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Erschienen in: Cluster Computing 4/2019

05.01.2018

The data analysis of roughness extraction of target topography using minimum median plane fitting method

verfasst von: Qiangfeng Wang, Yan Cao, Yu Bai, Yujia Wu, Qingyun Wu

Erschienen in: Cluster Computing | Sonderheft 4/2019

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Abstract

According to the problem that the elevation data does not reflect the slope and surface roughness of target topography, the preprocessing of topographic elevation data and extraction algorithm of topographic feature are proposed, and the corresponding extraction of topographic feature is done. A terrain risk assessment method is presented based on terrain roughness and slope information fusion, aiming at the problem that terrain roughness and gradient cannot be directly reflected from the terrain elevation data, in this paper. The innovation is that it is the first time that the bilinear interpolation algorithm is applied in preprocess of elevation data and extraction of topographic feature, as well as the terrain roughness and gradient information fusion algorithm are applied to terrain feature extraction and risk assessment for the first time. By simulation and checking calculation of a certain digital topography example, it is proved that the extraction method of topographic information based on elevation data is feasible and reliable. It will provide a new research approach for target information recognition and topography risk assessment accurately.

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Metadaten
Titel
The data analysis of roughness extraction of target topography using minimum median plane fitting method
verfasst von
Qiangfeng Wang
Yan Cao
Yu Bai
Yujia Wu
Qingyun Wu
Publikationsdatum
05.01.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 4/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1582-0

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