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A dynamic and generic cloud computing model for glaciological image processing

机译:用于冰川图像处理的动态通用云计算模型

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As satellite imaging is quite expensive, and because of poor weather conditions including common heavy cloud cover at polar latitudes, daily satellite imaging is not always accessible or suitable to observe fast temporal evolutions. We complement satellite imagery with a set of ground based autonomous automated digital cameras which take three pictures a day. With these pictures we build a mosaic with their projection and apply a classification to define the temporal evolution of the snow cover. As the pictures are subject to heavy disturbance, some processing is needed to build the mosaic. Once the processes are defined, we present our model. This model is built upon a cloud computing environment using Web services workflow. Then we present how the processes are dynamically organized using a scheduler. This scheduler chooses the order and the processes to apply to every picture to build the mosaic. Once we obtain a mosaic we can study the variation of the snow cover.
机译:由于卫星成像非常昂贵,并且由于恶劣的天气条件(包括极地纬度上常见的厚云层),每天的卫星成像并不总是可以访问或适合于观察快速的时间演变。我们用一组每天拍摄三张照片的地面自主自动数码相机来补充卫星图像。利用这些图片,我们用它们的投影构建马赛克,并应用分类来定义积雪的时间演变。由于图片受到严重干扰,因此需要一些处理来构建马赛克。定义流程后,我们将介绍模型。该模型基于使用Web服务工作流的云计算环境。然后,我们介绍如何使用调度程序动态组织流程。该调度程序选择要应用于每张图片以构建马赛克的顺序和过程。一旦获得马赛克,就可以研究积雪的变化。

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