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全球1m分辨率冠层高度数据由meta公司利用深度学习方法制作,卫星影像由Maxar公司提供,数据获取时间为2017-2020。这是当前全球范围内最精细的树冠高度数据。 • Very high resolution canopy height maps at jurisdictional scale are released. • Improved performance from vision transformers based on Self-Supervised Learning (SSL). • First use of SSL and vision transformers for canopy height estimation. • Low resolution GEDI and high resolution aerial lidar predictions are combined. • Model generalizes well to aerial imagery, even though trained with satellite images. 作者称其精度为" Mean Absolute Error (MAE) of 2.8 m and Mean Error (ME) of 0.6 m". 全球1m分辨率冠层高度数据简单介绍及下载方法参照: AI驱动全球森林\树冠高度地图,以及1米数据下载教程 。 数据生产方法及详细介绍参照文章: Using Artificial Intelligence to Map the Earth’s Forests.https://sustainability.f
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