A Physical Process Driven Digital Terrain Model Generating Method Based on D-NURBS
| Autor: | Lu Zehong, Zhiming Zheng, Cheng Su, Xin Jiang, Bolun Wang, Guanying Huo, Ye Danlei |
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| Rok vydání: | 2020 |
| Předmět: |
physical process driven fitting
General Computer Science Light detection Computer science business.industry General Engineering Point cloud Process (computing) Ranging Terrain NURBS Lidar Digital terrain model Surface fitting LiDAR point cloud General Materials Science Computer vision lcsh:Electrical engineering. Electronics. Nuclear engineering Artificial intelligence business Digital elevation model lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 8, Pp 3115-3122 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2019.2962385 |
| Popis: | Airborne light detection and ranging (LiDAR) technology is becoming the primary method for generating high-resolution digital terrain models (DTMs), which is essential for commercial and scientific uses. In order to generate DTMs, non-ground features as buildings, vehicles, and vegetation must be recognized and distinguished from the LiDAR point cloud. However, various degrees of errors may accumulate in the separated filtering and modeling processes. In this paper, a novel physical process driven DTM generating method for airborne LiDAR measurement is proposed, which combines the point cloud classification and surface fitting process simultaneously. Actually, the physical dynamic process is integrated with the common non-uniform rational b-splines (NURBS) model under the corresponding parameter mediation. The experimental results show that the proposed method is efficacious in reducing errors and have a nice performance in terrain fitting. |
| Databáze: | OpenAIRE |
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