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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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Principais autores: Liya Zhao, François Waldner, Peter Scarth, Benjamin Mack, Zvi Hochman
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2020-04-01
Serier:Remote Sensing
Fag:
sentinel-2
biased support vector machine
cover fractions
classification
agriculture
crop emergence
Online adgang:https://www.mdpi.com/2072-4292/12/8/1337
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