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• W4313334096 abstract "Abstract Tailings reservoirs are an inevitable part of the production process of metal mines and are typical of post‐mining and post‐industrial lands. Tailings reservoirs are often located in mountainous areas so earth observation and remote sensing is a necessary monitoring means. However, existing observation are generally based on satellite, air or ground platforms, Combined satellite‐air‐ground observation is rare, and the coordination ability of processing methods to cope with it is insufficient. Therefore, the response to sudden major environmental and disaster events is slow and lagging. In this study, inspired by the human brain, a satellite‐air‐ground integrated multi‐source earth observation and machine learning processing system was built up for tailings reservoir stereoscopic monitoring and rapid emergency response (SAGTR). Firstly, the brain‐inspired human visual multimodal data acquisition by satellite‐air‐ground integration platform has been established to break through the traditional single‐source and single‐mode data approach and involves satellite remote sensing images, UAV hyperspectral images, and ground parameters. Moreover, it is unique among current tailings reservoir monitoring systems. In general, our proposed SAGTR framework has promise for improving the comprehensive monitoring and emergency response to tailings reservoir failures." @default.
• W4313334096 created "2023-01-06" @default.
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• W4313334096 date "2023-01-25" @default.
• W4313334096 modified "2023-09-30" @default.
• W4313334096 title "Satellite‐air‐ground integrated multi‐source earth observation and machine learning processing brain for tailings reservoir monitoring and rapid emergency response" @default.
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• W4313334096 doi "https://doi.org/10.1002/ldr.4580" @default.
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