UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points
Unmanned aerial vehicle (UAV) photogrammetry has recently emerged as a popular solution to obtain certain products necessary in linear projects, such as orthoimages or digital surface models. This is mainly due to its ability to provide these topographic products in a fast and economical way. In ord...
| Main Authors: | , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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MDPI
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/8406 |
| _version_ | 1789406373350473728 |
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| author | Ferrer González, Ezequiel Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio |
| author_facet | Ferrer González, Ezequiel Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio |
| author_sort | Ferrer González, Ezequiel |
| collection | DSpace |
| description | Unmanned aerial vehicle (UAV) photogrammetry has recently emerged as a popular solution to obtain certain products necessary in linear projects, such as orthoimages or digital surface models. This is mainly due to its ability to provide these topographic products in a fast and economical way. In order to guarantee a certain degree of accuracy, it is important to know how many ground control points (GCPs) are necessary and how to distribute them across the study site. The purpose of this work consists of determining the number of GCPs and how to distribute them in a way that yields higher accuracy for a corridor-shaped study area. To do so, several photogrammetric projects have been carried out in which the number of GCPs used in the bundle adjustment and their distribution vary. The different projects were assessed taking into account two different parameters: the root mean square error (RMSE) and the Multiscale Model to Model Cloud Comparison (M3C2). From the different configurations tested, the projects using 9 and 11 GCPs (4.3 and 5.2 GCPs km−1, respectively) distributed alternatively on both sides of the road in an offset or zigzagging pattern, with a pair of GCPs at each end of the road, yielded optimal results regarding fieldwork cost, compared to projects using similar or more GCPs placed according to other distributions. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-8406 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-84062023-04-12T19:29:21Z UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points Ferrer González, Ezequiel Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio unmanned aerial vehicle (UAV) structure-from-motion (SfM) ground control points (GCP) accuracy assessment point clouds corridor mapping Unmanned aerial vehicle (UAV) photogrammetry has recently emerged as a popular solution to obtain certain products necessary in linear projects, such as orthoimages or digital surface models. This is mainly due to its ability to provide these topographic products in a fast and economical way. In order to guarantee a certain degree of accuracy, it is important to know how many ground control points (GCPs) are necessary and how to distribute them across the study site. The purpose of this work consists of determining the number of GCPs and how to distribute them in a way that yields higher accuracy for a corridor-shaped study area. To do so, several photogrammetric projects have been carried out in which the number of GCPs used in the bundle adjustment and their distribution vary. The different projects were assessed taking into account two different parameters: the root mean square error (RMSE) and the Multiscale Model to Model Cloud Comparison (M3C2). From the different configurations tested, the projects using 9 and 11 GCPs (4.3 and 5.2 GCPs km−1, respectively) distributed alternatively on both sides of the road in an offset or zigzagging pattern, with a pair of GCPs at each end of the road, yielded optimal results regarding fieldwork cost, compared to projects using similar or more GCPs placed according to other distributions. 2020-09-02T10:41:59Z 2020-09-02T10:41:59Z 2020-07-30 info:eu-repo/semantics/article 2072-4292 http://hdl.handle.net/10835/8406 en https://www.mdpi.com/2072-4292/12/15/2447 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | unmanned aerial vehicle (UAV) structure-from-motion (SfM) ground control points (GCP) accuracy assessment point clouds corridor mapping Ferrer González, Ezequiel Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points |
| title | UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points |
| title_full | UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points |
| title_fullStr | UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points |
| title_full_unstemmed | UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points |
| title_short | UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points |
| title_sort | uav photogrammetry accuracy assessment for corridor mapping based on the number and distribution of ground control points |
| topic | unmanned aerial vehicle (UAV) structure-from-motion (SfM) ground control points (GCP) accuracy assessment point clouds corridor mapping |
| url | http://hdl.handle.net/10835/8406 |
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