Combining Fractional Cover Images with One-Class Classifiers Enables Near Real-Time Monitoring of Fallows in the Northern Grains Region of Australia

Fallows are widespread in dryland cropping systems. However, timely information about their spatial extent and location remains scarce. To overcome this lack of information, we propose to classify fractional cover data from Sentinel-2 with biased support vector machines. Fractional cover images desc...

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Detalhes bibliográficos

Principais autores:	Liya Zhao, François Waldner, Peter Scarth, Benjamin Mack, Zvi Hochman
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2020-04-01
coleção:	Remote Sensing
Assuntos:	sentinel-2 biased support vector machine cover fractions classification agriculture crop emergence
Acesso em linha:	https://www.mdpi.com/2072-4292/12/8/1337
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