Land Cover Classification from Very High-Resolution UAS Data for Flood Risk Mapping

Monitoring the world’s areas that are more vulnerable to natural hazards has become crucial worldwide. In order to reduce disaster risk, effective tools and relevant land cover (LC) data are needed. This work aimed to generate a high-resolution LC map of flood-prone rural villages in southwest Niger...

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Detalles Bibliográficos
Autores principales: Belcore, Elena, Piras, Marco, Pezzoli, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370894/
https://www.ncbi.nlm.nih.gov/pubmed/35957173
http://dx.doi.org/10.3390/s22155622

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370894/
https://www.ncbi.nlm.nih.gov/pubmed/35957173
http://dx.doi.org/10.3390/s22155622

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