RaVÆn: unsupervised change detection of extreme events using ML on-board satellites

RaVÆn: unsupervised change detection of extreme events using ML on-board satellites

Introduction Satellite observations of the Earth’s surface provide vital data for diverse environmental applications, including disaster management 1 , 2 , landcover change detection 3 , and ecological 4 , urban 5 and agricultural 6 monitoring. Currently, Earth observation (EO) satellites collect and downlink raw or low-compression-rate images for further processing on the ground 7 . Limitations in downlink capacity and speed result in delayed data availability and inefficient use of ground stations. This adversely impacts time-sensitive applications such […]

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