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Open AccessArticle

Photogrammetric 3D Model via Smartphone GNSS Sensor: Workflow, Error Estimate, and Best Practices

1
DISTAR, Università degli Studi di Napoli Federico II, Via Cupa Nuova Cintia, 21, 80126 Napoli, Italy
2
Consiglio Nazionale delle Ricerche, IGAG, c.o. Dipartimento di Scienze della Terra, Università di Roma Sapienza, P.le Aldo Moro 5, 00185 Roma, Italy
3
Geologist, Via Forno Vecchio, 38, Marigliano, 80034 Napoli, Italy
4
Department of Petroleum Engineering, Texas A&M University at Qatar, Education City, Doha PO Box 23874, Qatar
5
Dipartimento di Scienze della Terra, Sapienza Università di Roma, P.le Aldo Moro 5, 00185 Roma, Italy
6
Research Group ‘Geodesia’, Universidad Complutense de Madrid, 28040 Madrid, Spain
7
Department of Geological Sciences, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(21), 3616; https://doi.org/10.3390/rs12213616
Received: 29 September 2020 / Revised: 1 November 2020 / Accepted: 2 November 2020 / Published: 4 November 2020
(This article belongs to the Special Issue GNSS for Geosciences)
Geotagged smartphone photos can be employed to build digital terrain models using structure from motion-multiview stereo (SfM-MVS) photogrammetry. Accelerometer, magnetometer, and gyroscope sensors integrated within consumer-grade smartphones can be used to record the orientation of images, which can be combined with location information provided by inbuilt global navigation satellite system (GNSS) sensors to geo-register the SfM-MVS model. The accuracy of these sensors is, however, highly variable. In this work, we use a 200 m-wide natural rocky cliff as a test case to evaluate the impact of consumer-grade smartphone GNSS sensor accuracy on the registration of SfM-MVS models. We built a high-resolution 3D model of the cliff, using an unmanned aerial vehicle (UAV) for image acquisition and ground control points (GCPs) located using a differential GNSS survey for georeferencing. This 3D model provides the benchmark against which terrestrial SfM-MVS photogrammetry models, built using smartphone images and registered using built-in accelerometer/gyroscope and GNSS sensors, are compared. Results show that satisfactory post-processing registrations of the smartphone models can be attained, requiring: (1) wide acquisition areas (scaling with GNSS error) and (2) the progressive removal of misaligned images, via an iterative process of model building and error estimation. View Full-Text
Keywords: SfM-MVS photogrammetry; 3D model registration; GNSS-Smartphone; GCPs alternative SfM-MVS photogrammetry; 3D model registration; GNSS-Smartphone; GCPs alternative
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  • Externally hosted supplementary file 1
    Link: https://youtu.be/Jcoa0cc0L4I
    Description: This video illustrates step-by-step procedure for model construction and registration
MDPI and ACS Style

Tavani, S.; Pignalosa, A.; Corradetti, A.; Mercuri, M.; Smeraglia, L.; Riccardi, U.; Seers, T.; Pavlis, T.; Billi, A. Photogrammetric 3D Model via Smartphone GNSS Sensor: Workflow, Error Estimate, and Best Practices. Remote Sens. 2020, 12, 3616.

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