Hierarchical Classification of Urban ALS Data by Using Geometry and Intensity Information.

Liu, Xiaoqiang; Chen, Yanming; Li, Shuyi; Cheng, Liang; Li, Manchun

Liu, Xiaoqiang; Chen, Yanming; Li, Shuyi; Cheng, Liang; Li, Manchun.

Afiliação

Liu X; School of Geography and Ocean Science, Nanjing University, Nanjing 210093, China.
Chen Y; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, China.
Li S; School of Geography and Ocean Science, Nanjing University, Nanjing 210093, China. chenyanming@nju.edu.cn.
Cheng L; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, China. chenyanming@nju.edu.cn.
Li M; Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing, China. chenyanming@nju.edu.cn.

Sensors (Basel) ; 19(20)2019 Oct 21.

Article em En | MEDLINE | ID: mdl-31640270

Palavras-chave

airborne laser scanning; geometry; hierarchical classification; intensity; supervised learning; unsupervised learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

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