Search

Context: Recently, Unoccupied Aerial Systems (UAS) with photographic or Light Detection and Ranging (LIDAR) sensors have incorporated on-board survey-grade Global Navigation Satellite Systems that allow the direct georeferencing of the resulting datasets without Ground Control Points either in Real-Time (RTK) or Post-Processing Kinematic (PPK) modes. These approaches can be useful in hard-to-reach or hazardous areas. However, the resulting 3D models have not been widely tested, as previous studies tend to evaluate only a few points and conclude that systematic errors can be found. Objectives: We test the absolute positional accuracy of point clouds produced using UAS with direct-georeferencing systems. Methods: We test the accuracy and characteristics of point clouds produced using a UAS-LIDAR (with PPK) and a UAS-RGB (Structure-from-Motion or SfM photogrammetry with RTK and PPK) in a challenging environment: a coastline with a composite beach and cliff. The resulting models of each processing were tested using as a benchmark a point cloud surveyed simultaneously by a Terrestrial Laser Scanner. Results: The UAS-LIDAR produced the most accurate point cloud, with homogeneous cover and no noise. The systematic bias previously observed in the UAS-RGB RTK approaches are minimized using oblique images. The accuracy observed across the different surveyed landforms varied significantly. Conclusions: The UAS-LIDAR and UAS-RGB with PPK produced unbiased point clouds, being the latter the most cost-effective method. For the other direct georeferencing systems/approaches, the acquisition of GCP or the co-registration of the resulting point cloud is still necessary. [ABSTRACT FROM AUTHOR]

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

Copyright of Virtual Archaeology Review is the property of Virtual Archaeology Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The alpine environment with a high degree of nature protection is characterized by complete non-intervention. The processes and phenomena occurring in it are exclusively of a natural origin. Related geohazards are threatening the safety of people's movement. They arise as a result of a combination of meteorological, hydrological, and geological–morphological factors permanently operating in the country. Therefore, the prevention of fatal events is limited to monitoring and predicting changes in selected objects where we expect change. Changes in the shape and dimension, or the object's deformation, can be documented using geodetic and photogrammetric measurements. Our research focuses on monitoring a rock talus cone in High Tatras, Slovakia, at an altitude of 1700 m above sea level (ASL), created mainly due to erosion and seasonal torrential rains. To monitor changes in selected objects, we used mass non-contact methods of terrestrial laser scanning (TLS), UAS photogrammetry based on the principle of structure-from-motion–multi-view stereo (SfM–MVS), and airborne laser scanning (ALS). From the selective measurement methods, spatial measurement by a total station (TS) and height measurement based on the principle of precise leveling were used in the monitoring deformation network on a stand-alone boulder. The research results so far analyze and evaluate the possibilities, limits, effectiveness, and accuracy of the measurement and data processing methods used. As a result, we propose a complex methodology for monitoring similar phenomena in alpine environments. [ABSTRACT FROM AUTHOR]

Grain size assessments are necessary for understanding the various geomorphological, hydrological and ecological processes that occur within rivers. Recent research has shown that the application of Structure‐from‐Motion (SfM) photogrammetry to imagery from uncrewed aerial vehicles (UAVs) shows promise for rapidly characterising grain sizes along rivers in comparison to traditional field‐based methods. Here, we evaluated the applicability of different methods for estimating grain sizes in gravel bars along a study reach in the Olentangy River in Columbus, Ohio. We collected imagery of these gravel bars with a UAV and processed those images with SfM photogrammetry software to produce three‐dimensional point clouds and orthomosaics. Our evaluation compared statistical models calibrated on topographic roughness, which was computed from the point clouds, and to those based on image texture, which was computed from the orthomosaics. Our results showed that statistical models calibrated on image texture were more accurate than those based on topographic roughness. This might be because of site‐specific patterns of grain size, shape and imbrication. Such patterns would have complicated the detection of topographic signatures associated with individual grains. Our work illustrates that UAV‐SfM approaches show potential to be used as an accessible method for characterising surface grain sizes along rivers at higher spatial and temporal resolutions than those provided by traditional methods. [ABSTRACT FROM AUTHOR]

High-resolution coastline detection and monitoring are challenging on a global scale, especially in flat areas where natural events, sea level rise, and anthropic activities constantly modify the coastal environment. While the coastline related to the 0-level contour line can be extracted from accurate Digital Terrain Models (DTMs), the detection of the real-time, instantaneous coastline, especially at low tide, is a challenge that warrants further study and evaluation. In order to investigate an efficient combination of methods that allows to contribute to the knowledge in this field, this work uses topographic total station measurements, Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) technique, and the Structure from Motion (SfM) approach (using a low-cost drone equipped with optical and thermal cameras). All the data were acquired at the beginning of 2022 and refer to the areas of Boccasette and Barricata, in the Po River Delta (Northeastern of Italy). The real-time coastline obtained from the GNSS data was validated using the topographic total station measurements; the correspondent polylines obtained from the photogrammetric data (using both automatic extraction and manual restitutions by visual inspection of orhophotos) were compared with the GNSS data to evaluate the performances of the different techniques. The results provided good agreement between the real-time coastlines obtained from different approaches. However, using the optical images, the accuracy was strictly connected with the radiometric changes in the photos and using thermal images, both manual and automatic polylines provided differences in the order of 1–2 m. Multi-temporal comparison of the 0-level coastline with those obtained from a LiDAR survey performed in 2018 provided the detection of the erosion and accretion areas in the period 2018–2022. The investigation on the two case studies showed a better accuracy of the GNSS RTK method in the real-time coastline detection. It can be considered as reliable ground-truth reference for the evaluation of the photogrammetric coastlines. While GNSS RTK proved to be more productive and efficient, optical and thermal SfM provided better results in terms of morphological completeness of the data. [ABSTRACT FROM AUTHOR]

This article presents research conducted as part of the European project F-ATLAS, which aims to study the convent complexes of the Franciscan Observance and their landscape context between Italy, Spain and Portugal. The research uses historical and archival sources and integrated digital survey methodologies to document and study the network of the Observance convents and the routes that connect them for their conservation, protection and valorisation. In particular, the text illustrates the preliminary phases of the study of the conventual complex La Romita di Cesi (TR) in Umbria, Italy - one of the Oratories given in concession to Paoluccio Trinci in 1373, suppressed in 1866 and brought back to light in 1991 by Fra Bernardino. Parallel to studying historical and archival sources, two integrated digital survey campaigns were carried out using TLS and photographic instruments. This work aimed to become a reliable support for the preservation of the Observant Cultural Heritage, for its promotion to insiders and the public, and finally, for the future management of La Romita.

Abstract Benthic components of tropical mesophotic coral ecosystems (MCEs) are home to diverse fish assemblages, but the effect of multiscale spatial benthic characteristics on MCE fish is not well understood. To investigate the influence of fine‐scale benthic seascape structure and broad‐scale environmental characteristics on MCE fish, we surveyed fish assemblages in Seychelles at 30, 60 and 120 m depth using submersible video transects. Spatial pattern metrics from seascape ecology were applied to quantify fine‐scale benthic seascape composition, configuration and terrain morphology from structure‐from‐motion photogrammetry and multibeam echosounder bathymetry and to explore seascape–fish associations. Hierarchical clustering using fish abundance and biomass data identified four distinct assemblages separated by the depth and geographic location, but also significantly influenced by variations in fine‐scale seascape structure. Results further revealed variable responses of assemblage characteristics (fish biomass, abundance, trophic group richness, Shannon diversity) to seascape heterogeneity at different depths. Sites with steep slopes and high terrain complexity hosted higher fish abundance and biomass, with shallower fish assemblages (30–60 m) positively associated with aggregated patch mixtures of coral, rubble, sediment and macroalgae with variable patch shapes. Deeper fish assemblages (120 m) were positively associated with relief and structural complexity and local variability in the substratum and benthic cover. Our study demonstrates the potential of spatial pattern metrics quantifying benthic composition, configuration and terrain structure to delineate mesophotic fish–habitat associations. Furthermore, incorporating a finer‐scale perspective proved valuable to explain the compositional patterns of MCE fish assemblages. As developments in marine surveying and monitoring of MCEs continue, we suggest that future studies incorporating spatial pattern metrics with multiscale remotely sensed data can provide insights will that are both ecologically meaningful to fish and operationally relevant to conservation strategies.

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

Coral bleaching and mortality can show significant spatial and taxonomic heterogeneity at local scales, highlighting the need to understand the fine-scale drivers and impacts of thermal stress. In this study, we used structure-from-motion photogrammetry to track coral bleaching, mortality, and changes in community composition during the 2019 marine heatwave in Kāneʻohe Bay, Hawaiʻi. We surveyed 30 shallow reef patches every 3 weeks for the duration of the bleaching event (August-December) and one year after, resulting in a total of 210 large-area, high-resolution photomosaics that enabled us to follow the fate of thousands of coral colonies through time. We also measured environmental variables such as temperature, sedimentation, depth, and wave velocity at each of these sites, and extracted estimates of habitat complexity (rugosity R and fractal dimension D) from digital elevation models to better understand their effects on patterns of bleaching and mortality. We found that up to 80% of corals experienced moderate to severe bleaching in this period, with peak bleaching occurring in October when heat stress (Degree Heating Weeks) reached its maximum. Mortality continued to accumulate as bleaching levels dropped, driving large declines in more heat-susceptible species (77% loss of Pocillopora cover) and moderate declines in heat-tolerant species (19% and 23% for Porites compressa and Montipora capitata, respectively). Declines in live coral were accompanied by a rapid increase in algal cover across the survey sites. Spatial differences in bleaching were significantly linked to habitat complexity and coral species composition, with reefs that were dominated by Pocillopora experiencing the most severe bleaching. Mortality was also influenced by species composition, fractal dimension, and site-level differences in thermal stress. Our results show that spatial heterogeneity in the impacts of bleaching are driven by a mix of environmental variation, habitat complexity, and differences in assemblage composition.

The alpine environment with a high degree of nature protection is characterized by complete non-intervention. The processes and phenomena occurring in it are exclusively of a natural origin. Related geohazards are threatening the safety of people’s movement. They arise as a result of a combination of meteorological, hydrological, and geological–morphological factors permanently operating in the country. Therefore, the prevention of fatal events is limited to monitoring and predicting changes in selected objects where we expect change. Changes in the shape and dimension, or the object’s deformation, can be documented using geodetic and photogrammetric measurements. Our research focuses on monitoring a rock talus cone in High Tatras, Slovakia, at an altitude of 1700 m above sea level (ASL), created mainly due to erosion and seasonal torrential rains. To monitor changes in selected objects, we used mass non-contact methods of terrestrial laser scanning (TLS), UAS photogrammetry based on the principle of structure-from-motion–multi-view stereo (SfM–MVS), and airborne laser scanning (ALS). From the selective measurement methods, spatial measurement by a total station (TS) and height measurement based on the principle of precise leveling were used in the monitoring deformation network on a stand-alone boulder. The research results so far analyze and evaluate the possibilities, limits, effectiveness, and accuracy of the measurement and data processing methods used. As a result, we propose a complex methodology for monitoring similar phenomena in alpine environments.

Structure from Motion (SfM) photogrammetry has become in the last years one of the most used methodologies for three-dimensional recording in many scientific fields thanks to its great precision, low cost and speed. The aim of this paper is to present a workflow methodology to obtain precise results for the graphical documentation of an archaeological site with complex structures (Rouco & Benavides, 2023)The improvement of photogrammetric hardware and software has provided us with a tool of great value for archaeological research and survey. SfM photogrammetry has been widely applied to cultural heritage studies in a variety of ways, such as digitizing historical buildings, archaeological sites and artefacts. Improvement in UAV-mounted camera technology and calibration methods of non-metric cameras have expanded the use of photogrammetric modelling to non-professional and semi-professional users (Westoby et al. 2012). Although the potential of SfM photogrammetry allows obtaining 3D models with a very good graphic appearance using almost any type of camera, these models need certain calibration and adjustment processes in order to achieve enough precision for professional use.This paper focuses on discussing some important data capture workflow recommendations, as well as the new processing workflows implemented in Agisoft Metashape version 2.0, which improve 3D digital reconstruction and graphical documentation to make it complete and precise.The Herrera Roman Baths site offers an excellent opportunity to explore the complex casuistry in the record of cultural heritage due to the complexity in the registration of the structures and the high degree of precision and graphic resolution that the project required for the tasks of restoration of decorative elements. The existence of a roof structure that protects them has forced us to carry out a manual flight with a UAV at a very low altitude (4m), and to develop different modeling strategies to guarantee metric precision and a high level of detail.DOI: https://doi.org/10.20365/disegnarecon.30.2023.2

Change detection has been increasingly studied in remote and close-range sensing in the last decades, driven by its importance in environment monitoring and database updating. Due to the development of sensing technologies, data acquisition has become more accessible and affordable and thus more data from various sensing platforms have become available. Thanks to structure-from-motion photogrammetry and lidar technologies, 3D change detection from point cloud data is drawing considerable attention in recent years. Motivated by the lack of a comprehensive review of 3D change detection in the urban environment, this paper reviews the latest developments in urban object change detection using point cloud data. In particular, four types of objects, namely building, street scene, urban tree, and construction site, are analysed in-depth. The use of different data sources for each object-of-interest and the open-source data with change labels are summarised. Then the change detection methods are thoroughly reviewed at pixel, point, voxel, segment and object levels, whose pros and cons are analysed in detail. Moreover, the challenges and opportunities brought by point cloud data and new methods, such as Siamese network deep learning, are discussed for future considerations.

This article presents research conducted as part of the European project F-ATLAS, which aims to study the convent complexes of the Franciscan Observance and their landscape context between Italy, Spain and Portugal. The research uses historical and archival sources and integrated digital survey methodologies to document and study the network of the Observance convents and the routes that connect them for their conservation, protection and valorisation. In particular, the text illustrates the preliminary phases of the study of the conventual complex La Romita di Cesi (TR) in Umbria, Italy - one of the Oratories given in concession to Paoluccio Trinci in 1373, suppressed in 1866 and brought back to light in 1991 by Fra Bernardino. Parallel to studying historical and archival sources, two integrated digital survey campaigns were carried out using TLS and photographic instruments. This work aimed to become a reliable support for the preservation of the Observant Cultural Heritage, for its promotion to insiders and the public, and finally, for the future management of La Romita. [ABSTRACT FROM AUTHOR]

Benthic components of tropical mesophotic coral ecosystems (MCEs) are home to diverse fish assemblages, but the effect of multiscale spatial benthic characteristics on MCE fish is not well understood. To investigate the influence of fine‐scale benthic seascape structure and broad‐scale environmental characteristics on MCE fish, we surveyed fish assemblages in Seychelles at 30, 60 and 120 m depth using submersible video transects. Spatial pattern metrics from seascape ecology were applied to quantify fine‐scale benthic seascape composition, configuration and terrain morphology from structure‐from‐motion photogrammetry and multibeam echosounder bathymetry and to explore seascape–fish associations. Hierarchical clustering using fish abundance and biomass data identified four distinct assemblages separated by the depth and geographic location, but also significantly influenced by variations in fine‐scale seascape structure. Results further revealed variable responses of assemblage characteristics (fish biomass, abundance, trophic group richness, Shannon diversity) to seascape heterogeneity at different depths. Sites with steep slopes and high terrain complexity hosted higher fish abundance and biomass, with shallower fish assemblages (30–60 m) positively associated with aggregated patch mixtures of coral, rubble, sediment and macroalgae with variable patch shapes. Deeper fish assemblages (120 m) were positively associated with relief and structural complexity and local variability in the substratum and benthic cover. Our study demonstrates the potential of spatial pattern metrics quantifying benthic composition, configuration and terrain structure to delineate mesophotic fish–habitat associations. Furthermore, incorporating a finer‐scale perspective proved valuable to explain the compositional patterns of MCE fish assemblages. As developments in marine surveying and monitoring of MCEs continue, we suggest that future studies incorporating spatial pattern metrics with multiscale remotely sensed data can provide insights will that are both ecologically meaningful to fish and operationally relevant to conservation strategies. [ABSTRACT FROM AUTHOR]

High-resolution coastline detection and monitoring are challenging on a global scale, especially in flat areas where natural events, sea level rise, and anthropic activities constantly modify the coastal environment. While the coastline related to the 0-level contour line can be extracted from accurate Digital Terrain Models (DTMs), the detection of the real-time, instantaneous coastline, especially at low tide, is a challenge that warrants further study and evaluation. In order to investigate an efficient combination of methods that allows to contribute to the knowledge in this field, this work uses topographic total station measurements, Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) technique, and the Structure from Motion (SfM) approach (using a low-cost drone equipped with optical and thermal cameras). All the data were acquired at the beginning of 2022 and refer to the areas of Boccasette and Barricata, in the Po River Delta (Northeastern of Italy). The real-time coastline obtained from the GNSS data was validated using the topographic total station measurements; the correspondent polylines obtained from the photogrammetric data (using both automatic extraction and manual restitutions by visual inspection of orhophotos) were compared with the GNSS data to evaluate the performances of the different techniques. The results provided good agreement between the real-time coastlines obtained from different approaches. However, using the optical images, the accuracy was strictly connected with the radiometric changes in the photos and using thermal images, both manual and automatic polylines provided differences in the order of 1–2 m. Multi-temporal comparison of the 0-level coastline with those obtained from a LiDAR survey performed in 2018 provided the detection of the erosion and accretion areas in the period 2018–2022. The investigation on the two case studies showed a better accuracy of the GNSS RTK method in the real-time coastline detection. It can be considered as reliable ground-truth reference for the evaluation of the photogrammetric coastlines. While GNSS RTK proved to be more productive and efficient, optical and thermal SfM provided better results in terms of morphological completeness of the data.

Urban development will likely continue to increase in suburban areas to cater for the growing human population. In Nigeria, the relevant analysis of these urban developments is not well documented. This article presents spatiotemporal datasets for analysing urban developments in a suburb of Kuje, an Area Council within the Federal Capital Territory of Nigeria. Data from Google Earth (GE) historical imagery of 2005 was used as a baseline for analysis and was compared with a UAV digital orthomosaic of 2019 to quantify urban developments. This data provides useful information on the status of urban development that has taken place in the Kuje suburb over 14 years. The data will be of great importance to town planners and urban development authorities for future planning, and for making informed decisions about urban development issues in the area.

Accurate data on community structure is a priority issue in studying coastal habitats facing human pressures. The recent development of remote sensing tools has offered a ground-breaking way to collect ecological information at a very fine scale, especially using low-cost aerial photogrammetry. Although coastal mapping is carried out using Unmanned Aerial Vehicles (UAVs or drones), they can provide limited information regarding underwater benthic habitats. To achieve a precise characterisation of underwater habitat types and species assemblages, new imagery acquisition instruments become necessary to support accurate mapping programmes. Therefore, this study aims to evaluate an integrated approach based on Structure from Motion (SfM) photogrammetric acquisition using low-cost Unmanned Aerial (UAV) and Surface (USV) Vehicles to finely map shallow benthic communities, which determine the high complexity of coastal environments. The photogrammetric outputs, including both UAV-based high (sub-meter) and USV-based ultra-high (sub-centimetre) raster products such as orthophoto mosaics and Digital Surface Models (DSMs), were classified using Object-Based Image Analysis (OBIA) approach. The application of a supervised learning method based on Support Vector Machines (SVM) classification resulted in good overall classification accuracies > 70%, proving to be a practical and feasible tool for analysing both aerial and underwater ultra-high spatial resolution imagery. The detected seabed cover classes included above and below-water key coastal features of ecological interest such as seagrass beds, “banquettes” deposits and hard bottoms. Using USV-based imagery can considerably improve the identification of specific organisms with a critical role in benthic communities, such as photophilous macroalgal beds. We conclude that the integrated use of low-cost unmanned aerial and surface vehicles and GIS processing is an effective strategy for allowing fully remote detailed data on shallow water benthic communities.

The paper presents a group of four, approximately 0.5m large, stone disks from entrances or cemeteries of two protohistoric hillforts of north-eastern Adriatic. The disks, having a sparse chronology with the exception of one dated to the Middle Bronze Age, show flat and plain surfaces or covered with sub-circular depressions. One disk shows two larger cup-marks at the centre of both faces. They are interpreted as ritual artefacts based on the association with sacred settlement locations and comparisons with similar coeval stones found mainly close to citadel entrances, burials and thresholds in the Aegean area and Anatolia.

Currently, the creation of digital copies (digital twins) of various objects by remote sensing methods producing point clouds is becoming commonplace. This might be particularly important for the digital preservation of historical objects. Such clouds are typically primarily acquired as unordered sets of points with regular dense spacing, making the clouds huge in size, which causes such clouds to be difficult to process, store and share. The clouds are, therefore, usually diluted before use, typically through uniform dilution with a set spacing; such dilution can, however, lead to the loss of detail in the resulting cloud (washed-out edges and fine features). In this paper, we present an easy-to-use and computationally inexpensive progressive dilution method preserving detail in highly rugged/curved areas while significantly reducing the number of points in flat areas. This is done on the basis of a newly proposed characteristic T, which is based on the local scattering of the cloud (i.e., on the ruggedness of the local relief). The performance of this algorithm is demonstrated on datasets depicting parts of historic buildings of different characters. The results are evaluated on the basis of (a) root mean square deviation (RMSD) between the original and diluted clouds, (b) of visual evaluation of the differences and (c) of reduction in the point cloud size, demonstrating an excellent performance of the algorithm with a minimum loss of detail while significantly reducing the point clouds (approx. by 47–66% compared to the corresponding uniform dilution for individual datasets) [ABSTRACT FROM AUTHOR]

Soil emissivity of Arctic regions is a key parameter for assessing surface properties from microwave brightness temperature (Tb) measurements. Particularly in winter, frozen soil permittivity and roughness are two poorly characterized unknowns that must be considered. Here, we show that after removing snow, the 3D soil roughness can be accurately inferred from in-situ photogrammetry using Structure from Motion (SfM). We focus on using SfM techniques to provide accurate roughness measurements and improve emissivity models parametrization of frozen arctic soil for microwave applications. Validation was performed from ground-based radiometric measurements at 19 and 37 GHz using three different soil emission models: the Wegmüller and Mätzler [1999, TGRS] model (Weg99), the Wang and Choudhury [1981, JGR] model (QNH), and a geometrical optics model (Geo Optics). Measured and simulated brightness temperatures over different tundra and rock sites in the Canadian High Arctic show that Weg99, parametrized with SfM-based roughness and optimized permittivity $\lpar \varepsilon \rpar$, yielded an RMSE of 3.1 K ( $R^2 = 0.71$) for all frequencies and polarizations. Our SfM based approach allowed us to measure roughness with 0.1 mm accuracy at 55 locations of different land cover type using a digital camera and metal plates of know dimensions.

Abstract Recent advances in sea floor measurements and modelling have revealed new insight into submarine channel processes; however, understanding how these short‐term perspectives influence long‐term evolution of submarine channels has been limited by the difficulty in linking processes to products in the stratigraphic record. Outcrops present opportunities to characterise the detailed internal architecture of deep‐water channel fills over a wide range of timescales, but obtaining observations is compounded by challenges in outcrop accessibility and perspective along broad exposures. To demonstrate the potential value of modern remote sensing techniques in supplementing fieldwork, an extensive dip‐oriented outcrop exposure of Cretaceous deep‐water channel deposits was re‐evaluated using a 3D digital outcrop model generated from uninhabited/unmanned aerial vehicle photogrammetry. Results confirmed previous field‐based documentation of depositional element‐scale stratigraphic architecture, but also revealed nuanced internal detail that was not captured from field‐based perspectives alone. Subtle internal channel‐fill architecture, including discontinuous sandstone wedges and the interpreted stratigraphic products of upslope‐migrating bedforms, are also recognised. This study demonstrates the sedimentary detail that can be uncovered by integrating conventional field‐based approaches limited by viewable scale, perspective, and/or accessibility, with emerging remote sensing techniques. The unmanned aerial vehicle photogrammetry approach used here provides valuable supplemental data in the investigation of deep‐water channel system deposits and has the potential to overcome inherent challenges in outcrop mapping for numerous applications.

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

The Causeway Coast World Heritage Site (Northern Ireland) is subject to rockfalls occurring on the coastal cliffs, thus raising major safety concerns given the number of tourists visiting the site. However, such high tourist frequentation makes this site favorable to implement citizen science monitoring programs. Besides allowing for the collection of a larger volume of data, better distributed spatially and temporally, citizen science also increases citizens' awareness—in this case, about risks. Among citizen science approaches, Structure-from-Motion photogrammetry based on crowd-sourced photographs has the advantage of not requiring any particular expertise on the part of the operator who takes photos. Using a mock citizen survey for testing purposes, this study evaluated different methods relying on crowd-sourced photogrammetry to integrate surveys performed by citizens into a landslide monitoring program in Port Ganny (part of the touristic site of the Giant's Causeway). Among the processing scenarios that were tested, the Time-SIFT method allows the use of crowd-sourced data in a very satisfactory way in terms of reconstruction quality, with a standard deviation of 8.6 cm. [ABSTRACT FROM AUTHOR]

Copyright of Virtual Archaeology Review is the property of Virtual Archaeology Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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

Unoccupied aerial systems (UASs) are frequently used in the field of fluvial geomorphology due to their capabilities for observing the continuum rather than single sample points. We introduce a (semi-)automatic workflow to measure river bathymetry and surface flow velocities of entire river reaches at high resolution, based on UAS videos and imagery. Video frame filtering improved the visibility of the riverbed using frame co-registration and averaging with a median filter. Subsequently, these video frames were incorporated with still images acquired by UASs into a structure from motion (SfM) photogrammetry approach to reconstruct the camera poses (i.e. positions and orientations) and the 3D point cloud of the river reach. The heights of submerged points were further processed using small-angle and multi-view refraction correction approaches to account for the refraction impact. The flow velocity pattern of the river surface was measured using the estimated camera pose from SfM, the reconstructed bathymetric point cloud and the co-registered video frames in combination with image velocimetry analysis. Finally, discharge was estimated at selected cross-sections, considering the average surface velocity and the bathymetry. Three case studies were considered to assess the performance of the workflow under different environmental conditions. The studied river reaches spanned a length between 0.15 and 1 km. The bathymetry was reconstructed with average deviations to RTK-GNSS point measurements as low as 1 cm with a standard deviation of 6 cm. If frames were processed with the median filter, the number of underwater points increased by up to 21%. The image-based surface velocities revealed an average deviation to reference measurements between 0.05 and 0.08 m s-1. The imagebased discharge was estimated with deviations to ADCP references of up to 5%, however this was sensitive to errors in water-level retrieval. The output of our workflow can provide a valuable input to hydro-morphological models. [ABSTRACT FROM AUTHOR]

Soil emissivity of Arctic regions is a key parameter for assessing surface properties from microwave brightness temperature (Tb) measurements. Particularly in winter, frozen soil permittivity and roughness are two poorly characterized unknowns that must be considered. Here, we show that after removing snow, the 3D soil roughness can be accurately inferred from in-situ photogrammetry using Structure from Motion (SfM). We focus on using SfM techniques to provide accurate roughness measurements and improve emissivity models parametrization of frozen arctic soil for microwave applications. Validation was performed from ground-based radiometric measurements at 19 and 37 GHz using three different soil emission models: the Wegmüller and Mätzler [1999, TGRS] model (Weg99), the Wang and Choudhury [1981, JGR] model (QNH), and a geometrical optics model (Geo Optics). Measured and simulated brightness temperatures over different tundra and rock sites in the Canadian High Arctic show that Weg99, parametrized with SfM-based roughness and optimized permittivity (ε) , yielded an RMSE of 3.1 K ( R 2 = 0.71) for all frequencies and polarizations. Our SfM based approach allowed us to measure roughness with 0.1 mm accuracy at 55 locations of different land cover type using a digital camera and metal plates of know dimensions. [ABSTRACT FROM AUTHOR]

Recent advances in sea floor measurements and modelling have revealed new insight into submarine channel processes; however, understanding how these short‐term perspectives influence long‐term evolution of submarine channels has been limited by the difficulty in linking processes to products in the stratigraphic record. Outcrops present opportunities to characterise the detailed internal architecture of deep‐water channel fills over a wide range of timescales, but obtaining observations is compounded by challenges in outcrop accessibility and perspective along broad exposures. To demonstrate the potential value of modern remote sensing techniques in supplementing fieldwork, an extensive dip‐oriented outcrop exposure of Cretaceous deep‐water channel deposits was re‐evaluated using a 3D digital outcrop model generated from uninhabited/unmanned aerial vehicle photogrammetry. Results confirmed previous field‐based documentation of depositional element‐scale stratigraphic architecture, but also revealed nuanced internal detail that was not captured from field‐based perspectives alone. Subtle internal channel‐fill architecture, including discontinuous sandstone wedges and the interpreted stratigraphic products of upslope‐migrating bedforms, are also recognised. This study demonstrates the sedimentary detail that can be uncovered by integrating conventional field‐based approaches limited by viewable scale, perspective, and/or accessibility, with emerging remote sensing techniques. The unmanned aerial vehicle photogrammetry approach used here provides valuable supplemental data in the investigation of deep‐water channel system deposits and has the potential to overcome inherent challenges in outcrop mapping for numerous applications. [ABSTRACT FROM AUTHOR]

• SfM photogrammetry can be applied for recovery of 3D footwear impressions. • Workflow and main sources of error are outlined. • Protocol for determining precision set out that can be used by any practitioner. • Range of examples and cases studies are presented. • Future research agenda to aid application in practice is established. The recovery of three-dimensional footwear impressions at crime scenes can be a challenge but can also yield important investigative data. Traditional methods involve casting 3D impressions but these methods have limitations: the trace is usually destroyed during capture; the process can be time consuming, with a risk of failure; and the resultant cast is bulky and therefore difficult to share and store. The use of Structure from Motion (SfM) photogrammetry has been used widely to capture fossil footprints in the geological record and while there is a small body of work advocating its use in forensic practice the full potential of this technique has yet to be realised in an operational context. The availability of affordable software is one limiting factor and here we report the availability of a bespoke freeware for SfM recovery and subsequent analysis of for footwear evidence (DigTrace). Our aim here is not to provide a rigorous comparison of SfM methods to other recovery methods, but more to illustrate the potential while also documenting the typical workflows and potential errors associated with an SfM based approach. By doing so we hope to encourage further research, experimentation and ultimately adoption by practitioners. [ABSTRACT FROM AUTHOR]

The Causeway Coast World Heritage Site (Northern Ireland) is subject to rockfalls occurring on the coastal cliffs, thus raising major safety concerns given the number of tourists visiting the site. However, such high tourist frequentation makes this site favorable to implement citizen science monitoring programs. Besides allowing for the collection of a larger volume of data, better distributed spatially and temporally, citizen science also increases citizens’ awareness—in this case, about risks. Among citizen science approaches, Structure-from-Motion photogrammetry based on crowd-sourced photographs has the advantage of not requiring any particular expertise on the part of the operator who takes photos. Using a mock citizen survey for testing purposes, this study evaluated different methods relying on crowd-sourced photogrammetry to integrate surveys performed by citizens into a landslide monitoring program in Port Ganny (part of the touristic site of the Giant’s Causeway). Among the processing scenarios that were tested, the Time-SIFT method allows the use of crowd-sourced data in a very satisfactory way in terms of reconstruction quality, with a standard deviation of 8.6 cm.

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

Image‐based gauging stations can allow for significant densification of monitoring networks of river water stages. However, thus far, most camera gauges do not provide the robustness of accurate measurements due to the varying appearance of water in the stream throughout the year. We introduce an approach that allows for automatic and reliable water stage measurement combining deep learning and photogrammetric techniques. First, a convolutional neural network (CNN), a class of deep learning, is applied to the segmentation (i.e., pixel classification) of water in images. The CNNs SegNet and fully convolutional network (FCN) are associated with a transfer learning strategy to segment water on images acquired by a Raspberry Pi camera. Errors of water segmentation with the two CNNs are lower than 3%. Second, the image information is transformed into metric water stage values by intersecting the extracted water contour, generated using the segmentation results, with a 3D model reconstructed with structure‐from‐motion (SfM) photogrammetry. The highest correlations between a reference gauge and the image‐based approaches reached 0.93, and average deviations were lower than 4 cm. Our approach allows for the densification of river monitoring networks based on camera gauges, providing accurate water stage measurements. Key Points: Development of a camera gauge to measure the water stage from single images using convolutional neural network (CNN)Combining automatic/robust water area detection with high‐resolution 3D data for stage retrieval in challenging environmental conditionsCNN based water stage measurements reveal accuracy potential at cm‐range and up to 93% agreement with traditional reference gauge [ABSTRACT FROM AUTHOR]

Camera calibration is an avoidable process for computationalvision applications, such as 3D reverse engineering, industrial robot calibration, optic-pattern recognition, simultaneous localization and mapping, autonomous visual-driving and photogrammetric vision. The camera calibration problem is too complex, nonlinear and multimodal. Traditional camera calibration methods using gradient-based optimization often trap to one of the many local solutions available. Accurate computation ability of traditional camera calibration methods is limited since they use gradient-based optimization methods. Since evolutionary computing algorithms can avoid local solutions of numerical problems, they have the potential to accurately compute the required camera calibration parameters for high-precision computationalvision applications. In this paper, the camera calibration parameters are computed by using 11 evolutionary computing algorithms, i.e., WDE, ABC, PSO, COBIDE, DE, CS, GWO, TLBO, MVMO, FOA and LSHADE. In order to make unbiased evaluation of the camera calibration results provided by the related evolutionary computing algorithms, two gradient-based traditional camera calibration methods, i.e., Zhang and Bouguet, have been used in the conducted experiments in this paper. The camera calibration results of the related methods were used to model a 3D physical test scene by using Structure from Motion photogrammetry method. The reference data set of the related 3D physical scene has been captured by using a 3D terrestrial laser scanner. Statistical comparison of the camera calibration results exposed that WDE supplies statistically better results than other comparison algorithms. [ABSTRACT FROM AUTHOR]

In temperate coastal regions of Western Europe, the polychaete Sabellaria alveolata (Linné) builds large intertidal reefs of several hectares on soft-bottom substrates. These reefs are protected by the European Habitat Directive EEC/92/43 under the status of biogenic structures hosting a high biodiversity and providing ecological functions such as protection against coastal erosion. As an alternative to time-consuming field campaigns, a UAV-based Structure-from-Motion photogrammetric survey was carried out in October 2020 over Noirmoutier Island (France) where the second-largest known European reef is located in a tidal delta. A DJI Phantom 4 Multispectral UAV provided a topographic dataset at very high resolutions of 5 cm/pixel for the Digital Surface Model (DSM) and 2.63 cm/pixel for the multispectral orthomosaic images. The reef footprint was mapped using a combination of two topographic indices: the Topographic Openness Index and the Topographic Position Index. The reef structures covered an area of 8.15 ha, with 89% corresponding to the main reef composed of connected and continuous biogenic structures, 7.6% of large isolated structures (2), and 4.4% of small isolated reef clumps (2). To further describe the topographic complexity of the reef, the Geomorphon landform classification was used. The spatial distribution of tabular platforms considered as a healthy stage of the reef in contrast to a degraded stage was mapped with a proxy that consists in comparing the reef volume to a theoretical tabular-shaped reef volume. Epibionts colonizing the reef (macroalgae, mussels, and oysters) were also mapped by combining multispectral indices such as the Normalised Difference Vegetation Index and simple band ratios with topographic indices. A confusion matrix showed that macroalgae and mussels were satisfactorily identified but that oysters could not be detected by an automated procedure due to their spectral complexity. The topographic indices used in this work should now be further exploited to propose a health index for these large intertidal reefs.

This paper is the first of a pair that report the findings of a river rehabilitation project centred on the reconnection of a formerly diverted headwater tributary (Ben Gill) to its main‐stem river (the River Ehen). The present paper describes the geomorphic evolution of the tributary in the 2 years following its reconnection, with a particular focus on assessing the volumes of sediment now being supplied to the main‐stem Ehen. Structure‐from‐Motion photogrammetry was used to produce Digital Elevation Models (DEMs) of the newly connected tributary, with successive DEMs compared to assess topographic changes in the channel and quantify volumes of material exported. 3D errors in the DEMs were small relative to the scour and fill observed in the channel (error 0.016–0.056 m compared to up to 1.7 m vertical change between consecutive surveys). Erosion was the dominant process in the tributary channel, though this varied spatially and temporally. Over the 2‐year period, an estimated minimum of 384 m3 of coarse sediment was exported from Ben Gill and delivered to the confluence zone, where a new bar feature developed as a result. This estimate is twice as high as earlier ones. Analysis of the growth of this bar suggested that much of the material supplied by Ben Gill remains here temporarily, with onward conveyance constrained by the competence of the regulated main‐stem. The work shows that, thanks to the reconnection, this small (0.55 km2) ephemeral tributary (flowing for only around 20% of the time) has become a key source of sediment for the main‐stem Ehen. The second in the pair of papers focuses on the geomorphic responses of the main‐stem to this renewed supply of sediment. [ABSTRACT FROM AUTHOR]

Recent development of lightweight and small size multi-frequency GNSS receivers allows determination of the precise position of the moving platform and spatial data acquisition without the need for setting up and measuring of ground control points. The main advantage of this approach is a higher operational capacity with reduced time and cost of field measurement. This relates to fieldwork in inaccessible areas with demanding terrain configuration. In this paper development and use of a UAS with direct georeferencing of camera sensor for spatial data acquisition is described, and the possibility of 3D scene reconstruction based on the precise position of the camera with predetermined interior parameters is examined. Modern computer vision-based SfM photogrammetry algorithms are used for determining attitude parameters and reconstruction of the scene. For that purpose, several tests on two different test fields were performed using various system parameters for collecting and analysis of several spatial data sets. The presented results demonstrate a satisfactory accuracy (3.1 cm planar and 6.4 cm spatial) of the system for various applications in geodesy. [ABSTRACT FROM AUTHOR]

It is well established that digital elevation models (DEMs) derived from unmanned aerial vehicle (UAV) images and processed by structure from motion may contain important systematic vertical errors arising from limitations in camera geometry modelling. Even when significant, such 'dome'‐shaped errors can often remain unnoticed unless specific checks are conducted. Previous methods used to reduce these errors have involved: the addition of convergent images to supplement traditional vertical datasets, the usage of a higher number of ground control points, precise direct georeferencing techniques (RTK/PPK) or more refined camera pre‐calibration. This study confirms that specific UAV flight designs can significantly reduce dome errors, particularly those that have a higher number of tie points connecting distant images, and hence contribute to a strengthened photogrammetric network. A total of 22 flight designs were tested, including vertical, convergent, point of interest (POI), multiscale and mixed imagery. Flights were carried out over a 300 × 70 m2 flat test field area, where 143 ground points were accurately established. Three different UAVs and two commercial software packages were trialled, totalling 396 different tests. POI flight designs generated the smallest systematic errors. In contrast, vertical flight designs suffered from larger dome errors; unfortunately, a configuration that is ubiquitous and most often used. By using the POI flight design, the accuracy of DEMs will improve without the need to use more ground control or expensive RTK/PPK systems. Over flat terrain, the improvement is especially important in self‐calibration projects without (or with just a few) ground control points. Some improvement will also be observed on those projects using camera pre‐calibration or with stronger ground control. © 2020 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) equipped with photogrammetric or remote sensing instrumentations offer numerous opportunities in mapping and data collection for topographic modelling. An example is an emerging technique known as Structure-from-Motion (SfM) photogrammetry used for the collection of low-cost, high spatial resolution, three-dimensional data. This study utilised the real time kinematic-based point-to-point validation technique and two sets of randomly selected ground control points to assess the capability and geometric accuracy of SfM-technology for three-dimensional (3D) terrain mapping over a small study area to contribute to the knowledge of applicability. The data used was collected in Garscube Sports Complex, Glasgow City Council, Scotland. The study utilised fifteen (15) Ground Control Points (GCPs) coordinated by the Real Time Kinematic Global Navigation Satellite System (RTK GNSS) positioning technique, while a DJI Phantom 3 Professional unmanned aerial vehicle was used to obtain the aerial photos in a single flight to minimise cost. The processing of the photos was done using Pix4Dmapper Pro software version 4.2.27. A point-to-point validation method was used to evaluate the 3D positional accuracy of the orthophoto and DSM. The results of the validation with ten checkpoints suggest a high level of accuracy and acceptability given a Root Mean Square Error of 20.93 mm, 18.48 mm and 46.05 mm in the X, Y and Z coordinates respectively. In conclusion, the study has shown that SfM technique can be used to produce highresolution and accurate topographic data for geospatial applications with significant advantages over the traditional methods. However, it is to be noted that the quality of the data captured is dependent on the methodology adopted and should be taken into consideration. [ABSTRACT FROM AUTHOR]

The surface roughness of agricultural soils is mainly related to the type of tillage performed, typically consisting of oriented and random components. Traditionally, soil surface roughness (SSR) characterization has been difficult due to its high spatial variability and the sensitivity of roughness parameters to the characteristics of the instruments, including its measurement scale. Recent advances in surveying have greatly improved the spatial resolution, extent, and availability of surface elevation datasets. However, it is still unknown how new roughness measurements relates with the conventional roughness measurements such as 2D profiles acquired by laser profilometers. The objective of this study was to evaluate the suitability of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) photogrammetry techniques for quantifying SSR over different agricultural soils. With this aim, an experiment was carried out in three plots (5 × 5 m) representing different roughness conditions, where TLS and SfM photogrammetry measurements were co‐registered with 2D profiles obtained using a laser profilometer. Differences between new and conventional roughness measurement techniques were evaluated visually and quantitatively using regression analysis and comparing the values of six different roughness parameters. TLS and SfM photogrammetry measurements were further compared by evaluating multi‐directional roughness parameters and analyzing corresponding Digital Elevation Models. The results obtained demonstrate the ability of both TLS and SfM photogrammetry techniques to measure 3D SSR over agricultural soils. However, profiles obtained with both techniques (especially SfM photogrammetry) showed a loss of high‐frequency elevation information that affected the values of some parameters (e.g. initial slope of the autocorrelation function, peak frequency and tortuosity). Nevertheless, both TLS and SfM photogrammetry provide a massive amount of 3D information that enables a detailed analysis of surface roughness, which is relevant for multiple applications, such as those focused in hydrological and soil erosion processes and microwave scattering. © 2019 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The traditional study of palaeoseismic trenches, involving logging, stratigraphic and structural interpretation, can be time consuming and affected by biases and inaccuracies. To overcome these limitations, a new workflow is presented that integrates infrared hyperspectral and photogrammetric data to support field‐based palaeoseismic observations. As a case study, this method is applied on two palaeoseismic trenches excavated across a post‐glacial fault scarp in northern Finnish Lapland. The hyperspectral imagery (HSI) is geometrically and radiometrically corrected, processed using established image processing algorithms and machine learning approaches, and co‐registered to a structure‐from‐motion point cloud. HSI‐enhanced virtual outcrop models are a useful complement to palaeoseismic field studies as they not only provide an intuitive visualisation of the outcrop and a versatile data archive, but also enable an unbiased assessment of the mineralogical composition of lithologic units and a semi‐automatic delineation of contacts and deformational structures in a 3D virtual environment. [ABSTRACT FROM AUTHOR]

In this paper, three methods (Terrestrial Laser Scanner (TLS), terrestrial Structure from Motion photogrammetry (SfM) and aerial SfM photogrammetry with an Unmanned Aerial Vehicle (UAV)) were evaluated and compared to produce high resolution point clouds and Digital Elevation Models (DEMs) in a semiarid, complex badland area (Los Aguarales) with tourism activities. Geomorphological processes and dynamics were studied at different spatial scales. The preliminary results showed the possibilities of a multiscale approach, using various non-invasive techniques, to assess geomorphological processes. The high resolution of the point clouds, obtained with TLS and terrestrial SfM photogrammetry, allowed preliminary identification of numerous spatial details, although no relevant topographical changes were detected during a short, wet spring period (with rainfall of 200 mm). UAV images allowed work at larger scales (catchment), mapping piping features, and could be seen as a worthwhile tool for time-effective data acquisition from larger areas. The application of different technologies and a multiscale approach to generate high resolution DEMs is a useful technique when carrying out geomorphological studies in semiarid badland areas. However, long term studies will be necessary to verify the suitability of these techniques in such complex landscapes, and quantify topographical changes and erosion rates. Finally, the information obtained with these tools could be used to promote the study area as an interesting geomorphosite with opportunities for tourism.

This article presents a novel approach to explore mangrove dynamics on a prograding delta by integrating unmanned aerial vehicle (UAV) and satellite imagery. The Porong Delta in Indonesia has a unique geographical setting with rapid delta development and expansion of the mangrove belt. This is due to an unprecedented mud load from the LUSI mud volcanic eruption. The mangrove dynamics analysis combines UAV-based Structure from Motion (SfM) photogrammetry and 11 years (2009–2019) satellite imagery cloud computing analysis by Google Earth Engine (GEE). Our analysis shows unique, high-spatiotemporal-resolution mangrove extent maps. The SfM photogrammetry analysis leads to a 3D representation of the mangrove canopy and an estimate of mangrove biophysical properties with accurate height and individual position of the mangroves stand. GEE derived vegetation indices resulted in high (three-monthly) resolution mangrove coverage dynamics over 11 years (2009–2019), yielding a value of more than 98% for the overall, producer and consumer accuracy. Combining the satellite-derived age maps and the UAV-derived spatial tree structure allowed us to monitor the mangrove dynamics on a rapidly prograding delta along with its structural attributes. This analysis is of essential value to ecologists, coastal managers, and policymakers.

Three‐dimensional (3D) documenting and rubbing of rock art is aimed to produce descriptive and analytic graphic documentation with metric scale and geospatial information for archaeological analysis. Although the integrated surveying technologies of aerial photogrammetry, close‐range photogrammetry, and laser scanning have been widely used to generate the 3D models of archaeological sites, the implementation of these technologies in complex surroundings with steep terrain, such as riverside cliffs, remains challenging. In this study, we present an unmanned aerial vehicle (UAV)‐based structure‐from‐motion (SfM) photogrammetry approach to obtain the 3D geospatial data of rock paintings. A field data collection approach for high‐resolution multiperspective images using UAV equipped with a high‐resolution camera is implemented together with high accuracy ground control points (GCPs). An appropriate flowchart of multi‐view stereo (MVS) photogrammetry processing is designed including multi‐view dense matching, bundle adjustment (BA) and metric rectification for the orthoimages production of the rock paintings. A digital rubbing approach based on the orthoimages is proposed to obtain the geometry contents, including symbols and characters, of the rock paintings. The Huashan rock paintings, which are located on the vertical faces of the cliffs that line the course of Zuo River, is taken as a case study. Our proposed approach can obtain orthoimages of the Huashan rock paintings with 2 mm resolution. The reality‐based 3D model can reach the absolute accuracy of 5 mm. Clear, exact, and blur‐free metric rubbing images of the Huashan rock paintings are produced, which are useful for the research and preservation of Zhuang culture. [ABSTRACT FROM AUTHOR]

Highlights • Impact of the UAV camera tilting angle on the 3D cliff face reconstruction. • Because of occlusions, irrelevance of nadir pointing camera for sub-vertical cliffs. • Satisfying accuracy and texture for both 20°, 30° and 40° off-nadir imaging angles. • Other parameters impacting tiepoint detection in the reconstruction process. Abstract UAVs are relevant for monitoring cliff faces. In this study, several flights are performed with various imaging angles (nadir, 20°, 30° and 40° off-nadir) to assess the impact of the imaging angle on the 3D cliff face reconstruction. Occlusions issues arising with sub-vertical cliffs make nadir surveys nearly irrelevant. The results obtained with 20°, 30° and 40° off-nadir imaging angles are satisfactory regarding texture restitution and accuracy with respectively 5.5 cm, 5.9 cm and 4.9 cm of error, higher tilting angles yielding better reconstructions on sub-vertical or overhanging parts of the cliff. This article also investigates other parameters affecting tiepoint detection on the cliff face, as the effective overlap, the UAV-cliff face distance and the cliff face illumination. Guidelines are provided for UAV survey parameterization, aiming at capturing the whole cliff face with a good trade-off between distance to the cliff, flight height and spatial resolution of the photographs. [ABSTRACT FROM AUTHOR]