Abstract
Imagery and laser scanning data are two major sources of 3D information. Each dataset has distinct characteristics that render it preferable for certain applications. The fusion of imagery and laser scanning data is a prerequisite to utilising the complementary characteristics of both datasets. In the past decade, a number of methods have been developed for the geometrical fusion of the two types of datasets for better 3D mapping in various applications. This article presents a systematic review of these methods. First, comparative analysis of the derivation of 3D information from imagery through photogrammetry and laser scanning is presented. Then, three categories of methods for the geometric fusion of imagery and laser scanning data are detailed, namely, laser scanning data used as controls for imagery, imagery used as controls for laser scanning data and the combined adjustment of imagery and laser scanning data. The advantages and limitations of the three categories of methods are analysed. Finally, suggestions for future research in this area are discussed, and concluding remarks are given.
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