Generation of Highly Accurate Digital Elevation Models with Unmanned Aerial Vehicles

Reshetyuk, Yuriy; Mårtensson, Stig-Göran

doi:10.1111/phor.12143

Cited by 44 publications

(27 citation statements)

References 21 publications

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“…()). A similar GCP configuration was also suggested by Reshetyuk and Mårtensson (). Such establishment of a GCP network is a trade‐off between fieldwork time and optimal accuracy.…”

Section: Methodsmentioning

confidence: 99%

Automated co‐registration and calibration in SfM photogrammetry for landslide change detection

Peppa

Mills

Moore

et al. 2018

Earth Surf Processes Landf

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Landslides represent hazardous phenomena, often with significant implications. Monitoring landslides with time‐series surface observations can indicate surface failure. Unmanned aerial vehicles (UAVs) employing compact digital cameras, in conjunction with structure‐from‐motion (SfM) and multi‐view stereo (MVS) image processing approaches, have become commonplace in the geoscience research community. These methods offer relatively low‐cost, flexible solutions for many geomorphological monitoring applications. However, conventionally ground control points (GCPs) are required for registration purposes, the provision of which is often expensive, difficult or even impracticable in hazardous and inaccessible terrain. In an attempt to overcome the reliance on GCPs, this paper reports research that has developed a morphology‐based strategy to co‐register multi‐temporal UAV‐derived products. It applies the attribute of curvature in combination with the scale‐invariant feature transform algorithm, to generate time‐invariant curvature features, which serve as pseudo‐GCPs. Openness, a surface morphological digital elevation model derivative, is applied to identify relatively stable ground regions from which pseudo‐GCPs are selected. A sensitivity threshold quantifies the minimum detectable change alongside unresolved biases and misalignment errors. The approach is evaluated at two study sites in the UK, first at Sandford with artificially induced surface change, and second at an active landslide at Hollin Hill, with multi‐epoch SfM‐MVS products derived from a consumer‐grade UAV. Elevation changes and annual displacement rates at dm‐level are estimated, with optimal results achieved over winter periods. The morphology‐based co‐registration strategy resulted in relative error ratios (i.e. mean error divided by average flying height) in the range 1:800–2500, comparable with those reported by similar studies conducted with UAVs augmented with real time kinematic (RTK)‐Global Navigation Satellite Systems. Analysis demonstrates the potential of the morphology‐based strategy for a semi‐automatic, and practical co‐registration approach to quantify surface motion. This can ultimately complement geotechnical and geophysical investigations and support the understanding of landslide behaviour, model prediction and construction of measures for mitigating risks. © 2018 John Wiley & Sons, Ltd.

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“…()). A similar GCP configuration was also suggested by Reshetyuk and Mårtensson (). Such establishment of a GCP network is a trade‐off between fieldwork time and optimal accuracy.…”

Section: Methodsmentioning

confidence: 99%

Automated co‐registration and calibration in SfM photogrammetry for landslide change detection

Peppa

Mills

Moore

et al. 2018

Earth Surf Processes Landf

View full text Add to dashboard Cite

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“…SfM is a useful range viewing technique that refers to the process of estimating 3D geometries from 2D images. This methodology has become increasingly popular in a wide range of geologic and geomorphic investigations and standoff distances in the past half-decade (e.g., Westoby et al 2012;Niethammer et al 2010;Johnson et al 2014;Bemis et al 2014;Micheletti et al 2015;Nouwakpo et al 2015;Reshetyuk and Martensson 2016;Carrivick et al 2016;Piras et al 2017) and provides valuable data to link with other geological and geophysical techniques. The Agisoft Photoscan Ò software package is a powerful SfM tool that uses photogrammetric algorithms to calculate distances between points in overlapping photos to create high-resolution 3D models from 2D images.…”

Section: Structure-from-motionmentioning

confidence: 99%

Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

Schultz-Fellenz

Coppersmith²,

Sussman

et al. 2017

Pure Appl. Geophys.

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Abstract-Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy's Source Physics Experiments (SPE-5) series. The highresolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models were created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within *40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90-130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan Ò in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixelsize digital elevation model (DEM) for the test table grid region. This provided the B3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.

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“…SfM is the most widely used method nowadays for common UAV RGB photographs; it has been proved on several occasions that it enables the generation of 3D surface models with high accuracy. As an example, Reshetyuk and Mårtensson () demonstrate that it is possible to create a DEM with a height uncertainty of less than 20 mm for flat terrain from UAV images acquired from a flying height of up to 160 m using only five GCPs. It is also well documented that SfM does not work well for DEM generation with specific conditions such as reflective or very low‐textured surfaces such as water, sand and snow (Mancini et al., ; Gómez‐Gutiérrez et al., ).…”

Section: Discussionmentioning

confidence: 99%

“…Several studies confirm that natural surfaces can be very accurately reconstructed using UAV images and SfM methodology (Eltner and Schneider, ; Uysal et al., ; Reshetyuk and Mårtensson, ). On the other hand, there are some specific issues to be considered when applying SfM methodology that have also been reported in several articles.…”

Section: Introductionmentioning

confidence: 86%

Assessing multitemporal water‐level changes with uav‐based photogrammetry

Kohv

Sepp

Vammus

2017

The Photogrammetric Record

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Unmanned aerial vehicle (UAV) images and structure-from-motion (SfM) methodology allow very high resolution surface reconstruction. This fairly low-cost and time-saving method is used for northern bog hydrology characterisation. The primary interest of this study lies in seasonally changing bog pool water levels. The study site is located in a potential conflict zone where water extraction from an underground oil shale mine threatens protected wetlands. The study involves two test areas that were surveyed three times, allowing spatio-temporal quantification of seasonal changes of the bog surface. Aerial lidar data and manual measurements were used to assess the quality of SfM surfaces and discrepancies between the different methods were analysed. Overall, there is a good fit between the methods used, validating the use of SfM methodology in a natural wetland environment. This study demonstrates that the nearby mine is influencing the seasonal water-level fluctuations of the protected wetland.

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Generation of Highly Accurate Digital Elevation Models with Unmanned Aerial Vehicles

Cited by 44 publications

References 21 publications

Automated co‐registration and calibration in SfM photogrammetry for landslide change detection

Automated co‐registration and calibration in SfM photogrammetry for landslide change detection

Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

Assessing multitemporal water‐level changes with uav‐based photogrammetry

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