Abstract
This paper focuses on the classification of airborne lidar (LiDAR) data using TerraScan software. At first, the composition of the airborne lidar system and the organization and characteristics of the point cloud data are analyzed. Then, the basic principles of classification by TerraScanare analyzed based on the airborne lidar data in the urban. First, noise points such as blank and low points are removed, next, implement point cloud filtered according to the macro commands provided by TerraScan, and finally further classify and point cloud are thinned, included that classify ground points, vegetation points, building points, and model key points, this operation is generated mainly by program implementation; In order to ensure the accuracy of the classification, manual classification must be carried out. Consequently the classification results of TerraScan are summarized, involving the advantages and disadvantages of the classification, and the technical development requirements of classification using TerraScan are proposed.
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Liu, M., Sun, X., Shao, Y., You, Y. (2019). Surface Features Classification of Airborne Lidar Data Based on TerraScan. In: Xie, Y., Zhang, A., Liu, H., Feng, L. (eds) Geo-informatics in Sustainable Ecosystem and Society. GSES 2018. Communications in Computer and Information Science, vol 980. Springer, Singapore. https://doi.org/10.1007/978-981-13-7025-0_19
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DOI: https://doi.org/10.1007/978-981-13-7025-0_19
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