Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry

Unmanned aerial vehicle (UAV) systems are often used to collect high-resolution imagery. Data obtained from UAVs are now widely used for both military and civilian purposes. This article discusses the issues related to the use of UAVs for the imaging of restricted areas. Two methods of developing si...

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Main Authors: Marta Lalak, Damian Wierzbicki, Michał Kędzierski
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/20/3336
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author Marta Lalak
Damian Wierzbicki
Michał Kędzierski
author_facet Marta Lalak
Damian Wierzbicki
Michał Kędzierski
author_sort Marta Lalak
collection DOAJ
description Unmanned aerial vehicle (UAV) systems are often used to collect high-resolution imagery. Data obtained from UAVs are now widely used for both military and civilian purposes. This article discusses the issues related to the use of UAVs for the imaging of restricted areas. Two methods of developing single-strip blocks with the optimal number of ground control points are presented. The proposed methodology is based on a modified linear regression model and an empirically modified Levenberg–Marquardt–Powell algorithm. The effectiveness of the proposed methods of adjusting a single-strip block were verified based on several test sets. For method I, the mean square errors (RMSE) values for the <i>X</i>, <i>Y</i>, <i>Z</i> coordinates of the control points were within the range of 0.03–0.13 m/0.08–0.09 m, and for the second method, 0.03–0.04 m/0.06–0.07 m. For independent control points, the RMSE values were 0.07–0.12 m/0.06–0.07 m for the first method and 0.07–0.12 m/0.07–0.09 m for the second method. The results of the single-strip block adjustment showed that the use of the modified Levenberg–Marquardt–Powell method improved the adjustment accuracy by 13% and 16%, respectively.
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spelling doaj.art-cfbdf611693b484aa6f5fd58cfec54df2023-11-20T16:53:55ZengMDPI AGRemote Sensing2072-42922020-10-011220333610.3390/rs12203336Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV PhotogrammetryMarta Lalak0Damian Wierzbicki1Michał Kędzierski2Institute of Navigation, Military University of Aviation, 08-521 Dęblin, PolandInstitute of Geospatial Engineering and Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, PolandInstitute of Geospatial Engineering and Geodesy, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, PolandUnmanned aerial vehicle (UAV) systems are often used to collect high-resolution imagery. Data obtained from UAVs are now widely used for both military and civilian purposes. This article discusses the issues related to the use of UAVs for the imaging of restricted areas. Two methods of developing single-strip blocks with the optimal number of ground control points are presented. The proposed methodology is based on a modified linear regression model and an empirically modified Levenberg–Marquardt–Powell algorithm. The effectiveness of the proposed methods of adjusting a single-strip block were verified based on several test sets. For method I, the mean square errors (RMSE) values for the <i>X</i>, <i>Y</i>, <i>Z</i> coordinates of the control points were within the range of 0.03–0.13 m/0.08–0.09 m, and for the second method, 0.03–0.04 m/0.06–0.07 m. For independent control points, the RMSE values were 0.07–0.12 m/0.06–0.07 m for the first method and 0.07–0.12 m/0.07–0.09 m for the second method. The results of the single-strip block adjustment showed that the use of the modified Levenberg–Marquardt–Powell method improved the adjustment accuracy by 13% and 16%, respectively.https://www.mdpi.com/2072-4292/12/20/3336photogrammetryunmanned aerial vehiclebundle block adjustmentsingle stripaccuracy analysisadditional parameters
spellingShingle Marta Lalak
Damian Wierzbicki
Michał Kędzierski
Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry
Remote Sensing
photogrammetry
unmanned aerial vehicle
bundle block adjustment
single strip
accuracy analysis
additional parameters
title Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry
title_full Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry
title_fullStr Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry
title_full_unstemmed Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry
title_short Methodology of Processing Single-Strip Blocks of Imagery with Reduction and Optimization Number of Ground Control Points in UAV Photogrammetry
title_sort methodology of processing single strip blocks of imagery with reduction and optimization number of ground control points in uav photogrammetry
topic photogrammetry
unmanned aerial vehicle
bundle block adjustment
single strip
accuracy analysis
additional parameters
url https://www.mdpi.com/2072-4292/12/20/3336
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AT damianwierzbicki methodologyofprocessingsinglestripblocksofimagerywithreductionandoptimizationnumberofgroundcontrolpointsinuavphotogrammetry
AT michałkedzierski methodologyofprocessingsinglestripblocksofimagerywithreductionandoptimizationnumberofgroundcontrolpointsinuavphotogrammetry