Topographic feature line extraction from point cloud based on SSV and HC-Laplacian smoothing

Zhou, Wei; Peng, Rencan; Zhang, Lihua; Wang, Wanjin

doi:10.1201/9781315212876-45

Cited by 2 publications

(1 citation statement)

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“…Extracting topographic feature lines from point cloud is proposed based on SSV(signed surface variation) and HC-Laplacian smoothing method (Zhou et al, 2016), in which the potential feature points are segmented into different clusters by region growing based on the Euclidean distance and SSV. Some automated algorithms and software of the extraction of ridges or ridge axes from DEMs are still not practical for the applications.…”

Section: Introductionmentioning

confidence: 99%

Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method

2023

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Terrain feature extraction is one of the critical issues in geographic information science. As important terrain feature lines, ridge lines and valley lines, play an important role in hydrological analysis, terrain reconstruction and automatic integration of contour lines. But, the extraction of terrain feature lines is complicated and time-consuming task. In this paper, a terrain feature line extraction method is proposed based on clustering technique. The terrain feature points are automatically extracted according to the agglomeration of terrain points, and the similar points are automatically identi ed according to the DBSCAN clustering algorithm. The points with high similarity are clustered along the direction of ridge or valley, and the whole terrain will be clustered into multiple sub-regions. The nearest sub-regions are found by calculating the minimum distance between these sub-regions, and the adjacent sub-regions are connected orderly by their center line to obtain terrain feature lines. Compared with other methods, the cluster analysis method in this paper has simple process and high e ciency.

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Section: Introductionmentioning

confidence: 99%

Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method

2023

View full text Add to dashboard Cite

show abstract

Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method

Zhang

Dou

Pang

2022

Preprint

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Terrain feature extraction is one of the critical issues in geographic information science. As important terrain feature lines, ridge lines and valley lines, play an important role in hydrological analysis, terrain reconstruction and automatic integration of contour lines. But, the extraction of terrain feature lines is complicated and time-consuming task. In this paper, a terrain feature line extraction method is proposed based on clustering technique. The terrain feature points are automatically extracted according to the agglomeration of terrain points, and the similar points are automatically identified according to the DBSCAN clustering algorithm. The points with high similarity are clustered along the direction of ridge or valley, and the whole terrain will be clustered into multiple sub-regions. The nearest sub-regions are found by calculating the minimum distance between these sub-regions, and the adjacent sub-regions are connected orderly by their center line to obtain terrain feature lines. Compared with other methods, the cluster analysis method in this paper has simple process and high efficiency.

show abstract

Topographic feature line extraction from point cloud based on SSV and HC-Laplacian smoothing

Cited by 2 publications

References 1 publication

Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method

Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method

Extraction of terrain ridge lines and valley lines based on agglomeration analysis of terrain points: a cluster analysis method

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