利用卫星图像进行降水临近预报Precipitation Nowcasting with Satellite Imagery |
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课程网址: | http://videolectures.net/kdd2019_lebedev_ivashkin_rudenko/ |
主讲教师: | Alexander Ganshin |
开课单位: | 扬德克斯 |
开课时间: | 2020-03-02 |
课程语种: | 英语 |
中文简介: | 降水预报是雨雪的短期预报(最长2小时),通常由气象部门显示在地理图顶部。现代降水预报算法依赖于地面雷达通过光流技术或神经网络模型外推观测值。根据这些雷达,典型的即时广播仅限于其位置周围的区域。我们开发了一种基于地球同步卫星图像的降水量预报方法,并将结果数据纳入Yandex。天气降水图(包括Yandex生态系统中产品推送通知的警报服务),从而扩大其覆盖范围,为真正的全球即时广播服务铺平道路。 |
课程简介: | Precipitation nowcasting is a short-range forecast of rain/snow (up to 2 hours), often displayed on top of the geographical map by the weather service. Modern precipitation nowcasting algorithms rely on the extrapolation of observations by ground-based radars via optical flow techniques or neural network models. Dependent on these radars, typical nowcasting is limited to the regions around their locations. We have developed a method for precipitation nowcasting based on geostationary satellite imagery and incorporated the resulting data into the Yandex.Weather precipitation map (including an alerting service with push notifications for products in the Yandex ecosystem), thus expanding its coverage and paving the way to a truly global nowcasting service. |
关 键 词: | 利用卫星图像; 降水临近预报; 数据科学 |
课程来源: | 视频讲座网 |
数据采集: | 2022-09-19:cyh |
最后编审: | 2022-09-19:cyh |
阅读次数: | 122 |