Testing Accuracy and Repeatability of UAV Blocks Oriented with GNSS-Supported Aerial Triangulation

Benassi, Francesco; Dall’Asta, E.; Diotri, Fabrizio; Forlani, G.; Cella, Umberto Morra di; Roncella, R.; Santise, M.

doi:10.3390/rs9020172

Cited by 160 publications

(189 citation statements)

References 45 publications

Supporting

Mentioning

145

Contrasting

Order By: Relevance

“…We performed extensive validation of the underlying SfM-derived terrain models used in this work using 678 ground points surveyed in the field (see [19] for details), and found no evidence of such distortion. As such, our experience with the SfM workflow for terrain modeling is in line with recent authors (e.g., [30,31]) who reported satisfactory vertical accuracies without the need for supplementary mitigation.…”

Section: Pre-processingsupporting

confidence: 71%

A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles

et al. 2017

View full text Add to dashboard Cite

Groundwater level (GWL) and depth to water (DTW) are related metrics aimed at characterizing groundwater-table positions in peatlands, and two of the most common variables collected by researchers working in these ecosystems. While well-established field techniques exist for measuring GWL and DTW, they are generally difficult to scale. In this study, we present a novel workflow for mapping groundwater using orthophotography and photogrammetric point clouds acquired from unmanned aerial vehicles. Our approach takes advantage of the fact that pockets of surface water are normally abundant in peatlands, which we assume to be reflective of GWL in these porous, gently sloping environments. By first classifying surface water and then extracting a sample of water elevations, we can generate continuous models of GWL through interpolation. Estimates of DTW can then be obtained through additional efforts to characterize terrain. We demonstrate our methodology across a complex, 61-ha treed bog in northern Alberta, Canada. An independent accuracy assessment using 31 temporally coincident water-well measurements revealed accuracies (root mean square error) in the 20-cm range, though errors were concentrated in small upland pockets in the study area, and areas of dense tree covers. Model estimates in the open peatland areas were considerably better.

show abstract

Section: Pre-processingsupporting

confidence: 71%

A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Recent simulations [35,36] suggest that block deformations are effectively kept in check by AAT. Previous empirical evidence [37][38][39][40] suggest that the traditional control through GCP is still the safest and most accurate way to georeference a UAV photogrammetric block. As far as DSM generation by AAT is concerned, an elevation root mean square error (RMSE) of about 9 cm was reported on 180 checkpoints [40], versus 3 cm by georeferencing with GCP.…”

Section: Gnss-assisted Block Georeferencing and Controlmentioning

confidence: 99%

“…Following a previous study by Benassi et al [39], the objective of this paper is to investigate a further step of the photogrammetric workflow in UAV blocks oriented by AAT, i.e., the repeatability and the accuracy of DSM generation. In most cases, the main survey product of an UAV flight is the DSM.…”

Section: Paper Motivations and Objectivesmentioning

confidence: 99%

“…On the other hand, only the diagonal entries of the variance-covariance matrix of the projection center coordinates are supplied by GNSS data processing, if any. As shown by Benassi et al [39], the precision assigned to camera station coordinates in the Helmert transformation or in the BBA by three widely used software packages affects the elevation accuracy of checkpoints in different ways.…”

Section: Paper Motivations and Objectivesmentioning

confidence: 99%

See 1 more Smart Citation

Quality Assessment of DSMs Produced from UAV Flights Georeferenced with On-Board RTK Positioning

et al. 2018

Self Cite

View full text Add to dashboard Cite

High-resolution Digital Surface Models (DSMs) from unmanned aerial vehicles (UAVs) imagery with accuracy better than 10 cm open new possibilities in geosciences and engineering. The accuracy of such DSMs depends on the number and distribution of ground control points (GCPs). Placing and measuring GCPs are often the most time-consuming on-site tasks in a UAV project. Safety or accessibility concerns may impede their proper placement, so either costlier techniques must be used, or a less accurate DSM is obtained. Photogrammetric blocks flown by drones with on-board receivers capable of RTK (real-time kinematic) positioning do not need GCPs, as camera stations at exposure time can be determined with cm-level accuracy, and used to georeference the block and control its deformations. This paper presents an experimental investigation on the repeatability of DSM generation from several blocks acquired with a RTK-enabled drone, where differential corrections were sent from a local master station or a network of Continuously Operating Reference Stations (CORS). Four different flights for each RTK mode were executed over a test field, according to the same flight plan. DSM generation was performed with three block control configurations: GCP only, camera stations only, and with camera stations and one GCP. The results show that irrespective of the RTK mode, the first and third configurations provide the best DSM inner consistency. The average range of the elevation discrepancies among the DSMs in such cases is about 6 cm (2.5 GSD, ground sampling density) for a 10-cm resolution DSM. Using camera stations only, the average range is almost twice as large (4.7 GSD). The average DSM accuracy, which was verified on checkpoints, turned out to be about 2.1 GSD with the first and third configurations, and 3.7 GSD with camera stations only.

show abstract

“…Both proprietary and open source photogrammetric software applications exist, which are used for work and research [6][7][8]. Unlike proprietary software, however, open source gives the possibility to examine [9,10], modify and redistribute the algorithms, and is particularly suitable for research reproducibility and replicability [11] and closer to the general concept of open science [12].…”

Section: Introductionmentioning

confidence: 99%

High Resolution Historical Topography: Getting More from Archival Aerial Photographs

Seccaroni

Santangelo

Marchesini

et al. 2018

The 2nd International Electronic Conference on Remote Sensing

View full text Add to dashboard Cite

High resolution elevation data is a fundamental information for multiple applications in geomorphology spanning from visual analyses to modeling. Nowadays, gathering of high-quality elevation data relies on multiple sensors and technologies which can be mounted on terrestrial, aerial and satellite platforms. In the last years, the Structure from Motion (SfM) algorithms have made possible the acquisition of high and very-high resolution elevation data from optical images acquired with high overlapping rates at virtually no cost. Such a feature made it possible to exploit remote sensing archival imagery to build historical topographic information with unprecedented detail. However, despite the increasing number of applications of SfM algorithms in the scientific literature, still little has been done in terms optimization and quality evaluation of the results. We have applied the SfM algorithm developed in the photogrammetric open source software MicMac to six black and white aerial photographs taken in 1954 at 1:33.000 in a mountainous and steep area in Central Italy. The aim of the experiment consists in a quantitative evaluation of the digital surface models obtained for different scanning settings.

show abstract

Testing Accuracy and Repeatability of UAV Blocks Oriented with GNSS-Supported Aerial Triangulation

Cited by 160 publications

References 45 publications

A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles

A New Method to Map Groundwater Table in Peatlands Using Unmanned Aerial Vehicles

Quality Assessment of DSMs Produced from UAV Flights Georeferenced with On-Board RTK Positioning

High Resolution Historical Topography: Getting More from Archival Aerial Photographs

Contact Info

Product

Resources

About