Unmanned Aerial Vehicle Photogrammetry Research Articles

UAV-Based Optical Granulometry as Tool for Detecting Changes in Structure of Flood Depositions

This paper presents a new non-invasive technique of granulometric analysis based on the fusion of two imaging techniques, Unmanned Aerial Vehicles (UAV)-based photogrammetry and optical digital granulometry. This newly proposed technique produces seamless coverage of a study site in order to analyze the granulometric properties of alluvium and observe its spatiotemporal changes. This proposed technique is tested by observing changes along the point bar of a mid-latitude mountain stream. UAV photogrammetry acquired at a low-level flight altitude (at a height of 8 m) is used to acquire ultra-high resolution orthoimages to build high-precision digital terrain models (DTMs). These orthoimages are covered by a regular virtual grid, and the granulometric properties of the grid fields are analyzed using the digital optical granulometric tool BaseGrain. This tested framework demonstrates the applicability of the proposed method for granulometric analysis, which yields accuracy comparable to that of traditional field optical granulometry. The seamless nature of this method further enables researchers to study the spatial distribution of granulometric properties across multiple study sites, as well as to analyze multitemporal changes using repeated imaging.

Comparison of low-altitude UAV photogrammetry with terrestrial laser scanning as data-source methods for terrain covered in low vegetation

This article juxtaposes results from an unmanned aerial vehicle (UAV) and a terrestrial laser scanning (TLS) survey conducted to determine land relief. The determination of terrain relief is a task that requires precision in order to, for example, map natural and anthropogenic uplifts and subsidences of the land surface. One of the problems encountered when using either method to determine relief is the impact of any vegetation covering the given site on the determination of the height of the site's surface. In the discussed case, the site was covered mostly in low vegetation (grass). In one part, it had been mowed, whereas in the other it was 30–40cm high. An attempt was made to filter point clouds in such a way as to leave only those points that represented the land surface and to eliminate those whose height was substantially affected by the surrounding vegetation. The reference land surface was determined from dense measurements obtained by means of a tacheometer and a rod-mounted reflector. This method ensures that the impact of vegetation is minimized. A comparison of the obtained accuracy levels, costs and effort related to each method leads to the conclusion that it is more efficient to use UAV than to use TLS for dense land relief modeling.

Integration between TLS and UAV photogrammetry techniques for forestry applications

Abstract: Forests are significant resources from an ecological, economic and social point of view. Their protection and management could greatly benefit from a complete knowledge of the shape and distribution of trees in forest stands. To this purpose, aerial surveys, especially through Airborne Laser Scanning (ALS), were carried out in the last years to acquire point clouds to be used in 3D models aimed at achieving an accurate description of tree crowns and terrain. However, airborne data acquisition is expensive and may provide poor results in case of dense foliage. Further, point cloud resolution is not very high, as models with a grid of 2-3 m are usually obtained. In order to implement more accurate 3D forest models, a feasible solution is the integration of point clouds obtained by aerial acquisition (ALS or photogrammetry) for the treetops and the terrain description, with information from terrestrial surveys. In this paper, we investigated the possible integration of point clouds obtained by Terrestrial Laser Scanner (TLS) with those collected by photogrammetric 3D models based on images captured by Unmanned Aerial Vehicle (UAV) in a test site located in northern Italy, with the aim of creating an accurate dataset of the forest site with high resolution and precision. The limits of ALS and TLS were bridged by aerial photogrammetry at low altitude (and vice versa). A 3D model of the study area was obtained with a resolution of 5 cm and a precision of 3 cm. Such model may be used in a wide range of applications in forestry studies, e.g., the reconstruction of 3D shapes of trees or the analysis of tree growth throught time. The implications of the use of such integrate approach as a support tool for decision-making in forest management are discussed.

Lightweight UAV digital elevation models and orthoimagery for environmental applications: data accuracy evaluation and potential for river flood risk modelling

ABSTRACTDigital elevation models (DEMs) generated from unmanned aerial vehicle (UAV) photogrammetry offer opportunities for on-demand DEM production in environmental modelling and flood risk prediction applications. The DEM and orthoimage accuracies that can be achieved using lightweight UAV on-board sensors only, are compared with cases where progressively higher numbers of Global Navigation Satellite System (GNSS) referenced ground targets are utilized. Unacceptably large 95% planimetric orthoimage errors of 5.22 m (root mean square error (RMSE) 3.27 m), and DEM 95% elevation errors of 5.03 m (RMSE 2.2 m) are observed when using the on-board positioning and orientation sensors only. Introducing GNSS ground control points (GCPs) in increasing numbers progressively and substantially improves data accuracy. Remarkably small xy orthoimage errors of 0.076 m (RMS) and DEM elevation errors of 0.08 m (RMS) are achieved using 1 GCP for every 2 ha of ground area and utilizing more GCPs produced more or less identical results. These accuracies compare very favourably with the best commercial airborne survey DEMs, suggesting strong potential for the application of lightweight UAV photogrammetric DEMs in local environmental modelling and flood risk prediction applications. The potential of these DEMS for flood prediction is subsequently assessed and demonstrated by comparison with published flood risk maps and flood depth data, and by cross-comparing the outputs of the UAV DEM flood model predictions.

Mapping hazardous mining-induced sinkhole subsidence using unmanned aerial vehicle (drone) photogrammetry

Accurate subsidence inventory data, based on an understanding of local topography, are a crucial first step toward reliable subsidence prediction and mapping future subsidence hazards. However, conventional, human-based methods of surveying and mapping subsidence suffer from data omissions and errors due to problems regarding accessibility, safety, and manual digitization. This study employed unmanned aerial vehicle photogrammetry to compile an accurate subsidence inventory map of abandoned mine areas. A Phantom 2 Vision+ drone was used, which is inexpensive yet appropriate for detailed topographic surveying of small-sized mine sites with a history of subsidence. An autonomous flight plan was designed, taking into account the extent of target mapping areas. A series of 29 aerial photographs were obtained within 2 min; digitally georeferenced orthoimage and digital terrain model (DTM) with 5 cm resolution could be obtained by processing with coordinate information of pre-installed ground control points (GCPs) within 30 min. sinkhole-type subsidence, including locational information, was identified from the geocoded high-resolution orthoimage and the DTM, and its area and volume were calculated to be 427 m2 and 2323 m3 (length 25 m, width 23 m, depth 9.1 m), respectively, from its modeled shape. Contour lines (10 cm interval), slope, and curvature were produced using the DTM. Validation using the GCP locations showed an error of approximately 14 cm in the generated DTM, which was considered acceptable for subsidence mapping purposes. The proposed approach enables accurate, rapid, low-cost, and safe surveying and mapping, which complements conventional surveying methods at sites of mining subsidence.

Kinematic analysis of sea cliff stability using UAV photogrammetry

ABSTRACTErosion and slope instability poses a significant hazard to communities and infrastructure located in coastal areas. We use point cloud and spectral data derived from close-range digital photogrammetry to perform a kinematic analysis of chalk sea cliffs located at Telscombe, UK. Our data were captured from an unmanned aerial vehicle (UAV) and cover a cliff face that is about 750 m long and ranges from 20 to 49 m in height. The resulting point clouds had an average density of 354 points m−2. The models fitted our ground control network within a standard error of 0.03 m. Structural features such as joints, bedding planes, and faults were manually mapped and are consistent with results from other studies that have been conducted using direct measurement in the field. These data were then used to assess differing modes of failure at the site. Our results indicate that wedge failure is by far the most likely mode of slope instability. A large wedge failure occurred at the site during the period of study supporting our analysis. Volumetric analysis of this failure through a comparison of sequential models indicates a failure volume of about 160 m3. Our results show that data capture through UAV photogrammetry can provide a useful basis for slope stability analysis over long sections of coast. This technology offers significant benefits in equipment costs and field time over existing methods.

Estimating Earthwork Volumes Through Use of Unmanned Aerial Systems

Unmanned aerial systems (UASs) and unmanned aerial vehicles (UAVs) have become increasingly attractive for numerous surveying applications in civil engineering, agriculture, and many other fields. The unmanned systems and vehicles are capable of performing photogrammetric data acquisition with equipped digital cameras that allows for converting images to highly precise, georeferenced three-dimensional models. However, more studies are needed to demonstrate practical applications of UAS systems and UAVs on construction sites. In this project, UAS systems and UAVs and digital photogrammetry technology are introduced to estimate the earthwork volume of a highway extension project. The georeferenced images were processed by the photogrammetry software, Pix4Dmapper, which is a tool for converting images into an accurate and applicable three-dimensional point cloud model. Progress models were created over the course of several weeks. The volume of earth was computed by comparing the point cloud of the progress models after model processing. To ensure reliability, the accuracy of the UAS and UAV photogrammetry was verified by comparison with conventional ground survey methods and the results from different flights. The project presents the feasibility and effectiveness of using UAS systems and UAVs in estimating earthwork volumes on the basis of the results of an accuracy test and the efficiency of the survey.

By Means of Unmanned Aerial Vehicle (UAV) -Based Photogrammetry, Observing, Analyzing and Reporting of the Big Construction Projects, Ethiopia Application

The method of map production by using UAV photogrammetry is widely-used in Turkey and World in recent years. With the developing technology, the capabilities of UAV platforms increase in parallel with the scale of projects, which are done by using UAVs, almost reaches to enough magnitude in order to compete with manned aircraft platforms. In the article, it has been discussed in observing, analyzing and reporting of cut and fill productions within the scope of 270km railway Project in Ethiopia. In the result of article, it has been evaluated that the maps required by large-scale construction projects can be produced by using UAVs within high accuracies and it has some advantages in time and cost.

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

We provide the first assessment of tropical peatland depth of burn (DoB) using structure from motion (SfM) photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV) system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB) of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR) data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs) show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE) respectively, compared to ground-based global navigation satellite system (GNSS) surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia) shows burn depths extending from close to zero to over 1 m, with a mean (±1σ) DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra). Our combustion heterogeneity analysis suggests the deepest burns, which extend to ~1.3 m, occur around tree roots. We use these DoB data within the Intergovernmental Panel on Climate Change (IPCC) default equation for fire emissions to estimate mean carbon emissions as 134 ± 29 t·C∙ha−1 for this peatland fire, which is in an area that had not had a recorded fire previously. This is amongst the highest per unit area fuel consumption anywhere in the world for landscape fires. Our approach provides significant uncertainty reductions in such emissions calculations via the reduction in DoB uncertainty, and by using the UAV SfM approach this is accomplished at a fraction of the cost of airborne LiDAR—albeit over limited sized areas at present. Deploying this approach at locations across Indonesia, sampling a variety of fire-affected landscapes, would provide new and important DoB statistics for producing optimized carbon and greenhouse gas (GHG) emissions estimates from peatland fires.

3D point cloud analysis for surface roughness measurement: application of UAV photogrammetry

This paper describes the application of close-range digital photogrammetry through Unmanned Aerial Vehicle (UAV) for rock discontinuity roughness determination. This was possible thanks to the creation of a georeferenced point cloud characterised by 3D information useful for rock mass study. In particular, UAV systems allows producing dense point clouds (with high spatial resolution), suitable to describe the rock surfaces and allowing the surveying of inaccessible outcrops. In fact, the occlusion phenomenon was minimized by means of different acquisition angles. In this context, the computation of the Joint Roughness Coefficient (JRC) was carried out picking several points within the cloud and obtaining rock profiles of the maximum asperity amplitude. Furthermore, we present in the manuscript a rapid and preliminary estimation of the whole rock slope roughness using the freeware CloudCompare code. A 3D roughness model was generated. The JRC results, both manually measured and automatically computed by the code, are comparable. The reliability of the values was confirmed by direct engineering-geological surveys where the surface roughness was calculated using the traditional method of visual comparison to Barton's reference roughness profiles. The paper aims to demonstrate how data derived from UAV processing are, nowadays, so dense and accurate to be able to provide adequate measurements of discontinuity roughness even transcending the problem of the JRC scale effect.

Identification of paleoearthquakes based on geomorphological evidence and their tectonic implications for the southern part of the active Anqiu–Juxian fault, eastern China

This study utilized an unmanned aerial vehicle (UAV) photogrammetry system to acquire orthoimages and generate a digital elevation model (DEM) covering the southern part of the Anqiu–Juxian fault for geomorphological analysis and paleoearthquake identification. Six offset gullies were identified and analyzed on the orthoimages. Our results indicate that at least three large and several moderate earthquakes have occurred along the fault zone. Knickpoints recognized from the DEM reveal several paleoearthquakes. An average Holocene horizontal slip rate of 2.86±0.35mmyr−1 was estimated from the offset gullies, which is consistent with previous results from field surveys. The tectonic evolution of this fault zone is most likely related to subduction of the Pacific plate under the Eurasian plate, which gave rise to the right-lateral strike-slip and thrust movement of the Tan-Lu fault zone. This study provided valuable information regarding fault activity and paleoearthquake occurrence along the Anqiu–Juxian fault zone during the Holocene and demonstrated the potential of using UAVs for studies involving tectonic geomorphology.

High Spatial Resolution Mapping of Dykes Using Unmanned Aerial Vehicle (UAV) Photogrammetry: New Insights On Emplacement Processes

High Spatial Resolution Mapping of Dykes Using Unmanned Aerial Vehicle (UAV) Photogrammetry: New Insights On Emplacement Processes

Effects of image orientation and ground control points distribution on unmanned aerial vehicle photogrammetry projects on a road cut slope

The morphology of road cut slopes, such as length and high slopes, is one of the most prevalent causes of landslides and terrain stability troubles. Digital elevation models (DEMs) and orthoimages are used for land management purposes. Two flights with different orientations with respect to the target surface were planned, and four photogrammetric projects were carried out during these flights to study the image orientation effects. Orthogonal images oriented to the cut slope with only sidelaps were compared to the classical vertical orientation, with sidelapping, endlapping, and both types of overlapping simultaneously. DEM and orthoimages obtained from the orthogonal project showed smaller errors than those obtained from the other three photogrammetric projects, with the first one being much easier to manage. One additional flight and six photogrammetric projects were used to establish an objective criterion to locate the three ground control points for georeferencing and rectification DEMs and orthoimages. All possible sources of errors were evaluated in the DEMs and orthoimages.

UAV vs classical aerial photogrammetry for archaeological studies

Excavations at Stavros, Chalandritsa, 20km south of Patras, Greece, have brought to light an extensive Late Bronze Age settlement, inhabited at least during the 13th and 12thcenturies B.C. The settlement covers an area of approx. 12 acres on top of a rocky hilltop, which offers an unobstructed supervision of the wider region. As highly accurate mapping and 3D reconstructions are fundamental for analyses and interpretations in archaeology, the specific area was used as a test area for a comparison between classical topographic survey, airphoto and Unmanned Aerial Vehicle (UAV) based photogrammetry. The settlement was mapped with traditional topographic surveying methods using tachymeter and Differential GNSS system. Digital photogrammetric techniques were applied on analogue airphotos to create (DSMs) and orthophotos from the archaeological site. Two independent low altitude aerial campaigns were carried out using two different UAVs. Computer vision techniques along with photogrammetric analysis techniques were used to perform bundle adjustment with ground control points (GCPs) collected with a differential GNSS receiver. 3D models were created from the imagery captured from the UAV campaigns. Ultra-high resolution orthophotos with a pixel size of 5cm and DSMs with respective spatial resolution were also created. The orthophotos were validated in terms of georeferencing accuracy and the DSMs were validated in terms of height accuracy. The accuracy of the UAV derived products reaches 99.6% compared to classical topographic measurements. Chalandritsa test site results provide strong evidence that 3D models created by UAV imagery can be accurate enough to perform precise measurements.

Unmanned Aerial Vehicle (UAV) photogrammetry produces accurate high-resolution orthophotos, point clouds and surface models for mapping wetlands

Unmanned Aerial Vehicle (UAV) photogrammetry has recently become a powerful tool that offers a viable alternative to traditional remote sensing systems, particularly for applications covering relatively small spatial extents. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool for the mapping of wetlands. A multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. The survey of the 100ha study area at the Kameelzynkraal farm, Gauteng Province, South Africa took about 2½ hours and the generation of the point cloud about 18 hours. Ground control points (GCPs) were positioned across the site to achieve geometrical precision and georeferencing accuracy. Structure from Motion (SfM) computer vision techniques were used to reconstruct the camera positions, terrain features and to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The results of the geometric accuracy of the data based on the 20 GCPs were 0.018m for the overall and 0.0025m for the vertical root mean squared error (RMSE). The results exceeded our expectations and provided valuable, rapid and accurate mapping of wetlands that can be used for wetland studies and thereby support and enhance associated decision making to secure our future.

Accuracy of Digital Surface Models and Orthophotos Derived from Unmanned Aerial Vehicle Photogrammetry

AbstractThis paper explores the influence of flight altitude, terrain morphology, and the number of ground control points (GCPs) on digital surface model (DSM) and orthoimage accuracies obtained with unmanned aerial vehicle (UAV) photogrammetry. For this study, 60 photogrammetric projects were carried out considering five terrain morphologies, four flight altitudes (i.e., 50, 80, 100, and 120 m), and three different numbers of GCPs (i.e., 3, 5, and 10). The UAV was a rotatory wing platform with eight motors, and the sensor was a nonmetric mirrorless reflex camera. The root-mean-square error (RMSE) was used to assess the accuracy of the DSM (Z component) and orthophotos (X, Y, and XY components RMSEX, RMSEY, and RMSEXY, respectively). The results show that RMSEX, RMSEY, and RMSEXY were not influenced by flight altitude or terrain morphology. For horizontal accuracy, differences between terrain morphologies were observed only when 5 or 10 GCPs were used, which were the best accuracies for the flattest morph...

BEACH VOLUME CHANGE USING UAV PHOTOGRAMMETRY SONGJUNG BEACH, KOREA

Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D) and beach profile (vertical 2D) on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV) to 3D map and beach volume change. UAV (Quadcopter) equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

BEACH VOLUME CHANGE USING UAV PHOTOGRAMMETRY SONGJUNG BEACH, KOREA

Abstract. Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D) and beach profile (vertical 2D) on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV) to 3D map and beach volume change. UAV (Quadcopter) equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

UAV photogrammetry for mapping vegetation in the low-Arctic

Plot-scale field measurements are necessary to monitor changes to tundra vegetation, which has a small stature and high spatial heterogeneity, while satellite remote sensing can be used to track coarser changes over larger regions. In this study, we explored the potential of unmanned aerial vehicle (UAV) photographic surveys to map low-Arctic vegetation at an intermediate scale. A multicopter was used to capture highly overlapping, subcentimetre photographs over a 2 ha site near Tuktoyaktuk, Northwest Territories. Images were processed into ultradense 3D point clouds and 1 cm resolution orthomosaics and vegetation height models using Structure-from-Motion (SfM) methods. Shrub vegetation heights measured on the ground were accurately represented using SfM point cloud data (r2 = 0.96, SE = 8 cm, n = 31) and a combination of spectral and height predictor variables yielded an 11-class classification with 82% overall accuracy. Differencing repeat UAV surveys before and after manually trimming shrub patches showed that vegetation height decreases in trimmed areas (− 6.5 cm, SD = 21 cm). Based on these findings, we conclude that UAV photogrammetry provides a promising, cost-efficient method for high-resolution mapping and monitoring of tundra vegetation that can be used to bridge the gap between plot and satellite remote sensing measurements.

INTEGRATED PROCESSING OF HIGH RESOLUTION TOPOGRAPHIC DATA FOR SOIL EROSION ASSESSMENT CONSIDERING DATA ACQUISITION SCHEMES AND SURFACE PROPERTIES

Soil erosion is a decisive earth surface process strongly influencing the fertility of arable land. Several options exist to detect soil erosion at the scale of large field plots (here 600 m²), which comprise different advantages and disadvantages depending on the applied method. In this study, the benefits of unmanned aerial vehicle (UAV) photogrammetry and terrestrial laser scanning (TLS) are exploited to quantify soil surface changes. Beforehand data combination, TLS data is co-registered to the DEMs generated with UAV photogrammetry. TLS data is used to detect global as well as local errors in the DEMs calculated from UAV images. Additionally, TLS data is considered for vegetation filtering. Complimentary, DEMs from UAV photogrammetry are utilised to detect systematic TLS errors and to further filter TLS point clouds in regard to unfavourable scan geometry (i.e. incidence angle and footprint) on gentle hillslopes. In addition, surface roughness is integrated as an important parameter to evaluate TLS point reliability because of the increasing footprints and thus area of signal reflection with increasing distance to the scanning device. The developed fusion tool allows for the estimation of reliable data points from each data source, considering the data acquisition geometry and surface properties, to finally merge both data sets into a single soil surface model. Data fusion is performed for three different field campaigns at a Mediterranean field plot. Successive DEM evaluation reveals continuous decrease of soil surface roughness, reappearance of former wheel tracks and local soil particle relocation patterns.