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Effects of training data size and composition on the classification of irrigated agriculture in Sub-Saharan Africa through remote sensing using four algorithms.

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training-data-size-and-composition

Effects of training data size and composition on the classification of irrigated agriculture in Sub-Saharan Africa through remote sensing using four algorithms.

Python scripts are used in Digital Earth Africa sandbox (https://sandbox.digitalearth.africa/hub/login) to create the raster data. R script is used for classification. Visualisation scripts are not shared, mostly done through ggplot2.

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Effects of training data size and composition on the classification of irrigated agriculture in Sub-Saharan Africa through remote sensing using four algorithms.

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