Abstract
The article discusses the experience of using machine learning methods (gradient boosting, deep neural networks) for cloud detection and mapping on the example of the Perm Region using high spatial resolution images in visible range (Sentinel-2). With existing cloud detection algorithms (Fmask, Sen2Cor) Comparisons are made, as well as with the basic cloud mask provided with Sentinel-2 images. For automatic production of cartographic data Python script in the ArcGIS environment was cones fad.
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