Impact of Training Set Size and Lead Time on Early Tomato Crop Mapping Accuracy

Estimating key crop parameters (e.g., phenology, yield prediction) is a prerequisite for optimizing agrifood supply chains through the use of satellite imagery, but requires timely and accurate crop mapping. The moment in the season and the number of training sites used are two main drivers of crop...

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Detalles Bibliográficos

Principais autores:	Michele Croci, Giorgio Impollonia, Henri Blandinières, Michele Colauzzi, Stefano Amaducci
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2022-09-01
Series:	Remote Sensing
Assuntos:	lead time Sentinel-2 training set size RSM machine learning agrifood supply chains
Acceso en liña:	https://www.mdpi.com/2072-4292/14/18/4540
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