Agricultural Land Cover Mapping through Two Deep Learning Models in the Framework of EU’s CAP Activities Using Sentinel-2 Multitemporal Imagery

The images of the Sentinel-2 constellation can help the verification process of farmers’ declarations, providing, among other things, accurate spatial explicit maps of the agricultural land cover. The aim of the study is to design, develop, and evaluate two deep learning (DL) architectures tailored...

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Detalles Bibliográficos

Principais autores:	Eleni Papadopoulou, Giorgos Mallinis, Sofia Siachalou, Nikos Koutsias, Athanasios C. Thanopoulos, Georgios Tsaklidis
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2023-09-01
Series:	Remote Sensing
Assuntos:	crop classification entropy land cover mapping neural networks random forest remote sensing
Acceso en liña:	https://www.mdpi.com/2072-4292/15/19/4657
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