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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MDPI AG
2020-10-01
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Series: | Remote Sensing |
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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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issn | 2072-4292 |
language | English |
last_indexed | 2024-03-10T15:40:51Z |
publishDate | 2020-10-01 |
publisher | MDPI AG |
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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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