WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY
The use of Unmanned Arial Vehicle (UAV) photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2016-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B1/781/2016/isprs-archives-XLI-B1-781-2016.pdf |
| _version_ | 1811307559822295040 |
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| author | M. A. Boon R. Greenfield S. Tesfamichael |
| author_facet | M. A. Boon R. Greenfield S. Tesfamichael |
| author_sort | M. A. Boon |
| collection | DOAJ |
| description | The use of Unmanned Arial Vehicle (UAV) photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool to enhance the assessment of wetland ecosystems. The UAV images were collected during a single flight within 2½ hours over a 100 ha area at the Kameelzynkraal farm, Gauteng Province, South Africa. An AKS Y-6 MKII multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. Twenty ground control points (GCPs) were surveyed using a Trimble GPS to achieve geometrical precision and georeferencing accuracy. Structure-from-Motion (SfM) computer vision techniques were used to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The geometric accuracy of the data based on the 20 GCP’s were 0.018 m for the overall, 0.0025 m for the vertical root mean squared error (RMSE) and an over all root mean square reprojection error of 0.18 pixel. The UAV products were then edited and subsequently analysed, interpreted and key attributes extracted using a selection of tools/ software applications to enhance the wetland assessment. The results exceeded our expectations and provided a valuable and accurate enhancement to the wetland delineation, classification and health assessment which even with detailed field studies would have been difficult to achieve. |
| first_indexed | 2024-04-13T09:06:28Z |
| format | Article |
| id | doaj.art-217e09d365a74375a40a443bf6928beb |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-04-13T09:06:28Z |
| publishDate | 2016-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-217e09d365a74375a40a443bf6928beb2022-12-22T02:52:59ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342016-06-01XLI-B178178810.5194/isprs-archives-XLI-B1-781-2016WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRYM. A. Boon0R. Greenfield1S. Tesfamichael2Department of Zoology University of Johannesburg, PO Box 524 Auckland Park, 2006, South AfricaDepartment of Zoology University of Johannesburg, PO Box 524 Auckland Park, 2006, South AfricaDepartment of Geography, Environmental Management and Energy Studies University of Johannesburg Auckland Park, South AfricaThe use of Unmanned Arial Vehicle (UAV) photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool to enhance the assessment of wetland ecosystems. The UAV images were collected during a single flight within 2½ hours over a 100 ha area at the Kameelzynkraal farm, Gauteng Province, South Africa. An AKS Y-6 MKII multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. Twenty ground control points (GCPs) were surveyed using a Trimble GPS to achieve geometrical precision and georeferencing accuracy. Structure-from-Motion (SfM) computer vision techniques were used to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The geometric accuracy of the data based on the 20 GCP’s were 0.018 m for the overall, 0.0025 m for the vertical root mean squared error (RMSE) and an over all root mean square reprojection error of 0.18 pixel. The UAV products were then edited and subsequently analysed, interpreted and key attributes extracted using a selection of tools/ software applications to enhance the wetland assessment. The results exceeded our expectations and provided a valuable and accurate enhancement to the wetland delineation, classification and health assessment which even with detailed field studies would have been difficult to achieve.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B1/781/2016/isprs-archives-XLI-B1-781-2016.pdf |
| spellingShingle | M. A. Boon R. Greenfield S. Tesfamichael WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY |
| title_full | WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY |
| title_fullStr | WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY |
| title_full_unstemmed | WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY |
| title_short | WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY |
| title_sort | wetland assessment using unmanned aerial vehicle uav photogrammetry |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B1/781/2016/isprs-archives-XLI-B1-781-2016.pdf |
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