Multi-view Stereo Photogrammetry Research Articles

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

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

Structure-from-motion, multi-view stereo photogrammetry applied to line-scan sediment core images

Images of sediment cores are often acquired to preserve primary color information, before such profiles are altered by subsequent sampling and destructive analyses. In many cases, however, no post-processing of these images is undertaken to extract information, despite the fact that image processing can be used to describe and measure structures within the sample. Improvements of RGB (Red/Green/Blue) cameras and image processing algorithms now enable acquisition of high-resolution, metrically calibrated pictures called ortho-images, which have great potential. The way to obtain such ortho-images is by processing several raw images. We propose a semi-automated method that uses metrically calibrated targets to create the ortho-image, using Agisoft Photoscan software and a Python script. The method was tested on sediment cores up to 1.5 m long. It was compared to an approach without markers, one that uses only image matching. The proposed method showed better resolution and less distortion (GSD: 59 µm, RMSE: 7–18 µm). Images acquired without calibrated targets can still be used, by manually positioning points that can then be metrically calibrated. This approach is very useful for smartphone images taken in the field. There are many potential applications for such images of sediment cores, for instance as metric stratigraphic logs to facilitate description of the profile by unit, to study and measure structures (e.g. laminae, instantaneous deposits), or use of image registration or data fusion to create spatial landmarks for non-destructive sensors or destructive laboratory analyses. High-resolution metrically calibrated RGB images of sediment cores are simple to acquire and can play an important role in paleoclimate and paleoenvironmental studies.

Observation of Diurnal Ground Surface Changes Due to Freeze-Thaw Action by Real-Time Kinematic Unmanned Aerial Vehicle

Ground surface changes caused by freeze-thaw action affect agriculture and forestry, as well as artificial structures such as roads. In this study, an area is examined in which reforestation is urgently needed but the growth of naturally restored seedlings and planted trees is impaired by freeze-thaw action. Thus, a method of measuring freeze-thaw induced ground surface changes and mitigating their negative impacts is needed. Real-time kinematic unmanned aerial vehicle and structure-from-motion multiview stereophotogrammetry are used on slope-failure sites in forest areas to observe the ground surface changes caused by freeze-thaw action over a wide area, in a nondestructive manner. The slope characteristics influencing the ground-surface changes were examined, and it was confirmed that it is possible to observe minute topographical changes of less than ±5 cm resulting from freeze-thaw action. Statistical models show that the amount of freeze-thaw action is mostly linked to the cumulative solar radiation, daily ground-surface temperature range, and topographic-wetness index, which influence the microscale dynamics of the ground surface. The proposed method will be useful for future quantitative assessments of ground-surface conditions. Further, efficient reforestation could be implemented by considering the effects of the factors identified on the amount of freeze-thaw action.

Accuracy of Unmanned Aerial Systems Photogrammetry and Structure from Motion in Surveying and Mapping: A Review

Highly detailed topographic surveying at minimal cost and effort has always been one of the developing areas of scientific interest. Image-based remote sensing solutions using unmanned aerial systems (UAS) and structure from motion (SfM) with multi-view stereo (MVS) photogrammetry are the latest automation and advancement in surveying engineering that provides high-resolution topographic data. Although recent developments have led to the extensive use of UAS–SfM in mapping applications, the only concern that remains is the UAS-based survey accuracy; is this method accurate enough to be used in surveying and mapping applications as an alternative to conventional methods? Evaluation of accuracy and validation of products before they can be applied to a real-world problem is a prerequisite for any emerging technology. Recently, there has been a proliferation of accuracy assessment and validation studies of UAS–SfM-based surveying. However, quantitative validation studies are slightly different, and the accuracy of each study is significantly different from another. The true limits of this technique can only be revealed by assembling a large dataset from previous individual studies. This study was motivated by the lack of such quantitative analysis. This study gives an overview of UAS and SfM, discusses the major factors that influence the accuracy, and presents a synthesis of the recent validation studies conducted quantitative assessments of UAS–SfM-derived digital elevation datasets, and thereby demonstrates the accuracy and limitation of UAS–SfM -based topographic surveying.

3D Reconstruction of Coastal Cliffs from Fixed-Wing and Multi-Rotor UAS: Impact of SfM-MVS Processing Parameters, Image Redundancy and Acquisition Geometry

Monitoring the dynamics of coastal cliffs is fundamental for the safety of communities, buildings, utilities, and infrastructures located near the coastline. Structure-from-Motion and Multi View Stereo (SfM-MVS) photogrammetry based on Unmanned Aerial Systems (UAS) is a flexible and cost-effective surveying technique for generating a dense 3D point cloud of the whole cliff face (from bottom to top), with high spatial and temporal resolution. In this paper, in order to generate a reproducible, reliable, precise, accurate, and dense point cloud of the cliff face, a comprehensive analysis of the SfM-MVS processing parameters, image redundancy and acquisition geometry was performed. Using two different UAS, a fixed-wing and a multi-rotor, two flight missions were executed with the aim of reconstructing the geometry of an almost vertical cliff located at the central Portuguese coast. The results indicated that optimizing the processing parameters of Agisoft Metashape can improve the 3D accuracy of the point cloud up to 2 cm. Regarding the image acquisition geometry, the high off-nadir (90°) dataset taken by the multi-rotor generated a denser and more accurate point cloud, with lesser data gaps, than that generated by the low off-nadir dataset (3°) taken by the fixed wing. Yet, it was found that reducing properly the high overlap of the image dataset acquired by the multi-rotor drone permits to get an optimal image dataset, allowing to speed up the processing time without compromising the accuracy and density of the generated point cloud. The analysis and results presented in this paper improve the knowledge required for the 3D reconstruction of coastal cliffs by UAS, providing new insights into the technical aspects needed for optimizing the monitoring surveys.

DIGITAL 3D MODELS OF MINERALS AND ROCKS IN A NUTSHELL: ENHANCING SCIENTIFIC, LEARNING, AND CULTURAL HERITAGE ENVIRONMENTS IN GEOSCIENCES BY USING CROSS-POLARIZED LIGHT PHOTOGRAMMETRY

Three-dimensional (3D) minerals and rocks in the form of interactive, engaging, and immersive experiences are of paramount importance to the geoscience community, researchers, students, and philomaths. Moreover, the SARS-CoV-2 (COVID-19) crisis affecting our society in the spring of 2020 highlighted the importance of 3D material in geoscience education — compared to 2D images, the three-dimensional models provide a better way to learn and to recognize different minerals and rocks, properties, textures, etc. This paper seeks to provide a comprehensive method to create an interactive scientific, learning, and cultural heritage environment in the field of Geosciences. In this paper, we overcome most of the Structure-from-Motion - Multi-View Stereo (SfM-MVS) photogrammetry limitations, where samples with a transparent, translucent, or glossy surface are a real challenge for the feature detection algorithms of the SfM workflow. Correct lighting setup, the usage of cross-polarized light photogrammetry workflow, anti-reflection coating spray and post-processing steps are the essential ingredients for an enhanced photogrammetric study. The main output of this research consists of a comprehensive virtual 3D collection of minerals and rocks which are available online via the Sketchfab repository of the Museum of Mineralogy and Petrography “Grigore Cobălcescu” (https://sketchfab.com/MineralogyPetrographyMuseum).

Combining UAV-Based SfM-MVS Photogrammetry with Conventional Monitoring to Set Environmental Flows: Modifying Dam Flushing Flows to Improve Alpine Stream Habitat

Setting environmental flows downstream of hydropower dams is widely recognized as important, particularly in Alpine regions. However, the required flows are strongly influenced by the effects of the physical environment of the downstream river. Here, we show how unmanned aerial vehicle (UAV)-based structure-from-motion multiview stereo (SfM-MVS) photogrammetry allows for incorporation of such effects through determination of spatially distributed patterns of key physical parameters (e.g., bed shear stress, bed grain size) and how they condition available stream habitat. This is illustrated for a dam-impacted Alpine stream, testing whether modification of the dam’s annual flushing flow could achieve the desired downstream environmental improvement. In detail, we found that (1) flood peaks in the pilot study were larger than needed, (2) only a single flood peak was necessary, (3) sediment coarsening was likely being impacted by supply from nonregulated tributaries, often overlooked, and (4) a lower-magnitude but longer-duration rinsing flow after flushing is valuable for the system. These findings were enabled by the spatially rich geospatial datasets produced by UAV-based SfM-MVS photogrammetry. Both modeling of river erosion and deposition and river habitat may be revolutionized by these developments in remote sensing. However, it is combination with more traditional and temporarily rich monitoring that allows their full potential to be realized.

Combined geometric-radiometric and neural network approach to shallow bathymetric mapping with UAS imagery

There is a pressing need for shallow bathymetry in regions around the world, including in fragile marine ecosystems, such as coral reefs. Unfortunately, mapping these shallow-water areas using in situ or boat-based methods is expensive, time consuming, and potentially dangerous, due to the need to put personnel and/or boats in high-energy nearshore areas, which may contain rocks, reefs, and other submerged hazards. For this reason, passive remote sensing methods of shallow bathymetric mapping have been rapidly growing in interest and usage. Two general categories of approaches using passive imaging can be distinguished as: (1) those based on geometry (stereo-photogrammetry); (2) those based on radiometry (attenuation of light in the water column). These two broad categories of approaches have been tested on imagery collected using aircraft and satellites in numerous previous studies. Recent work within the geometric category includes processing unmanned aircraft system (UAS) imagery using Structure from Motion and Multi-View Stereo (SfM-MVS) photogrammetry, while radiometric methods encompass the broad range of spectral bathymetry retrieval algorithms. Each broad approach category has advantages and disadvantages. Fortunately, the geometric and radiometric approaches are highly complementary. The geometric approaches tend to work best in areas of high bottom texture, which facilitates feature matching in the SfM-MVS software. Meanwhile, the radiometric approaches work best in relatively homogeneous bottom types. To leverage the strengths of each type of approach and overcome their respective weaknesses, this work develops and tests a combined geometric-radiometric bathymetric mapping approach designed for shallow-water mapping from UAS imagery. Four radiometric models of varying complexity are tested, ranging from a color-based lookup table approach to neural networks. Two UAS flights on Buck Island, off St Croix in the U.S. Virgin Islands (USVI), are used to assess the accuracy of the methodology when compared to aerial bathymetric lidar data. The results show that the combined geometric-radiometric approach provides an increase in spatial coverage of up to 61% and improvement (i.e. decrease) in 95th percentile error of up to 49% when compared to traditional refraction-corrected SfM-MVS bathymetry.

Spatial accuracy assessment of unmanned aerial vehicle-based structures from motion multi-view stereo photogrammetry for geomorphic observations in initiation zones of debris flows, Ohya landslide, Japan

Fluctuations in sediment storage arising from sediment discharge and recharge in headwater channels are an important factor influencing changes in landforms in mountainous areas, but the frequency of surveys is limited because of access difficulties and complex topography. Although unmanned aerial vehicle-based structure-from-motion photogrammetry (UAV-SfM) may be effective for topographic measurement, its utilization in headwater channels has not been fully examined. We assessed the accuracy and reproducibility of a digital elevation model acquired via UAV-SfM (DEMSfM) in a headwater channel within the Ohya landslide area, Japan, using a DEM acquired via terrestrial laser scanning (DEMTLS). The results indicate that differences in the measured elevation between DEMSfM and DEMTLS in the vicinity of the channel bed ranged from about 0.4 to −0.4 m, with a median of 0.06 m. Hence, the profiles acquired via DEMSfM coincide well with those acquired via DEMTLS, and the spatial distributions and histograms of the measured surface slope were nearly the same for UAV-SfM and TLS. However, part of the DEMSfM indicates low elevation compared with DEMTLS, probably because of topical distortion arising from technical problems in UAV-SfM. The positive and negative differences in volume between DEMSfM and DEMTLS were approximately 200 and −30 m3, respectively. To remedy this bias, an alignment of the UAV-SfM point cloud using the TLS point cloud in the hillslope sections was conducted, based on an iterative closest point (ICP) algorithm. Consequently, the median of the elevation differences decreased to −0.002 m, resulting in the positive and negative differences becoming approximately 100 m3. This demonstrates that ICP-based alignment can lead to a reduction of the deviation of differences in the estimated volume. In terms of eliminating biases due to topical distortion in elevation, this approach would be valid for the estimation of volumetric changes using UAV-SfM.

Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms

The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.

Image Data Acquisition for Estimating Individual Trees Metrics: Closer Is Better

Background and Objectives: The recent use of Structure-from-Motion with Multi-View Stereo photogrammetry (SfM-MVS) in forestry has underscored its robustness in tree mensuration. This study evaluated the differences in tree metrics resulting from various related SfM-MVS photogrammetric image acquisition scenarios. Materials and Methods: Scaled tri-dimensional models of 30 savanna trees belonging to five species were built from photographs acquired in a factorial design with shooting distance (d = 1, 2, 3, 4 and 5 m away from tree) and angular shift (α = 15°, 30°, 45° and 60°; nested in d). Tree stem circumference at 1.3 m and bole volume were estimated using models resulting from each of the 20 scenarios/tree. Mean absolute percent error (MAPE) was computed for both metrics in order to compare the performance of each scenario in relation to reference data collected using a measuring tape. Results: An assessment of the effect of species identity (s), shooting distance and angular shift showed that photographic point cloud density was dependent on α and s, and optimal for 15° and 30°. MAPEs calculated on stem circumferences and volumes significantly differed with d and α, respectively. There was a significant interaction between α and s for both circumference and volume MAPEs, which varied widely (1.6 ± 0.4%–20.8 ± 23.7% and 2.0 ± 0.6%–36.5 ± 48.7% respectively), and were consistently lower for smaller values of d and α. Conclusion: The accuracy of photogrammetric estimation of individual tree attributes depended on image-capture approach. Acquiring images 2 m away and with 30° intervals around trees produced reliable estimates of stem circumference and bole volume. Research Highlights: This study indicates that the accuracy of photogrammetric estimations of individual tree attributes is species-dependent. Camera positions in relation to the subject substantially influence the level of uncertainty in measurements.

Smartphone: An alternative to ground control points for orienting virtual outcrop models and assessing their quality

AbstractThe application of structure from motion–multiview stereo (SfM-MVS) photogrammetry to map metric- to hectometric-scale exposures facilitates the production of three-dimensional (3-D) surface reconstructions with centimeter resolution and range error. In order to be useful for geospatial data interrogation, models must be correctly located, scaled, and oriented, which typically requires the geolocation of manually positioned ground control points with survey-grade accuracy. The cost and operational complexity of portable tools capable of achieving such positional accuracy and precision is a major obstacle in the routine deployment of SfM-MVS photogrammetry in many fields, including geological fieldwork. Here, we propose a procedure to overcome this limitation and to produce satisfactorily oriented models, which involves the use of photo orientation information recorded by smartphones. Photos captured with smartphones are used to: (1) build test models for evaluating the accuracy of the method, and (2) build smartphone-derived models of outcrops, used to reference higher-resolution models reconstructed from image data collected using digital single-lens reflex (DSLR) and mirrorless cameras. Our results are encouraging and indicate that the proposed workflow can produce registrations with high relative accuracies using consumer-grade smartphones. We also find that comparison between measured and estimated photo orientation can be successfully used to detect errors and distortions within the 3-D models.

Evaluation of grapevine trunk size by use of a handheld camera and three-dimensional modelling

Background and aims: Measurement of grapevine size is necessary to assess carbon reserves at the level of individual vines and to estimate the carbon sequestration potential of vineyards. Methods of measurement rely mostly on traditional dendrological techniques that may be prone to error. In this study, we examined the use of structure-from-motion with multiview stereophotogrammetry (SfM-MVS) to obtain accurate measurements of vine trunk thickness and volume. SfM-MVS enables the creation of scaled, georeferenced three-dimensional models based on a set of overlapping photographs.Methods and results: The study was conducted using field-grown Vitis vinifera L. cv. Riesling vines aged 5, 22 and 46 years and pruned in a bilateral Guyot. Trunk diameter, cross-sectional area and circumference 10 cm above the grafting point were measured by traditional dendrometry, and the values obtained compared with corresponding estimates from reconstructed three-dimensional SfM-MVS models. SfM-MVS was also used to estimate total trunk volume. Correlation between measured values and modelled estimates was close to unity (0.976 ≤ R2 ≤ 0.988). The estimates for 5-year-old vines had the largest errors.Conclusions: Under adequate lighting conditions and with sufficient image resolution, SfM-MVS is able to produce accurate models of vine trunks.Significance of the study: This work serves as proof of concept for the use of SfM-MVS to measure the trunk size of field-grown grapevines of different ages. This technique, which is relatively new, is cost-effective and easy to implement. Further research is necessary to determine specific applications of SfM-MVS, in which it could supplement or replace traditional dendrological techniques.

Linking hydrological connectivity to gully erosion in savanna rangelands tributary to the Great Barrier Reef using structure‐from‐motion photogrammetry

AbstractGully erosion is a major land management challenge globally and a particularly important issue in dry tropical savanna rangelands tributary to the Great Barrier Reef, Australia. This study investigated linkages between hillslope hydrological connectivity pathways and gully geomorphic change in the Burdekin River Basin. High‐resolution (0.1 m) topographic and land cover data derived from low‐cost aerial (via unmanned aircraft system) structure‐from‐motion with multiview stereo photogrammetry (SfM) were used to map fine‐scale connectivity patterns and quantify headcut retreat at the hillslope scale (~150,000 m2). Very high resolution (0.01 m) topographic models derived from ground‐based (via handheld digital camera) SfM were used to quantify the morphology and geomorphic change of several gully arms (300–700 m2) between 2016 and 2018. Median linear, areal, and volumetric headcut (n = 21) retreat rates were 0.2 m, 0.8 m2, and 0.3 m3 yr−1, respectively. At all study sites, the points where modelled hydrological flow lines intersected gullies corresponded to observed geomorphic change, enabling spatially explicit identification of gully extension pathways as a result of overland flow. Application of an index of connectivity demarcated parts of the hillslope most connected to the gully network. Bare areas, roads, and cattle trails were identified as important runoff source areas and hydrological conduits driving gully extension. Ground‐based SfM accurately reconstructed complex morphologic features including undercuts, overhangs, rills, and flutes, providing insights into within‐channel erosion processes. This study contributes to an improved understanding and modelling of hydrogeomorphic drivers of gully erosion in degraded savanna rangelands, ultimately benefiting gully management.

Mountain glacier-to-rock glacier transition

Abstract In many of the world's high mountain systems, glacier recession in response to climate change is accompanied by a paraglacial response whereby glaciers are undergoing a transition to rock glaciers. We hypothesise that this transition has important implications for hydrological resources in high mountain systems and the surrounding lowlands given the insulating effects that debris cover can have on glacier ice. Despite this, however, little is known about how this transition occurs nor how quickly, which glaciers are liable to transition, the factors driving this process and the water supply implications that follow. This paper assesses the role of glacier and rock glacier textural properties from a deglaciating region of the Himalayas to begin to address some of these issues. We investigated six landsystems on the spectrum from glaciers-to-rock glaciers in the Khumbu Himal, Nepal, and sampled for clast shape and roundness during 2016 and 2017. Kite aerial photography was additionally used to capture aerial images of an ongoing glacier-to-rock glacier transitional landform (Chola Glacier) to elucidate the surface geomorphic features of a fully transitioned landform. This image data, processed using a structure-from-motion multi-view stereo photogrammetry approach, revealed the presence of a spatially coherent ridge-and-furrow surface morphology in the lower reaches of Chola Glacier, which is potentially indicative of an ongoing glacier-to-rock glacier transition. We show that glacier-derived and slope-derived clast roundness significantly statistically different (Kolmogorov–Smirnov two-sample test: Dmax = 0.62, two-tail p

High-accuracy UAV photogrammetry of ice sheet dynamics with no ground control

Abstract. Unmanned aerial vehicles (UAVs) and structure from motion with multi-view stereo (SfM–MVS) photogrammetry are increasingly common tools for geoscience applications, but final product accuracy can be significantly diminished in the absence of a dense and well-distributed network of ground control points (GCPs). This is problematic in inaccessible or hazardous field environments, including highly crevassed glaciers, where implementing suitable GCP networks would be logistically difficult if not impossible. To overcome this challenge, we present an alternative geolocation approach known as GNSS-supported aerial triangulation (GNSS-AT). Here, an on-board carrier-phase GNSS receiver is used to determine the location of photo acquisitions using kinematic differential carrier-phase positioning. The camera positions can be used as the geospatial input to the photogrammetry process. We describe the implementation of this method in a low-cost, custom-built UAV and apply the method in a glaciological setting at Store Glacier in western Greenland. We validate the technique at the calving front, achieving topographic uncertainties of ±0.12 m horizontally (∼1.1× the ground sampling distance) and ±0.14 m vertically (∼1.3× the ground sampling distance), when flying at an altitude of ∼ 450 m above ground level. This compares favourably with previous GCP-derived uncertainties in glacial environments and allows us to apply the SfM–MVS photogrammetry at an inland study site where ice flows at 2 m day−1 and stable ground control is not available. Here, we were able to produce, without the use of GCPs, the first UAV-derived velocity fields of an ice sheet interior. Given the growing use of UAVs and SfM–MVS in glaciology and the geosciences, GNSS-AT will be of interest to those wishing to use UAV photogrammetry to obtain high-precision measurements of topographic change in contexts where GCP collection is logistically constrained.

UAV-Based 3D Point Clouds of Freshwater Fish Habitats, Xingu River Basin, Brazil

Dense 3D point clouds were generated from Structure-from-Motion Multiview Stereo (SFM-MVS) photogrammetry for five representative freshwater fish habitats in the Xingu river basin, Brazil. The models were constructed from Unmanned Aerial Vehicle (UAV) photographs collected in 2016 and 2017. The Xingu River is one of the primary tributaries of the Amazon River. It is known for its exceptionally high aquatic biodiversity. The dense 3D point clouds were generated in the dry season when large areas of aquatic substrate are exposed due to the low water level. The point clouds were generated at ground sampling distances of 1.20–2.38 cm. These data are useful for studying the habitat characteristics and complexity of several fish species in a spatially explicit manner, such as calculation of metrics including rugosity and the Minkowski–Bouligand fractal dimension (3D complexity). From these dense 3D point clouds, substrate complexity can be determined more comprehensively than from conventional arbitrary cross sections.

Freshwater Fish Habitat Complexity Mapping Using Above and Underwater Structure-From-Motion Photogrammetry

Substrate complexity is strongly related to biodiversity in aquatic habitats. We illustrate a novel framework, based on Structure-from-Motion photogrammetry (SfM) and Multi-View Stereo (MVS) photogrammetry, to quantify habitat complexity in freshwater ecosystems from Unmanned Aerial Vehicle (UAV) and underwater photography. We analysed sites in the Xingu river basin, Brazil, to reconstruct the 3D structure of the substrate and identify and map habitat classes important for maintaining fish assemblage biodiversity. From the digital models we calculated habitat complexity metrics including rugosity, slope and 3D fractal dimension. The UAV based SfM-MVS products were generated at a ground sampling distance (GSD) of 1.20–2.38 cm while the underwater photography produced a GSD of 1 mm. Our results show how these products provide spatially explicit complexity metrics, which are more comprehensive than conventional arbitrary cross sections. Shallow neural network classification of SfM-MVS products of substrate exposed in the dry season resulted in high accuracies across classes. UAV and underwater SfM-MVS is robust for quantifying freshwater habitat classes and complexity and should be chosen whenever possible over conventional methods (e.g., chain-and-tape) because of the repeatability, scalability and multi-dimensional nature of the products. The SfM-MVS products can be used to identify high priority freshwater sectors for conservation, species occurrences and diversity studies to provide a broader indication for overall fish species diversity and provide repeatability for monitoring change over time.

Observing Clouds in 4D with Multiview Stereophotogrammetry

AbstractNewly installed stereo cameras ringing the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site in Oklahoma are providing a 4D gridded view of shallow clouds. Six digital cameras have been installed in pairs at a distance of 6 km from the site and with a spacing of 500 m between cameras in a pair. These pairs of cameras provide stereoscopic views of shallow clouds from all sides; when these data are combined, they allow for a complete stereo reconstruction. The result—the Clouds Optically Gridded by Stereo (COGS) product—is a 4D grid of cloudiness covering a 6 km × 6 km × 6 km cube at a spatial resolution of 50 m and a temporal resolution of 20 s. This provides a unique set of data on the sizes, lifetimes, and life cycles of shallow clouds. This type of information is critical for developing cloud macrophysical schemes for the next generation of weather and climate models.

Thermokarst Development Detected from High-Definition Topographic Data in Central Yakutia

Eastern Siberia is characterized by widespread permafrost thawing and subsequent thermokarst development. Estimation of the impacts of the predicted rise in precipitation and air temperatures under climate change requires quantitative knowledge about the spatial distribution of thermokarst development. In the last few years, unmanned aerial systems (UAS) and structure-from-motion multi-view stereo (SfM-MVS) photogrammetry attracted a tremendous amount of interest for acquiring high-definition topographic data. This study detected characteristics of thermokarst landforms using UAS and SfM-MVS photogrammetry at a disused airfield (3.0 ha) and for arable land that was previously used for farming (6.3 ha) in the Churapcha area, located on the right bank of the Lena River in central Yakutia. Orthorectified photographs and digital terrain models with spatial resolutions of 4.0 cm and 8.0 cm, respectively, were obtained for this study. At the disused airfield site and the abandoned arable land, 174 and 867 high-centered polygons that developed after the 1990s were detected, respectively. The data showed that the average diameter and average area of the polygons at the disused airfield site were 11.6 m and 111.2 m2, respectively, while those of the polygons in the abandoned arable land were 7.4 m and 46.8 m2, respectively. The abandoned arable land was characterized by smaller polygons and a higher polygon density. The differences in polygon size for the abandoned arable land and the disused airfield site indicate a difference in the ice wedge distributions and thermokarst developments. The subsidence rate was estimated as 2.1 cm/year for the disused airfield site and 3.9 cm/year for the abandoned arable land.