Maintaining accurate, current, rural road network data: An extraction and updating routine using RapidEye, participatory GIS and deep learning

Accurate and current road network data is fundamental to land management and emergency response, yet challenging to produce for unpaved roads in rural and forested regions using traditional cartographic approaches. Automatic extraction of roads from satellite imagery using deep learning is a promisi...

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Detalhes bibliográficos

Principais autores:	Sean P. Kearney, Nicholas C. Coops, Simran Sethi, Gordon B. Stenhouse
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2020-05-01
coleção:	International Journal of Applied Earth Observations and Geoinformation
Assuntos:	Convolutional neural network Road extraction Machine learning Forest road networks Ursus arctos Remote sensing
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S0303243419309882
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