Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing

ABSTRACT

Optical imagery and Light Detection And Ranging (LiDAR) point cloud are two major data sources in the community of photogrammetry and remote sensing. Optical images and LiDAR data have unique characteristics that make them preferable in certain applications. On the other hand, the disadvantage of one type of data source may be compensated by an advantage of the other. Hence, data fusion is a prerequisite to utilising the complementary characteristics of both data sources. Numerous methods haven been proposed to perform the fusion in various applications. This article makes a systematic review of the state-of-the-art fusion methodology used in various applications, such as registration, generation of true orthophotographs, pan-sharpening, classification, recognition of some key targets, three-dimensional reconstruction, change detection and forest inventory. Moreover, the future developing trends are introduced. In the coming few years, we expect that fusion of optical images and LiDAR point cloud will promote the development of both photogrammetry and laser scanning in both industry and scientific research.

KEYWORDS:

• Data fusion
• point cloud
• optical image
• classification
• target recognition
• change detection

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by a grant from the National Natural Science Foundation of China (Project No. 41371405).