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Open AccessArticle

Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK

1
Engineering Department, University of Ferrara, via Saragat 1, 44122 Ferrara, Italy
2
Physics and Earth Science Department, University of Ferrara, via Saragat 1, 44122 Ferrara, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(19), 3144; https://doi.org/10.3390/rs12193144
Received: 13 August 2020 / Revised: 17 September 2020 / Accepted: 21 September 2020 / Published: 24 September 2020
(This article belongs to the Special Issue RTK Positioning for UAV Remote Sensing)
Aerial photogrammetry by Unmanned Aerial Vehicles (UAVs) is a widespread method to perform mapping tasks with high-resolution to reconstruct three-dimensional (3D) building and façade models. However, the survey of Ground Control Points (GCPs) represents a time-consuming task, while the use of Real-Time Kinematic (RTK) drones allows for one to collect camera locations with an accuracy of a few centimeters. DJI Phantom 4 RTK (DJI-P4RTK) combines this with the possibility to acquire oblique images in stationary conditions and it currently represents a versatile drone widely used from professional users together with commercial Structure-from-Motion software, such as Agisoft Metashape. In this work, we analyze the architectural application of this drone to the photogrammetric modeling of a building with particular regard to metric survey specifications for cultural heritage for 1:20, 1:50, 1:100, and 1:200 scales. In particular, we designed an accuracy assessment test signalizing 109 points, surveying them with total station and adjusting the measurements through a network approach in order to achieve millimeter-level accuracy. Image datasets with a designed Ground Sample Distance (GSD) of 2 mm were acquired in Network RTK (NRTK) and RTK modes in manual piloting and processed both as single façades (S–F) and as an overall block (4–F). Subsequently, we compared the results of photogrammetric models generated in Agisoft Metashape to the Signalized Point (SP) coordinates. The results highlight the importance of processing an overall photogrammetric block, especially whenever part of camera locations exhibited a poorer accuracy due to multipath effects. No significant differences were found between the results of network real-time kinematic (NRTK) and real-time kinematic (RTK) datasets. Horizontal residuals were generally comparable to GNSS accuracy in NRTK/RTK mode, while vertical residuals were found to be affected by an offset of about 5 cm. We introduced an external GCP or used one SP per façade as GCP, assuming a poorer camera location accuracy at the same time, in order to fix this issue and comply with metric survey specifications for the widest architectural scale range. Finally, both S–F and 4–F projects satisfied the metric survey requirements of a scale of 1:50 in at least one of the approaches tested. View Full-Text
Keywords: GNSS; direct georeferencing; DJI Phantom 4 RTK; Unmanned Aerial Vehicle (UAV); real-time kinematic (RTK); network real-time kinematic (NRTK); on-board RTK; building modeling; façade mapping; photogrammetry GNSS; direct georeferencing; DJI Phantom 4 RTK; Unmanned Aerial Vehicle (UAV); real-time kinematic (RTK); network real-time kinematic (NRTK); on-board RTK; building modeling; façade mapping; photogrammetry
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MDPI and ACS Style

Taddia, Y.; González-García, L.; Zambello, E.; Pellegrinelli, A. Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK. Remote Sens. 2020, 12, 3144.

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