Next Article in Journal
Identifying Users’ Requirements for Emergency Mapping Team Operations in the Dominican Republic
Next Article in Special Issue
GNSS Positioning Using Mobile Devices with the Android Operating System
Previous Article in Journal
FloodSim: Flood Simulation and Visualization Framework Using Position-Based Fluids
Previous Article in Special Issue
Making Smart Cities Resilient to Climate Change by Mitigating Natural Hazard Impacts
Open AccessArticle

Accuracy Assessment of a UAV Block by Different Software Packages, Processing Schemes and Validation Strategies

1
Department of Civil Engineering and Architecture, University of Pavia, Via Ferrata, 3, 27100 Pavia, Italy
2
Department of Architecture and Design, Polytechnic of Turin, Viale Pier Andrea Mattioli, 39, 10125 Turin, Italy
3
Department of Environment, Land and Infrastructure Engineering, Polytechnic of Turin, Corso Duca degli Abruzzi, 24, 10129 Turin, Italy
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(3), 164; https://doi.org/10.3390/ijgi9030164
Received: 31 January 2020 / Revised: 14 February 2020 / Accepted: 8 March 2020 / Published: 11 March 2020
(This article belongs to the Special Issue Enhanced Modeling and Surveying Tools for Smart Cities)
Unmanned aerial vehicle (UAV) systems are heavily adopted nowadays to collect high-resolution imagery with the purpose of documenting and mapping environment and cultural heritage. Such data are currently processed by programs based on the Structure from Motion (SfM) concept, coming from the computer vision community, rather than from classical photogrammetry. It is interesting to check whether some widely accepted rules coming from old-fashioned photogrammetry still holds: the relation between accuracy and ground sampling distance (GSD), the ratio between the vertical and horizontal accuracy, accuracy estimated on ground control points (GCPs) vs. that estimated with check points (CPs) also in relation to their ratio and distribution. To face the envisaged aspects, the paper adopts a comparative approach, as several programs are used and numerous configurations considered. The paper illustrates the dataset adopted, the carefully tuned processing strategies and bundle block adjustment (BBA) results in terms of accuracy for both GCPs and CPs. Finally, a leave-one-out (LOO) cross-validation strategy is proposed to assess the accuracy for one of the proposed configurations. Some of the reported results were previously presented in the 5th GISTAM Conference. View Full-Text
Keywords: UAV; bundle block adjustment; accuracy evaluation; proprietary software; open source software; cross-validation UAV; bundle block adjustment; accuracy evaluation; proprietary software; open source software; cross-validation
Show Figures

Figure 1

MDPI and ACS Style

Casella, V.; Chiabrando, F.; Franzini, M.; Manzino, A.M. Accuracy Assessment of a UAV Block by Different Software Packages, Processing Schemes and Validation Strategies. ISPRS Int. J. Geo-Inf. 2020, 9, 164.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop