4.6 Article

Optimization of Ground Control Point Distribution for Unmanned Aerial Vehicle Photogrammetry for Inaccessible Fields

期刊

SUSTAINABILITY
卷 14, 期 15, 页码 -

出版社

MDPI
DOI: 10.3390/su14159505

关键词

GCP; UAV; photogrammetry; accuracy evaluation

资金

  1. Establishment of a Sustainable Community Development Model based on Integrated Natural Resource Management System in Lake Malawi National Park (Int NRMS) Project under the Science and Technology Research Partnership for Sustainable Development (SATREPS)
  2. Japan International Cooperation Agency (JICA)
  3. JSPS KAKENHI [JP20K06351]

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This study aims to suggest the optimal GCP distribution pattern when only the outer edge of a particular area is available. Results show that patterns with GCPs distributed evenly around the field provided the best calibration. If this kind of pattern is not achievable, patterns with GCPs distributed evenly around half of the field or forming an evenly distributed triangle can provide moderate accuracy.
Ground control point (GCP) is an important calibration factor when correcting position information during unmanned aerial vehicle (UAV) remote sensing. Studies of the optimal number and distribution shape of GCPs have been conducted worldwide in recent years. However, when conducting surveys at houses, construction sites, farming lands, forests, and some other locations, it is both difficult and destructive to install GCP inside the subject area. In many cases, it is only possible to install GCP at the outer edge around the area. Therefore, this study aims to suggest the optimal GCP distribution pattern, which can provide the highest accuracy, when only the outer edge of a particular area is available. In this research, 88 GCP patterns have been validated and compared at an 18 ha farm. Results show that the patterns with GCPs distributed evenly around the field provided the best calibration (RMSE = 0.15 m). If this kind of pattern is not achievable because of obstructions, patterns with GCPs distributed evenly around half of the field or forming an evenly distributed triangle can provide moderate accuracy (RMSE = 0.18 m and 0.43 m, respectively). Patterns with GCPs forming a straight line yielded the worst accuracy (RMSE = 2.10 m). This shows that GCP distributions of a two-dimensional shape, even if the surrounding area is small, are better calibrated than a long, straight line. These results strongly suggest that appropriate GCP distribution patterns in the study areas will provide satisfactory accuracy for constructing integrated monitoring systems of diverse resources.

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