Classification of protected grassland habitats using deep learning architectures on Sentinel-2 satellite imagery data

Classification of protected grassland habitats using deep learning architectures on Sentinel-2 satellite imagery data

This study examines the effectiveness of five deep learning models—ViTb-19, SwinV2-t, VGG-16, ResNet-50, and DenseNet-121—in distinguishing different vegetation types in the protected grasslands of Castilla y León region, Spain, following the guidelines of the Natura 92/43/CEE directive. Among the m...

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Bibliographische Detailangaben
Hauptverfasser: Gabriel Díaz-Ireland, Derya Gülçin, Aida López-Sánchez, Eduardo Pla, John Burton, Javier Velázquez
Format: Artikel
Sprache:English
Veröffentlicht: Elsevier 2024-11-01
Schriftenreihe:International Journal of Applied Earth Observations and Geoinformation
Schlagworte:
Machine learning
Computer vision
Satellite
Transformer
Grasslands
Online Zugang:http://www.sciencedirect.com/science/article/pii/S1569843224005776

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http://www.sciencedirect.com/science/article/pii/S1569843224005776

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