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- W2034270282 abstract "The exploitation of new high revisit frequency earth observations by the future Sentinel-2 satellite is clearly an important opportunity for global agricultural monitoring. In this context, the Sentinel-2Agriculture project aims at producing algorithms working on large geographical areas having different climates and different agricultural systems. In the framework of this project, the construction of a near-real-time deliverable cropland mask product has been studied here. A set of 12 selected test sites are used to benchmark the proposed method with regard to the diversity of agro-ecological context, the various landscape patterns, the different agriculture practices and the actual satellite observation conditions. The classification results yield very promising accuracies achieving around 90 % at the end of the agricultural season." @default.
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- W2034270282 date "2015-07-01" @default.
- W2034270282 modified "2023-09-30" @default.
- W2034270282 title "Processing Sentinel-2 image time series for developing a real-time cropland mask" @default.
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- W2034270282 doi "https://doi.org/10.1109/igarss.2015.7326378" @default.
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