A photogrammetric approach to fusing natural colour and thermal infrared UAS imagery in 3D point cloud generation

ABSTRACT

The inclusion of thermal infrared (TIR) data in point clouds derived from unmanned aircraft system (UAS) imagery can benefit a variety of applications in which surface temperature and 3D geometry are both important discriminants of feature type and condition. Low resolution and narrow fields of view (FOV) of current consumer-grade TIR cameras on UAS, combined with the lack of sharpness and texture in many image regions, may cause failure or poor results from structure from motion (SfM) photogrammetric software, which has gained widespread use for generating point clouds from UAS imagery. This paper proposes a photogrammetric approach for generating 3D multispectral point clouds utilizing coacquired TIR-RGB images. A 3D point cloud is first generated from the RGB imagery using standard SfM procedures. Then the TIR attributes are assigned to points, where the image coordinates of the points in TIR images are estimated using transformation parameters obtained from co-registration procedures. To obtain RGB-to-TIR transformation parameters, this study tests 3D and 2D co-registration approaches. The latter produces better results due to the challenge of calibrating the TIR camera as required for the 3D approach. This proposed approach is advantageous for generating TIR point clouds without loss of photogrammetric precision compared with solely TIR-based SfM, as the 3D accuracy, point density, and reliability are greatly enhanced.

Acknowledgements

The funding for this research was provided internally by the School of Civil and Construction Engineering (CCE) at Oregon State University (OSU). The UAS flights were conducted under Federal Aviation Administration (FAA) certificate of authorization (COA) number 2016-WSA-101-COA. We thank Dr. Michael Olsen, Dr. Jihye Park, and Dr. Michael Wing for their valuable comments and suggestions on improving the quality of this paper. We are thankful to Chase Simpson, Greyson Termini, William Gage Maurer, Laura Barreiro Fernández, Dr. Eduardo González-Ferreiro, and Erzhuo Che for their help with collecting the data, and Joseph Fradella for providing the FLIR E6 camera. We would like to acknowledge VDOS Global, OSU Research Office, Pacific Power, Adair RC Club, and Bonneville Power Administration (BPA) and Dr. Roberto Albertani for supplying the logistics for the UAS flight operations. We also appreciate Leica Geosystems, David Evans and Associates, and MicroSurvey for providing surveying equipment and/or software. We would like to thank two anonymous reviewers for their constructive suggestions and comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the School of Civil and Construction Engineering (CCE) at Oregon State University (OSU).