Unsupervised machine learning with different sampling strategies and topographic factors for distinguishing between landslide source and runout areas to improve landslide inventory production

This study derived 12 topographical and hydrological factors related to landslides from a 10-m digital elevation model. Three unsupervised machine learning algorithms were employed to distinguish between the features of landslide sources and runout areas for Typhoon Morakot. Two sampling strategies...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Jhe-Syuan Lai, Jun-Yi Huang, Hong-Mao Huang, Yung-Chung Chuang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Taylor & Francis Group 2024-12-01
coleção:	Geomatics, Natural Hazards & Risk
Assuntos:	Clustering landslide inventory machine learning sampling strategy topographic factors
Acesso em linha:	https://www.tandfonline.com/doi/10.1080/19475705.2024.2406302
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!