New and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined by the algorithm used, which should enable the user to obtain a dataset appropriate and optimal for the planned purpose. The aim of this article is to propose a new Optimum Dataset method (OptD method) in the processing of LiDAR point clouds. The OptD method can reduce the number of points in a dataset for the specified optimization criteria concerning the characteristics of generated DTM. The OptD method can be used in two variants: OptD-single (one criterion for optimization) and OptD-multi (two or more optimization criteria). The OptD-single method has been thoroughly tested and presented by Błaszczak-Bąk (2016 Acta Geodyn. Geomater. 13/4 379–86). In this paper the authors discussed the OptD-multi method.
Authors
- dr inż. Wioleta Błaszczak-bąk,
- dr inż. Anna Sobieraj-Żłobińska link open in new tab ,
- Michał Kowalik
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1088/1361-6501/aa7444
- Category
- Publikacja w czasopiśmie
- Type
- artykuł w czasopiśmie wyróżnionym w JCR
- Language
- polski
- Publication year
- 2017
Source: MOSTWiedzy.pl - publication "The OptD-multi method in LiDAR processing" link open in new tab
