Integrating image filters and confidence thresholds to improve cropland data layer for deep learning–based cropland segmentation

Accurate cropland segmentation is essential for agricultural monitoring, with deep learning (DL) models relying heavily on training data quality. The USDA’s Cropland Data Layer (CDL) is widely used for this purpose, but it includes classification errors and noise. Although a confidence layer is prov...

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Autores principales:	Reza Maleki, Falin Wu, Guoxin Qu, Yushuang Liu, Amel Oubara, Gongliu Yang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Taylor & Francis Group 2026-12-01
Colección:	European Journal of Remote Sensing
Materias:	Cropland Data Layer (CDL) confidence layer image filter deep learning Sentinel–2 agricultural monitoring
Acceso en línea:	https://www.tandfonline.com/doi/10.1080/22797254.2026.2631928
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