Vegetation indices’ spatial prediction based novel algorithm for determining tsunami risk areas and risk values

This paper aims to propose a new algorithm to detect tsunami risk areas based on spatial modeling of vegetation indices and a prediction model to calculate the tsunami risk value. It employs atmospheric correction using DOS1 algorithm combined with k-NN algorithm to classify and predict tsunami-affe...

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Detalles Bibliográficos
Autores principales: Hartomo, Kristoko Dwi, Nataliani, Yessica, Hasibuan, Zainal Arifin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Algorithms and Analysis of Algorithms
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044244/
https://www.ncbi.nlm.nih.gov/pubmed/35494821
http://dx.doi.org/10.7717/peerj-cs.935

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044244/
https://www.ncbi.nlm.nih.gov/pubmed/35494821
http://dx.doi.org/10.7717/peerj-cs.935

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