Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope
The 3D real scene model of high-steep rock slope established based on UAV image provides convenience for non-contact identification and interpretation of rock mass structures. The quality of 3D models directly influences the interpretability of rock mass structures. However, quantitative studies on...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223003825 |
| _version_ | 1797389518995718144 |
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| author | Mingyu Zhao Jianping Chen Shengyuan Song Yongchao Li Fengyan Wang Sicong Wang Dianze Liu |
| author_facet | Mingyu Zhao Jianping Chen Shengyuan Song Yongchao Li Fengyan Wang Sicong Wang Dianze Liu |
| author_sort | Mingyu Zhao |
| collection | DOAJ |
| description | The 3D real scene model of high-steep rock slope established based on UAV image provides convenience for non-contact identification and interpretation of rock mass structures. The quality of 3D models directly influences the interpretability of rock mass structures. However, quantitative studies on the relationship between these two aspects are scarce. Therefore, this study investigates the influence of indicators such as photography distance (D), model brightness (l), angle between photography optical axis and the discontinuity to be interpreted (θd), and texture distortion area ratio (tdp), among others, on the interpretability of the 3D models. Furthermore, it delves into the relationships among these indicators and their practical application effects in complex high-steep rock slopes. On this foundation, a novel multi-indicator quality evaluation method for 3D models constructed using UAV photogrammetry is introduced for the first time. This method, based on a composite index model and incorporating empirical approaches, classifies the quality of 3D models into five levels. Guided by the quality evaluation results and taking into account the terrain development and geometric characteristics of discontinuities, a technical framework supporting the acquisition of high-quality 3D models is proposed, known as multi-angle nap-of-the-object image acquisition (MNIA). The research indicates that the 3D models established based on MNIA exhibit significantly reduced texture distortion, leading to a substantial improvement in recognizability, with a goodness rate of 79.98%, far surpassing that of oblique photogrammetry (41.18%). This study provides crucial guidance for obtaining high-quality UAV image in complex terrain environments and holds significant engineering application value in the fine identification and interpretation of rock mass structures on high-steep rock slopes. |
| first_indexed | 2024-03-08T22:57:10Z |
| format | Article |
| id | doaj.art-0ef43aed4eb9465ba26cfc391c4288b6 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-08T22:57:10Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-0ef43aed4eb9465ba26cfc391c4288b62023-12-16T06:06:27ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-12-01125103558Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slopeMingyu Zhao0Jianping Chen1Shengyuan Song2Yongchao Li3Fengyan Wang4Sicong Wang5Dianze Liu6College of Construction Engineering, Jilin University, Changchun, 130026, ChinaCollege of Construction Engineering, Jilin University, Changchun, 130026, ChinaCollege of Construction Engineering, Jilin University, Changchun, 130026, China; Corresponding author.College of Construction Engineering, Jilin University, Changchun, 130026, ChinaCollege of Geo-Exploration Science and Technology, Jilin University, Changchun, 130026, ChinaCollege of Construction Engineering, Jilin University, Changchun, 130026, ChinaCollege of Construction Engineering, Jilin University, Changchun, 130026, ChinaThe 3D real scene model of high-steep rock slope established based on UAV image provides convenience for non-contact identification and interpretation of rock mass structures. The quality of 3D models directly influences the interpretability of rock mass structures. However, quantitative studies on the relationship between these two aspects are scarce. Therefore, this study investigates the influence of indicators such as photography distance (D), model brightness (l), angle between photography optical axis and the discontinuity to be interpreted (θd), and texture distortion area ratio (tdp), among others, on the interpretability of the 3D models. Furthermore, it delves into the relationships among these indicators and their practical application effects in complex high-steep rock slopes. On this foundation, a novel multi-indicator quality evaluation method for 3D models constructed using UAV photogrammetry is introduced for the first time. This method, based on a composite index model and incorporating empirical approaches, classifies the quality of 3D models into five levels. Guided by the quality evaluation results and taking into account the terrain development and geometric characteristics of discontinuities, a technical framework supporting the acquisition of high-quality 3D models is proposed, known as multi-angle nap-of-the-object image acquisition (MNIA). The research indicates that the 3D models established based on MNIA exhibit significantly reduced texture distortion, leading to a substantial improvement in recognizability, with a goodness rate of 79.98%, far surpassing that of oblique photogrammetry (41.18%). This study provides crucial guidance for obtaining high-quality UAV image in complex terrain environments and holds significant engineering application value in the fine identification and interpretation of rock mass structures on high-steep rock slopes.http://www.sciencedirect.com/science/article/pii/S1569843223003825High-steep rock slopeInterpretation of rock structureUAV photogrammetryImage acquisition3D model quality evaluation |
| spellingShingle | Mingyu Zhao Jianping Chen Shengyuan Song Yongchao Li Fengyan Wang Sicong Wang Dianze Liu Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope International Journal of Applied Earth Observations and Geoinformation High-steep rock slope Interpretation of rock structure UAV photogrammetry Image acquisition 3D model quality evaluation |
| title | Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope |
| title_full | Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope |
| title_fullStr | Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope |
| title_full_unstemmed | Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope |
| title_short | Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope |
| title_sort | proposition of uav multi angle nap of the object image acquisition framework based on a quality evaluation system for a 3d real scene model of a high steep rock slope |
| topic | High-steep rock slope Interpretation of rock structure UAV photogrammetry Image acquisition 3D model quality evaluation |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223003825 |
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