel section. In addition, the elevation differences for both intra-annual surveys revealed linear patterns that can be interpreted as braided river channels. As in both survey periods the same areas were affected by changes, it can be concluded that the channel mainly affected by reshaping persisted within the 4-year observation period. The subsurface investigations showed that although both near-surface and groundwater conditions changed, near-surface sediments are mostly dry with a thickness of several meters during the observations.

River bank erosion is controlled by a complex combination of factors and processes that play a main role in fluvial dynamics. However, the role played by lateral erosion in small low energy rivers functioning still needs to be better understood. This study deals with the characterization and the quantification of the bank erosion of a small low energy river of the Seine Basin (France) in periurban catchment where urbanization had led to an incision and widening of the bed in the past decades, using adapted monitoring surveys: erosion pins and Structure-from-Motion Photogrammetry. The paper provides an opportunity to compare reach-scale flux estimates using both techniques. Spatial and temporal variations in river bank rates were quantified over 16 months and the causes and controls of riverbank erosion were identified. The estimated morphological activity rate ranges from 117 cm/yr to 1 cm/yr, illustrating the very heterogeneous spatio-temporal pattern of bank erosion observed on the Merantaise River. Whereas a number of studies consider subaerial processes as the dominant processes, fluvial erosion was found to be the most significant causal process, and in particular the mean discharge of floods. However, the high local variability of the bank erosion of the studied river appears to be controlled by very local factors such as the bank angle, the presence of a berm at the bank-toe (providing protection against fluvial erosion), lateral supply (outlet of rainwater pipes) and deflected flow in the direction of the bank. [ABSTRACT FROM AUTHOR]

Much of the geomorphic work of rivers occurs underwater. As a result, high resolutionquantification of geomorphic change in these submerged areas is important. Currently, to quantify thischange, multiple methods are required to get high resolution data for both the exposed and submergedareas. Remote sensing methods are often limited to the exposed areas due to the challenges imposedby the water, and those remote sensing methods for below the water surface require the collection ofextensive calibration data in-channel, which is time-consuming, labour-intensive, and sometimesprohibitive in dicult-to-access areas. Within this paper, we pioneer a novel approach for quantifyingabove- and below-water geomorphic change using Structure-from-Motion photogrammetry andinvestigate the implications of water surface elevations, refraction correction measures, and thespatial variability of topographic errors. We use two epochs of imagery from a site on the River Teme,Herefordshire, UK, collected using a remotely piloted aircraft system (RPAS) and processed usingStructure-from-Motion (SfM) photogrammetry. For the first time, we show that: (1) Quantification ofsubmerged geomorphic change to levels of accuracy commensurate with exposed areas is possiblewithout the need for calibration data or a dierent method from exposed areas; (2) there is minimaldierence in results produced by dierent refraction correction procedures using predominantlynadir imagery (small angle vs. multi-view), allowing users a choice of software packages/processingcomplexity; (3) improvements to our estimations of water surface elevations are critical for accuratetopographic estimation in submerged areas and can reduce mean elevation error by up to 73%;and (4) we can use machine learning, in the form of multiple linear regressions, and a Gaussian NaïveBayes classifier, based on the relationship between error and 11 independent variables, to generate ahigh resolution, spatially continuous model of geomorphic change in submerged areas, constrained byspatially variable error estimates. Our multiple regression model is capable of explaining up to 54%of magnitude and direction of topographic error, with accuracies of less than 0.04 m. With on-goingtesting and improvements, this machine learning approach has potential for routine application inspatially variable error estimation within the RPAS−SfM workflow.

Long-term ecological monitoring of reef fish populations often requires the simultaneous collection of data on benthic habitats in order to account for the effects of these variables on fish assemblage structure. Here, we described an approach to benthic surveys that uses photogrammetric techniques to facilitate the extraction of quantitative metrics for characterization of benthic habitats from the resulting three-dimensional (3D) reconstruction of coral reefs. Out of 92 sites surveyed in the Northwestern Hawaiian Islands, photographs from 85 sites achieved complete alignment and successfully produced 3D reconstructions and digital elevation models (DEMs). Habitat metrics extracted from the DEMs were generally correlated with one another, with the exception of curvature measures, indicating that complexity and curvature measures should be treated separately when quantifying the habitat structure. Fractal dimension D64, calculated by changing resolutions of the DEMs from 1 cm to 64 cm, had the best correlations with other habitat metrics. Fractal dimension was also less affected by changes in orientations of the models compared to surface complexity or slope. These results showed that fractal dimension can be used as a single measure of complexity for the characterization of coral reef habitats. Further investigations into metrics for 3D characterization of habitats should consider relevant spatial scales and focus on obtaining variables that can complement fractal dimension in the characterization of reef habitats.

Complex landscapes with high topographic relief and intricate geometry present challenges for complete and accurate mapping of both lateral (x, y) and vertical (z) detail without deformation. Although small uninhabited/unmanned aerial vehicles (UAVs) paired with structure-from-motion (SfM) image processing has recently emerged as a popular solution for a range of mapping applications, common image acquisition and processing strategies can result in surface deformation along steep slopes within complex terrain. Incorporation of oblique (off-nadir) images into the UAV⁻SfM workflow has been shown to reduce systematic errors within resulting models, but there has been no consensus or documentation substantiating use of particular imaging angles. To address these limitations, we examined UAV⁻SfM models produced from image sets collected with various imaging angles (0⁻35°) within a high-relief ‘badland’ landscape and compared resulting surfaces with a reference dataset from a terrestrial laser scanner (TLS). More than 150 UAV⁻SfM scenarios were quantitatively evaluated to assess the effects of camera tilt angle, overlap, and imaging configuration on the precision and accuracy of the reconstructed terrain. Results indicate that imaging angle has a profound impact on accuracy and precision for data acquisition with a single camera angle in topographically complex scenes. Results also confirm previous findings that supplementing nadir image blocks with oblique images in the UAV⁻SfM workflow consistently improves spatial accuracy and precision and reduces data gaps and systematic errors in the final point cloud. Subtle differences among various oblique camera angles and imaging patterns suggest that higher overlap and higher oblique camera angles (20⁻35°) increased precision and accuracy by nearly 50% relative to nadir-only image blocks. We conclude by presenting four recommendations for incorporating oblique images and adapting flight parameters to enhance 3D mapping applications with UAV⁻SfM in high-relief terrain.

Owing to the combination of technological progress in Unmanned Aerial Vehicles (UAVs) and recent advances in photogrammetry processing with the development of the Structure-from-Motion (SfM) approach, UAV photogrammetry enables the rapid acquisition of high resolution topographic data at low cost. This method is particularly widely used for geomorphological surveys of linear coastal landforms. However, linear surveys are generally pointed out as problematic cases because of geometric distortions creating a “bowl effect” in the computed Digital Elevation Model (DEM). Secondly, the survey of linear coastal landforms is associated with peculiar constraints for Ground Control Points (GCPs) measurements and for the spatial distribution of the tie points. This article aims to assess the extent of the bowl effects affecting the DEM generated above a linear beach with a restricted distribution of GCPs, using different acquisition scenarios and different processing procedures, both with PhotoScan® software tool and MicMac® software tool. It appears that, with a poor distribution of the GCPs, a flight scenario that favors viewing angles diversity can limit DEM’s bowl effect. Moreover, the quality of the resulting DEM also depends on the good match between the flight plan strategy and the software tool via the choice of a relevant camera distortion model.

Lodging has been recognized as one of the major destructive factors for crop quality and yield, resulting in an increasing need to develop cost-efficient and accurate methods for detecting crop lodging in a routine manner. Using structure-from-motion (SfM) and novel geospatial computing algorithms, this study investigated the potential of high resolution imaging with unmanned aircraft system (UAS) technology for detecting and assessing lodging severity over an experimental maize field at the Texas A&M AgriLife Research and Extension Center in Corpus Christi, Texas, during the 2016 growing season. The method was proposed to not only detect the occurrence of lodging at the field scale, but also to quantitatively estimate the number of lodged plants and the lodging rate within individual rows. Nadir-view images of the field trial were taken by multiple UAS platforms equipped with consumer grade red, green, and blue (RGB), and near-infrared (NIR) cameras on a routine basis, enabling a timely observation of the plant growth until harvesting. Models of canopy structure were reconstructed via an SfM photogrammetric workflow. The UAS-estimated maize height was characterized by polygons developed and expanded from individual row centerlines, and produced reliable accuracy when compared against field measures of height obtained from multiple dates. The proposed method then segmented the individual maize rows into multiple grid cells and determined the lodging severity based on the height percentiles against preset thresholds within individual grid cells. From the analysis derived from this method, the UAS-based lodging results were generally comparable in accuracy to those measured by a human data collector on the ground, measuring the number of lodging plants (R² = 0.48) and the lodging rate (R² = 0.50) on a per-row basis. The results also displayed a negative relationship of ground-measured yield with UAS-estimated and ground-measured lodging rate. [ABSTRACT FROM AUTHOR]

Accurate and reliable methods for quantifying grain size are important for river science, management and in various other sedimentological settings. Remote sensing offers methods of quantifying grain size, typically providing; (a) coarse outputs ( c. 1 m) at the catchment scale where individual grains are at subpixel level, or; (b) fine resolution outputs ( c. 1 mm) at the patch scale. Recently, approaches using unmanned aerial vehicles (UAVs) have started to fill the gap between these scales, providing hyperspatial resolution data (< 10 cm) over reaches a few hundred metres in length, where individual grains are at suprapixel level. This 'mesoscale' is critical to habitat assessments. Most existing UAV-based approaches use two-dimensional (2D) textural variables to predict grain size. Validation of results is largely absent however, despite significant differences in platform stability and image quality obtained by manned aircraft versus UAVs. Here, we provide the first quantitative assessment of the accuracy and precision of grain size estimates produced from a 2D image texture approach. Furthermore, we present a new method which predicts subaerial gravel size using three-dimensional (3D) topographic data derived from UAV imagery. Data is collected from a small gravel-bed river in Cumbria, UK. Results indicate that our new topographic method gives more accurate measures of grain size (mean residual error -0.0001 m). Better results for the image texture method may be precluded by our choice of texture measure, the scale of analysis or the effects of image blur resulting from an inadequate camera gimbal. We suggest that at our scale of assessment, grain size is more strongly related to 3D variation in elevation than to the 2D textural patterns expressed within the imagery. With on-going improvements, our novel method has potential as the first grain size quantification approach where a trade-off between coverage and resolution is not necessary or inherent. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The availability of high-resolution, multi-temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three-dimensional topographic point measurements acquired from structure-from-motion (SfM) photogrammetry have been shown to be highly accurate and cost-effective compared to laser-based alternatives in some environments. Use of consumer-grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM- and LiDAR-derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. Greater information capacity of source imagery was found to increase pixel matching quality, which produced eight times greater point density and six times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6-37 cm) was sufficient to detect moderate geomorphic change (order 100 000 m3) on an unvegetated fluvial surface; change detection determined from repeat LiDAR and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post-processing techniques increased point density by 5-25% and decreased processing time by 10-30%. Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error. Published 2016. This article is a U.S. Government work and is in the public domain in the USA [ABSTRACT FROM AUTHOR]

Background: Large landslides triggered by rainfall and floods were registered on both sides of the Rječina River Valley, near City of Rijeka, in Croatia, where numerous instability phenomena in the past 250 years have been recorded, and yet only some locations have been investigated. The paper presents investigation of the dormant landslide located on the south-western slope, recorded in numerous historical descriptions from 1870. Due to intense and long-term rainfall, the landslide was reactivated in 1885, destroying and damaging houses in the eastern part of the Grohovo Village. Results: 2D stability back analyses have been performed based on landslide features, in order to approximate the position of the sliding surface and landslide dimensions. Because of the very steep landslide topography and the slope covered by unstable debris material, a Remotely Piloted Aircraft System (RPAS) was used to provide the data about the present slope topography. The landslide 3D point cloud was derived using Structure-from-Motion (SfM) photogrammetry. In order to verify the cloud of georeferenced sliding points obtained from images, it was compared with the existing models acquired from terrestrial photogrammetry and laser scanning, showing good accordance and small changes through the years. Based on the classification and Uniaxial Compressive Strength test results, rock mass strength was defined using generalised Hoek-Brown's failure criteria. Conclusions: Stability analysis results of the present slope conditions show that the slope is marginally stable for dry conditions, and that the critical seismic coefficient of about 0.14 would generate inertial forces corresponding to the factor of safety equal to 1. Analyses were performed with the purpose to predict the possible reactivation of a dormant landslide, and the presented results could be used in the establishment of an early warning system. [ABSTRACT FROM AUTHOR]

Current understanding of glacier mass balance changes under changing climate is limited by scarcity of in situ measurements in both time and space, as well as resolution of remote sensing products. Recent innovations in unmanned aerial vehicles (UAVs), as well as structure-from-motion photogrammetry (SfM), have led to increased use of digital imagery to derive topographic data in great detail in many fields, including glaciology. This study tested the capability of UAV surveys to detect surface changes over glacier ice during a three-day period in July 2016. Three UAV imaging missions were conducted during this time over 0.185 km 2 of the ablation area of Fountain Glacier, NU. These were processed with the SfM algorithms in Agisoft Photoscan Professional and overall accuracies of the resulting point clouds ranged from 0.030 to 0.043 m. The high accuracy of point clouds achieved here is primarily a result of a small ground sampling distance (0.018 m), and is also influenced by GPS precision. Glacier surface change was measured through differencing of point clouds and change was compared to ablation stake measurements. Surface change measured with the UAV-SfM method agreed with the coincident ablation stake measurements in most instances, with RMSE values of 0.033, 0.028, and 0.042 m for one-, two-, and three-day periods, respectively. Total specific melt over the study area measured with the UAV was 0.170 m water equivalent (w.e.), while interpolation of ablation measurements resulted in 0.144 m w.e. Using UAVs to measure small changes in glacier surfaces will allow for new investigations of distribution of mass balance measurements.