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Updated: Jan 13, 2026

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一个基于水类型的光学深度学习框架,用于从Sentinel-2图像中对内陆水域的增强度估计

Yue Ma1, Qiuyue Chen1, Kaishan Song2

  • 1School of Geomatics and Prospecting Engineering, Jilin Jianzhu University, Changchun 130118, China.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

这项研究引入了一种新的深度学习方法,用于使用Sentinel-2数据估计水的度. 该方法通过光学分类水类来准确地绘制度图,增强用于水质监测的遥感.

关键词:
这是"卫星卫星-2"的图像.深度学习模型深度学习模型光学水类型的水类型度估计 度估计

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