GNSS-supported direct georeferencing for UAV photogrammetry without GCP in Antarctica: a case study in Larsemann Hills

Abstract

Unmanned aerial vehicle (UAV) has become an increasingly popular remote sensing platform in Antarctica. Due to the challenging natural conditions and lack of global navigation satellite system (GNSS) references in Antarctica, GNSS-supported direct georeferencing holds great potential for remote sensing applications in this region. Based on UAV surveys and GNSS observations we performed in Larsemann Hills, Antarctica, four GNSS-supported direct georeferencing schemes for UAV photogrammetry without ground control point (GCP) were designed and evaluated. Three of the schemes can generate high-accuracy photogrammetric products (horizontal accuracy: ∼0.7 ground sampling distance (GSD), vertical accuracy: ∼2.6 GSD). The fourth scheme, while exhibiting a lower accuracy at the meter-level, could offer high flexibility, and the accuracy of its derived products could be improved by post-flight transformation. The selection of an appropriate georeferencing scheme should be contingent upon the given application scenario, which can enhance the quality and accuracy of UAV photogrammetry in Antarctica. Potential applications of UAV remote sensing in Antarctica were discussed. It’s proven that UAV photogrammetry constitutes a reliable tool for Antarctic expedition path planning and ice morphology evolution monitoring. Our study demonstrated that direct georeferencing can generate high-accuracy UAV products in a reliable and feasible way in Antarctica.

Keywords:

• Antarctica
• georeferencing
• Larsemann Hills
• photogrammetry
• UAV

Acknowledgements

We would like to thank the logistic and technical support provided by the 35th and 36th CHINARE teams, the Polar Research Institute of China, and the Chinese Arctic and Antarctic Administration.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Data Availability Statement

The availability of data is based on personal requests.

Additional information

Funding

This work was supported by the National Key Research and Development Program of China [2021YFB3900105 and 2022YFC2807105], the National Natural Science Foundation of China [42276249, 42011530088, 42111530185, and 41941006], and the Fundamental Research Funds for the Central Universities.