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

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-...

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Main Authors: Yuri Taddia, Laura González-García, Elena Zambello, Alberto Pellegrinelli
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/19/3144
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spelling doaj-19c919eb5ded4a058610fc8ee023ea312020-11-25T02:46:18ZengMDPI AGRemote Sensing2072-42922020-09-01123144314410.3390/rs12193144Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTKYuri Taddia0Laura González-García1Elena Zambello2Alberto Pellegrinelli3Engineering Department, University of Ferrara, via Saragat 1, 44122 Ferrara, ItalyEngineering Department, University of Ferrara, via Saragat 1, 44122 Ferrara, ItalyPhysics and Earth Science Department, University of Ferrara, via Saragat 1, 44122 Ferrara, ItalyEngineering Department, University of Ferrara, via Saragat 1, 44122 Ferrara, ItalyAerial 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.https://www.mdpi.com/2072-4292/12/19/3144GNSSdirect georeferencingDJI Phantom 4 RTKUnmanned Aerial Vehicle (UAV)real-time kinematic (RTK)network real-time kinematic (NRTK)
collection DOAJ
language English
format Article
sources DOAJ
author Yuri Taddia
Laura González-García
Elena Zambello
Alberto Pellegrinelli
spellingShingle Yuri Taddia
Laura González-García
Elena Zambello
Alberto Pellegrinelli
Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK
Remote Sensing
GNSS
direct georeferencing
DJI Phantom 4 RTK
Unmanned Aerial Vehicle (UAV)
real-time kinematic (RTK)
network real-time kinematic (NRTK)
author_facet Yuri Taddia
Laura González-García
Elena Zambello
Alberto Pellegrinelli
author_sort Yuri Taddia
title Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK
title_short Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK
title_full Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK
title_fullStr Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK
title_full_unstemmed Quality Assessment of Photogrammetric Models for Façade and Building Reconstruction Using DJI Phantom 4 RTK
title_sort quality assessment of photogrammetric models for façade and building reconstruction using dji phantom 4 rtk
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-09-01
description 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.
topic GNSS
direct georeferencing
DJI Phantom 4 RTK
Unmanned Aerial Vehicle (UAV)
real-time kinematic (RTK)
network real-time kinematic (NRTK)
url https://www.mdpi.com/2072-4292/12/19/3144
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