A spatiotemporal ensemble machine learning framework for generating land use/land cover time-series maps for Europe (2000–2019) based on LUCAS, CORINE and GLAD Landsat

A spatiotemporal machine learning framework for automated prediction and analysis of long-term Land Use/Land Cover dynamics is presented. The framework includes: (1) harmonization and preprocessing of spatial and spatiotemporal input datasets (GLAD Landsat, NPP/VIIRS) including five million harmoniz...

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Detalles Bibliográficos
Autores principales: Witjes, Martijn, Parente, Leandro, van Diemen, Chris J., Hengl, Tomislav, Landa, Martin, Brodský, Lukáš, Halounova, Lena, Križan, Josip, Antonić, Luka, Ilie, Codrina Maria, Craciunescu, Vasile, Kilibarda, Milan, Antonijević, Ognjen, Glušica, Luka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Data Mining and Machine Learning
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308969/
https://www.ncbi.nlm.nih.gov/pubmed/35891647
http://dx.doi.org/10.7717/peerj.13573

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308969/
https://www.ncbi.nlm.nih.gov/pubmed/35891647
http://dx.doi.org/10.7717/peerj.13573

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