Generating a High-Precision True Digital Orthophoto Map Based on UAV Images
Unmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distribut...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-08-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | http://www.mdpi.com/2220-9964/7/9/333 |
| _version_ | 1819212744993275904 |
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| author | Yu Liu Xinqi Zheng Gang Ai Yi Zhang Yuqiang Zuo |
| author_facet | Yu Liu Xinqi Zheng Gang Ai Yi Zhang Yuqiang Zuo |
| author_sort | Yu Liu |
| collection | DOAJ |
| description | Unmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distributed and images were collected using a multi-rotor UAV and professional camera, at a flight height of 160 m above the ground and a designed ground sample distance (GSD) of 0.016 m. A structure from motion (SfM), revised digital surface model (DSM) and multi-view image texture compensation workflow were outlined to generate a high-precision TDOM. We then used randomly distributed checkpoints on the TDOM to verify its precision. The horizontal accuracy of the generated TDOM was 0.0365 m, the vertical accuracy was 0.0323 m, and the GSD was 0.0166 m. Tilt and shadowed areas of the TDOM were eliminated so that buildings maintained vertical viewing angles. This workflow produced a TDOM accuracy within 0.05 m, and provided an effective method for identifying rural homesteads, as well as land planning and design. |
| first_indexed | 2024-12-23T06:47:50Z |
| format | Article |
| id | doaj.art-ffcdcd8e79d64dbd8c8847fa32e01b83 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-23T06:47:50Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-ffcdcd8e79d64dbd8c8847fa32e01b832022-12-21T17:56:31ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-08-017933310.3390/ijgi7090333ijgi7090333Generating a High-Precision True Digital Orthophoto Map Based on UAV ImagesYu Liu0Xinqi Zheng1Gang Ai2Yi Zhang3Yuqiang Zuo4School of Information Engineering, China University of Geoscience Beijing, Beijing 100083, ChinaSchool of Information Engineering, China University of Geoscience Beijing, Beijing 100083, ChinaSchool of Information Engineering, China University of Geoscience Beijing, Beijing 100083, ChinaSchool of Information Engineering, China University of Geoscience Beijing, Beijing 100083, ChinaChina Land Surveying and Planning Institute, Beijing 100035, ChinaUnmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distributed and images were collected using a multi-rotor UAV and professional camera, at a flight height of 160 m above the ground and a designed ground sample distance (GSD) of 0.016 m. A structure from motion (SfM), revised digital surface model (DSM) and multi-view image texture compensation workflow were outlined to generate a high-precision TDOM. We then used randomly distributed checkpoints on the TDOM to verify its precision. The horizontal accuracy of the generated TDOM was 0.0365 m, the vertical accuracy was 0.0323 m, and the GSD was 0.0166 m. Tilt and shadowed areas of the TDOM were eliminated so that buildings maintained vertical viewing angles. This workflow produced a TDOM accuracy within 0.05 m, and provided an effective method for identifying rural homesteads, as well as land planning and design.http://www.mdpi.com/2220-9964/7/9/333unmanned aerial vehiclestructure from motionmulti view stereodigital surface modeltrue digital orthophoto map |
| spellingShingle | Yu Liu Xinqi Zheng Gang Ai Yi Zhang Yuqiang Zuo Generating a High-Precision True Digital Orthophoto Map Based on UAV Images ISPRS International Journal of Geo-Information unmanned aerial vehicle structure from motion multi view stereo digital surface model true digital orthophoto map |
| title | Generating a High-Precision True Digital Orthophoto Map Based on UAV Images |
| title_full | Generating a High-Precision True Digital Orthophoto Map Based on UAV Images |
| title_fullStr | Generating a High-Precision True Digital Orthophoto Map Based on UAV Images |
| title_full_unstemmed | Generating a High-Precision True Digital Orthophoto Map Based on UAV Images |
| title_short | Generating a High-Precision True Digital Orthophoto Map Based on UAV Images |
| title_sort | generating a high precision true digital orthophoto map based on uav images |
| topic | unmanned aerial vehicle structure from motion multi view stereo digital surface model true digital orthophoto map |
| url | http://www.mdpi.com/2220-9964/7/9/333 |
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