UAV Survey Research Articles

Identification of potential landslides in Baihetan Dam area before the impoundment by combining InSAR and UAV survey

Identification of potential landslides in Baihetan Dam area before the impoundment by combining InSAR and UAV survey

Mapping snow depth and spatial variability using SFM photogrammetry of UAV images over rugged mountainous regions of the Western Himalaya

Accurate snow depth observations are one of the most important inputs in the process of avalanche hazard estimation, forecasting, and mitigation. This study presents the high-resolution snow depth mapping of avalanche-prone regions of the Manali–Dhundi area, Himachal Pradesh (HP), India, using, repeated UAV Photogrammetric surveys. The images captured by an RGB camera mounted on a fixed-wing UAV (e-Bee X) were used to generate the high-resolution Digital Surface Model (DSM) and Orthophotos of the study area. Mapping of snow depth of the study area is crucial for avalanche hazard assessment and safe movement of the personnel and vehicles passing through the highways in this area during winters. A total of 12 km2 area covering six major avalanche sites was surveyed. A snow depth map was generated by differencing co-registered snow-covered DSM and bare surface DSM. UAV-derived snow depth values have been validated with the point snow depth measurements of Wireless Sensor Networks (WSN), manual observation station, and snow depth around a structure of known height in the survey area. The UAV-retrieved snow depth values were found in good correlation with field-measured snow depth (R = 0.95). The maximum and minimum observed snow depth values at different locations on open slopes and flat areas were 1.62 m and 0.79 m. The estimated Mean Error (ME) and RMSE based on these measured values were found 0.15 and 0.21 m, respectively. The study reveals that the snow depth map generated from the UAV survey provides reliable estimates of snow depth values for flat areas and open slopes but the method is not suitable for forested areas. The study also infers that the statistical measures (i.e., µ, σ, RMSE, etc.) derived from the complete survey dataset without considering topographic factors and features of the region will not provide realistic estimates of snow depth and its accuracy. The study suggests that regular monitoring (before and after every snow storm) of the snow depth using a UAV-based method is quick, cost-effective, and provides accurate snow conditions for operational use and planning in snow-bound regions.

An HBIM Methodology for the Accurate and Georeferenced Reconstruction of Urban Contexts Surveyed by UAV: The Case of the Castle of Charles V

The potentialities of the use of the UAV survey as a base for the generation of the context mesh are illustrated through the experiments on the case study, the Crotone Fortress, proposing a systematic general methodology and two procedural workflows for the importation of the triangulated model, maintaining its real geographical coordinates, in the Autodesk Revit environment through a Dynamo Visual Programming script [VPL]. First, the texturisation of the mesh of the urban context was experimented with, using the real-sized photogrammetric orthoimage as Revit material; therefore, the reproduction of the discretised detailed areas of the urban context was tested. They were imported via Dynamo by reading the coordinates of the vertices of every single face that constitutes the triangulated model and associating to each of them the corresponding real colorimetric data. Starting from the georeferenced context of the photogrammetric mesh, nine federated BIM models were produced: the general context models, the detailed models and the architectural model of the fortress.

Spatial distribution assessment of invasive alien species Amorpha fruticosa L. by UAV-based on remote sensing in the Special Nature Reserve Obedska Bara, Serbia.

The Obedska Bara Special Nature Reserve is one of the oldest protected areas in the world, also enlisted as an Important Bird Area, Ramsar and UNESCO world heritage site. False indigo bush (Amorpha fruticosa L.) represents an invasive alien species which is significantly deteriorating the biodiversity of the Obedska Bara Special Nature Reserve in Serbia. Mapping of A. fruticosa, using an unmanned aerial vehicle and GIS tools, showed that in meadows, pastures, ponds and wetland areas, A. fruticosa covered 85ha or 11% of the area. However, coverage was uneven, and the most overgrown areas were some meadows (up to 35%), while flooded areas and areas where human impact is significant, as on pastures, were not so affected (1-3%). The most susceptible parts were forest edges. Active management practices, such as cattle grazing and topsoil tarping, and occasional moving, gave positive effects in A. fruticosa, but also other invasive terrestrial plant species spreading control in the reserve. This has also been confirmed by the UAV survey and mapping, which has proven to be an effective method for A. fruticosa monitoring over large areas.

ГЕОДЕЗІЯ, КАРТОГРАФІЯ І АЕРОФОТОЗНІМАННЯ

The aim of the work is to investigate the accuracy of the DEM of nearshore areas using UAV material. One of the important issues in hydrological flood modelling is the high accuracy of the DEM. In the case of a complex relief type, which is associated with meandering riverbeds, it is proposed to use UAV surveys to create a DEM. Hydrological modelling involves the following main steps: creation of high precision DEMs, determination of Manning coefficients to account for the influence of the underlying surface and determination of water level changes based on the water level graph derived from observations at hydrometeorological stations. This research presents the construction of a high-precision DEM, based on a UAV survey. For high-precision modeling, the fundamental issue is the consideration of vegetation in the nearshore areas and the choice of the optimal time period for the survey. The aim of the study is to develop a methodology for the construction of a high-precision DEM from UAV data, investigate the possibilities of eliminating the influence of vegetation on point marks using software methods, determine planned channel shifts and compare the accuracy of DEM construction for surveys conducted in June 2017 and in November 2021. The section at the transition from the mountainous to marshy-hilly part of the Dniester River near the town of Stary Sambir, with complex morphometric and hydrological characteristics of the channel and banks at the site of the complex meandering of the river in a rugged ravine area was the study object of this work. Results. It was found that for 4 years between two surveys, the planned displacements of some points are up to 25-31 meters. A priori estimation of coordinates determination by points from the GNSS-receiver was carried out, the accuracy of point coordinates determination is 2-3 cm. The a priori estimate of the accuracy of determining the coordinates of points from the input survey data is: for plan coordinates - 4-6 cm for two survey periods, the error in determining the marks of points for different values of the baseline - 21-31 cm. It has been established, that the program methods of accounting of influence of high vegetation do not give the possibility of its full accounting, the average square error, in places of such vegetation makes 0,64 m. Therefore, it is necessary to carry out UAV survey in the leafless period of the year, early spring or late autumn. Scientific novelty consists in the study of the possibility of constructing a high-precision DEM for different types of vegetation from materials obtained from UAVs. The results can be used for hydrological modeling of river channels with complex hydromorphological characteristics.

INTEGRATED MINING IMPACT MONITORING (EU-PROJECT I2MON) FOR OPEN-PIT AND UNDERGROUND MINES

Abstract. Monitoring mining impact has become increasingly important as the awareness of safety and environmental protection is rising. Our project Integrated Mining Impact Monitoring (i2Mon), funded by European Commission – Research Fund for Coal and Steel, intends to monitor the mining-induced impact, in particular, ground movement. The monitoring system comprises terrestrial measurement and remote sensing: levelling, GPS, LiDAR scanning, UAV survey, and SAR interferometry. The aim is to launch an interactive GIS-based platform as an early warning and decision making service for mining industry. This study has developed a scheme based on advanced SAR interferometry to monitor the ground movement over an extensive area at millimetre level. The first test site is a deactivated open-pit mine in Cottbus, Germany owned by Lausitz Energie Bergbau AG. The whole area was reclaimed into a post-mining lake and must be monitored for the safety. The second test site is located in Poland, where the underground mining operated by POLSKA GRUPA GÓRNICZA began in June 2021. We have monitored the in-situ ground movement carefully as part of the influenced area covers the human settlement. The ground movement of our test sites was analysed from Sentinel-1 images. The crucial parameters include stepwise movement series, instantaneous velocities and accelerations, and significance index. In addition, six corner reflectors along with sensors like GPS were installed across the region in Cottbus. They were observed in the Sentinel-1 series and the GPS readings will be used for validation. Finally, all the data will be integrated into DMT’s platform – SAFEGUARD.

A Framework for Survey Planning Using Portable Unmanned Aerial Vehicles (pUAVs) in Coastal Hydro-Environment

Recently, remote sensing using survey-grade UAVs has been gaining tremendous momentum in applications for the coastal hydro-environment. UAV-based remote sensing provides high spatial and temporal resolutions and flexible operational availability compared to other means, such as satellite imagery or point-based in situ measurements. As strict requirements and government regulations are imposed for every UAV survey, detailed survey planning is essential to ensure safe operations and seamless coordination with other activities. This study established a comprehensive framework for the planning of efficient UAV deployments in coastal areas, which was based on recent on-site survey experiences with a portable unmanned aerial vehicle (pUAV) that was carrying a heavyweight spectral sensor. The framework was classified into three main categories: (i) pre-survey considerations (i.e., administrative preparation and UAV airframe details); (ii) execution strategies (i.e., parameters and contingency planning); and (iii) environmental effects (i.e., weather and marine conditions). The implementation and verification of the framework were performed using a UAV–airborne spectral sensing exercise for water quality monitoring in Singapore. The encountered challenges and the mitigation practices that were developed from the actual field experiences were integrated into the framework to advance the ease of UAV deployment for coastal monitoring and improve the acquisition process of high-quality remote sensing images.

Evaluation of connectivity indices applied to a Mediterranean agricultural catchment

Connectivity analysis has proved a very valuable approach in understanding runoff and sediment fluxes in catchments. Many analyses use Connectivity Indices to model the patterns, but various versions of the Index have been developed. This paper tests the effects of these variants of the Index as applied to an agricultural-terraced catchment in the semi-arid Mediterranean region where occurrence of connectivity is relatively well documented to validate the modelling. This paper compares three versions of the Connectivity Index that use vegetation/land use (C), topography (RI) and roughness (n) as the weighting factors. Two different slope algorithms are also tested. The weightings are derived from a UAV (drone) survey, with simultaneous ground field mapping. The UAV imagery is found to provide a good, high resolution basis for determining detailed topography and vegetation cover. The slope limit present in some modelling is found to be unsuitable in this landscape where steep terrace embankments that are vegetated in places, and also partially vegetated uplands, occur. Subsequent modelling removed the slope limit. The major patterns of flow produced are similar between the models and are largely related to the overall topography and major drainage lines but considerably modified by the terracing. The model outcomes differ in detail, with the C factor model, incorporating vegetation, coming nearer to the field situation. The main deficiency in all the indices is the weakness in modelling ponding and sedimentation created by the terraces, and therefore the disconnectivity in the landscape. Comparison with field data confirms the variable connectivity in rainstorms, the effects of features such as tracks, and the effect of management actions. Evidence from field mapping during the last two decades indicates that the models probably represent the maximum possible functional connectivity.

HOLOGRAPHIC VISUALIZATION AND MANAGEMENT OF BIG POINT CLOUD

Abstract. The work aims to present and validate the workflow from the 3D survey to the visualization of cultural heritage objects using the innovative Euclideon Hologram Table©. Three case studies surveyed with three different systems and at three different scales have been selected: Santa Maria delle Grazie in Milan (terrestrial laser scanner for an architecturalscale), the village of Ghesc in the Ossola valley (UAV survey for an environmental scale) and the cuneiform clay tablet number 727 (structured light system for a detailscale). The whole process of transforming the 3D point/mesh model to hologram was verified, analysing the file formats, technical performance and specifications, file dimensions manageable, and details viewable. The first test shows great potentiality, becausethe hologram exploring is impressively fluid even when zooming to view a higher detail level, despite the high number of points/polygons. The power and performance of the point cloud 3D rendering engine result impressive. Nonetheless,different aspects need further research, from point cloud visualization quality to enhancing 3D model interaction.

Assessment of the landslide process intensity on the bank of the Kuybyshev Reservoir using instrumental methods

The aim of the work was to survey and monitor dangerous exogeodynamic processes on the shoreline of the Kuibyshev reservoir. Field instrumental studies were used as the main method, including topo-geodetic survey of key morphological elements of the slope with ground control points, video and photo recording of the processes. Since 2019, unmanned aerial vehicle surveys have been chosen as the main method of research. The paper presents the results of long-term studies of the local landslide near Tetyushi, Republic of Tatarstan. As a result of 2003-2006 situational plans processing and results of UAV survey in 2019 quantitative data on the intensity of slope processes in the mass landslide were obtained.

VALIDATION OF A UAV-DERIVED POINT CLOUD BY SEMANTIC CLASSIFICATION AND COMPARISON WITH TLS DATA

Abstract. Recent years showed a gradual transition from terrestrial to aerial survey thanks to the development of UAV and sensors for it. Many sectors benefited by this change among which geological one; drones are flexible, cost-efficient and can support outcrops surveying in many difficult situations such as inaccessible steep and high rock faces. The experiences acquired in terrestrial survey, with total stations, GNSS or terrestrial laser scanner (TLS), are not yet completely transferred to UAV acquisition. Hence, quality comparisons are still needed. The present paper is framed in this perspective aiming to evaluate the quality of the point clouds generated by an UAV in a geological context; data analysis was conducted comparing the UAV product with the homologous acquired with a TLS system. Exploiting modern semantic classification, based on eigenfeatures and support vector machine (SVM), the two point clouds were compared in terms of density and mutual distance. The UAV survey proves its usefulness in this situation with a uniform density distribution in the whole area and producing a point cloud with a quality comparable with the more traditional TLS systems.

Comparison of Flight Height Controlled UAV and Ground Vector Magnetometer Survey Data Covering an Urban Landfill

An autonomous UAV-mounted 3-axis fluxgate vector magnetometer (FVM) was flown over a Golden, Colorado landfill to test map buried ferromagnetic objects and infrastructure. The flights test terrain following flight control software using active GNSS positioning over a fixed 1-meter (m) resolution LiDAR control surface, at slung sensor clearances that approach ground survey sensor heights. The FVM was first walked over the landfill with the sensor at a constant 2 m above the surface, to provide a high-resolution ground survey dataset for comparison. Both the UAV and ground FVM data are scalar calibrated on the ground through a full sphere to return error corrected and 360⁰ maneuver compensated total magnetic intensity (TMI). The comparison also includes UAV downward and ground survey upward continuation filtered (DCF and UCF) TMI respectively, to put the two surveys on approximately the same levels, providing two inverse-distance-magnetic-source viewpoints for both surveys, one at ground level and one at UAV level. The UAV survey DCF results indicate that low level flights might be considered as a replacement for coarser reconnaissance ground TMI surveys in some mapping situations. Lastly, the ground and UAV survey calibration data statistics are reviewed, and the FVM survey TMI images are compared with each other. These in turn, are compared with a highresolution alkali-vapor scalar magnetometer (AVM) benchmark TMI survey, walked on the same lines as the FVM. The AVM provides a reference standard to compare with both FVM surveys.

Rapid characterisation of landslide heterogeneity using unsupervised classification of electrical resistivity and seismic refraction surveys

The characterisation of the subsurface of a landslide is a critical step in developing ground models that inform planned mitigation measures, remediation works or future early-warning of instability. When a landslide failure may be imminent, the time pressures on producing such models may be great. Geoelectrical and seismic geophysical surveys are able to rapidly acquire volumetric data across large areas of the subsurface at the slope-scale. However, analysis of the individual model derived from each survey is typically undertaken in isolation, and a robust, accurate interpretation is highly dependent on the experience and skills of the operator. We demonstrate a machine learning process for constructing a rapid reconnaissance ground model, by integrating several sources of geophysical data in to a single ground model in a rapid and objective manner. Firstly, we use topographic data acquired by a UAV survey to co-locate three geophysical surveys of the Hollin Hill Landslide Observatory in the UK. The data are inverted using a joint 2D mesh, resulting in a set of co-located models of resistivity, P-wave velocity and S-wave velocity. Secondly, we analyse the relationships and trends present between the variables for each point in the mesh (resistivity, P-wave velocity, S-wave velocity, depth) to identify correlations. Thirdly, we use a Gaussian Mixture Model (GMM), a form of unsupervised machine learning, to classify the geophysical data into cluster groups with similar ranges and trends in measurements. The resulting model created from probabilistically assigning each subsurface point to a cluster group characterises the heterogeneity of landslide materials based on their geophysical properties, identifying the major subsurface discontinuities at the site. Finally, we compare the results of the cluster groups to intrusive borehole data, which show good agreement with the spatial variations in lithology. We demonstrate the applicability of integrated geophysical surveys coupled with simple unsupervised machine learning for producing rapid reconnaissance ground models in time-critical situations with minimal prior knowledge about the subsurface.

Improving the efficiency and accuracy of evaluating aridland riparian habitat restoration using unmanned aerial vehicles

AbstractUnmanned Aerial Vehicles (UAVs) offer new opportunities for accurate, repeatable vegetation assessments, which are needed to adaptively manage restored habitat. We used UAVs, ground surveys, and satellite imagery to evaluate vegetation metrics for three riparian restoration sites along the Colorado River in Mexico and we compared the data accuracy and efficiency (cost and time requirements) between the three methods. We used an off‐the‐shelf UAV coupled with a multispectral sensor to determine Normalized Difference Vegetation Index (NDVI) and vegetation cover. We were unable to accurately classify vegetation by individual species, but by grouping riparian species of interest (cottonwood‐willow, mesquite, shrubs), we achieved high overall model accuracies of 87–96% across sites (Kappa = 0.82–0.95). Producer’s and user’s accuracies were moderate to high for target vegetation classes (69–100%). UAV and ground‐survey vegetation percent cover differed due to differences in methodologies (UAVs measure aerial cover; ground surveys measure foliar cover) and sources of error for each method. Correlations between UAV and ground survey vegetation cover were moderate (rs(90) = 0.24–0.58, p < 0.05). UAV NDVI (0.50–0.61) was significantly higher than Landsat NDVI (0.40–0.45) for all sites (p < 0.0001), likely due to presence of shadows with high NDVI values in UAV imagery. UAV NDVI, Landsat NDVI and UAV total vegetation cover were strongly correlated (rs(90) = 0.72–0.85, p < 0.05). UAV surveys were more labor‐ and cost‐ intensive than ground surveys in the first year, but were slightly less so in the second year. We conclude that UAVs can provide efficient, accurate assessments of riparian vegetation, which can be used in restoration site management. Due to UAV limitations to assess vegetation in a multi‐layered canopy and inability to classify individual riparian species with similar spectral signals, we recommend a combined approach of UAV and ground surveys.

From UAV survey to 3D printing, geomatics techniques for the enhancement of small village Cultural Heritage

Italy is rich in cultural heritage villages and places of interest. This work illustrates the methodology utilized by the Geomatics Laboratory (DICEAM of the Mediterranean University of Reggio Calabria) to create a archaeological structures’ 3D model. 3D modeling is based on the utilization of imaging techniques, such as computer vision and digital photogrammetry. The outcomes obtained determine the value of the technique used in the field of cultural heritage to create a digital models and to replicate them through 3d printing. Furthermore, in the renewed interest in the context of the studies of ancient villages, the implementation of open GIS represents a new method to amplify the number of visitors to the villages despite concerns about returns on investments. In fact, the use of 3D acquisition and modeling tools to enhance the Cultural Heritage represents one of the study’s areas in quickly development in the near future.

The use of image and laser scanner survey archives for cultural heritage 3D modelling and change analysis

Cultural heritage studies often require the analysis of buildings that have undergone several changes and alterations during their lifetime. This often implies the loss of architectural elements or the construction of new elements, which both change the characteristics of the former buildings. The recovery of lost elements or structures through virtual reconstruction is of paramount importance in both scientific and cultural applications. Novel procedures in surveying and photogrammetric processing including historical photogrammetry and historical terrestrial laser scanning offer powerful tools that enable the extraction of geometric information from historical documentation such as archival images. This paper presents the integration of a metric 3D model with information present in archival surveys of lost architectural volumes. The methodology implies the availability of historical plans representing the survey object at scales consistent with UAV surveys and featuring shared elements. The methodology used to frame these plans in the reference system of the UAV survey for an open source GIS environment is also described as well as the accuracy checks. Finally, the procedure followed for the virtual reconstruction of the Fortezza in a BIM environment, which produced a model derived from the integration of historic and current data, is described.

Late-Holocene evolution of the Northern Bay of Cádiz from geomorphological, stratigraphic and archaeological data

The present paper deals with the historical evolution of the northern Bay of Cádiz (SW Spain) between the last eustatic maximum (6.5 ka BP) and the present day, by means of a series of independent proxies. The zone is constituted by the tidal estuary of the Guadalete River, filled with saltmarsh sediments during the late Holocene, due to the sheltering of the zone by a confining outer sandy barrier. The northern border of the Bay records an urban settlement of Phoenician Age (first millennium BC), Doña Blanca. A detailed survey was made in the contact between the Phoenician city and the saltmarshes in order to detect other possible urban structures related to the morphological and sedimentary evolution of this environment during historical times. Two campaigns with GPR Stream-X array were carried out as well as aerial imaging and topographic survey with UAV. In parallel, a total of 8 boreholes were made in different parts of the saltmarshes, including radiocarbon dating of selected samples for estimating sedimentation rates in the saltmarshes. Results obtained by georadar prospection and UAV survey revealed the presence of a second urban settlement on the marginal sedimentary plain, very probably installed upon a sandy fluvial island of the Guadelete River. The urban remains, of Punic Age, are partly covered by clay sediments due to the subsequent evolution of these saltmarshes, where sedimentation rates of up to nearly 2.4 mm/yr have been estimated for environments close to fluvial and/or tidal channels and hence more affected by sediment aggradation during flooding episodes. In recent times, river regulation by dams and the artificial desiccation and cropping of the saltmarshes have interrupted the natural trend of the area towards sedimentary silting up.

Modeling and Simulation of Very High Spatial Resolution UXOs and Landmines in a Hyperspectral Scene for UAV Survey

This paper presents methods for the modeling and simulation of explosive target placement in terrain spectral images (i.e., real hyperspectral 90-channel VNIR data), considering unexploded ordnances, landmines, and improvised explosive devices. The models used for landmine detection operate at sub-pixel levels. The presented research uses very fine spatial resolutions, 0.945 × 0.945 mm for targets and 1.868 × 1.868 cm for the scene, where the number of target pixels ranges from 52 to 116. While previous research has used the mean spectral value of the target, it is omitted in this paper. The model considers the probability of detection and its confidence intervals, which are derived and used in the analysis of the considered explosive targets. The detection results are better when decreased target endmembers are used to match the scene resolution, rather than using endmembers at the full resolution of the target. Unmanned aerial vehicles, as carriers of snapshot hyperspectral cameras, enable flexible target resolution selection and good area coverage.

Study on Extraction of Landslide Information Based on UAV Survey

Traditional analysis of landslide evolution discipline requires particular on-site investigation, which not only consumes a lot of manpower and material resources, but is also very inefficient. With the development of small drone aerial photography technology, a method based on the whole area landslide measurement becomes possible. This paper uses the rapid development of digital photogrammetry technology in recent years to monitor the surface deformation of the Qinyu landslide, and conducts an in-depth study of its evolution. The results show that the evolution of the Qinyu landslide is inherited and different in time and space. The reconstruction of the three-dimensional model greatly simplifies the traditional on-site investigation, and it also provides new methods and ideas for landslide monitoring.

Modelling sediment transport in space in a watershed based on topographic change detection by UAV survey

Modelling sediment transport in space in a watershed based on topographic change detection by UAV survey