urban_emissions:使用卫星和街道图像预测城市排放

上传者: 42118770 | 上传时间: 2022-10-28 14:57:32 | 文件大小: 334.24MB | 文件类型: ZIP
使用卫星和街道图像预测城市排放 描述 该项目通过使用卷积神经网络(CNN)来研究城市地区臭氧浓度水平与其物理特征之间的关系。 我们训练了两种模型,其中一种接受过卫星图像训练,以捕获更高层次的特征(例如位置的地理位置),另一种进行过街道图像训练,以学习基础特征(例如,机动车活动)。 然后将这些特征连接起来,形成一个共享的表示形式,据此可以预测该位置的臭氧水平(以十亿分之一为单位)。 代码结构 02_Scripts/目录包含用于刮擦和预处理臭氧浓度数据的代码,该数据来自 。 它还包含一个01_Data_Exploration目录,该目录包含用于可视化数据集元素(如特定数据点和具有臭氧读数的位置的地理分布)的代码。 在“图像”中,我们找到了脚本,用于从Google Earth Engine中检索卫星图像( imagery/getting_imagery_no_mask.py )和从Google

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