Every spring the mechanical river ice break-up and associated ice-runs or flooding pose a threat to communities at Northern latitudes. Monitoring and mitigation efforts along remote Arctic rivers are possible but logistically complex. In recent years, Earth observation programs have emerged based on spaceborne sensors that record large parts of the Earth’s surface at a regular interval and with fast downlink. Most optical satellites have a similar sun-synchronous orbit, and have thus an akin ground track. When different sun-synchronous missions are combined this results in near-simultaneous acquisitions, which make it possible to monitor fast displacements that occur at or near the Earth’s surface over large scales. Hence, it becomes possible to generate a new monitoring system; one of observing river ice movement. In this study we demonstrate the feasibility of a multi-satellite monitoring system by combining data from freely available medium- and coarse-resolution satellites, in this study that is Sentinel-2 and PROBA-V. Velocities of floating river ice during the spring of 2016 are estimated over a more than 700 km long reach of the Lena River in Russia. In order to achieve automatic velocity estimates at such scales, efficient and river-ice specific processing steps are included. Entropy filters are used to detect regions of high contrast and neglects open water or an intact ice cover, and also help the image matching. Post-processing is done through filtering on the general flow direction, stemming from a global river mask dataset. In all, this study shows the potential of extracting river ice movement from a combination of low and medium resolution satellite sensors in sun-synchronous orbit.

每年春天，机械性的河冰破裂和相关的冰流或洪水都会威胁到北纬地区的社区。可以在偏远的北极河上进行监测和缓解工作，但后勤工作十分复杂。近年来，基于星载传感器的地球观测计划应运而生，这些星载传感器以规则的间隔和快速的下行链路记录地球表面的大部分。大多数光学卫星具有类似的太阳同步轨道，因此具有类似的地面轨迹。当组合执行不同的太阳同步任务时，这将导致近同时采集，这使得有可能监视大规模发生在地球表面或附近的快速位移。因此，有可能产生一个新的监测系统。观察河冰运动之一。在这项研究中，我们通过结合来自Sentinel-2和PROBA-V的免费提供的中分辨率和粗分辨率卫星的数据，证明了多卫星监视系统的可行性。据估计，2016年春季，俄罗斯列纳河（Lena River）长700公里以上的河冰漂浮速度。为了在这种规模上实现自动速度估算，包括了有效的和河冰特定的处理步骤。熵过滤器用于检测高对比度区域，而忽略了开阔水域或完整的冰盖，还有助于图像匹配。后处理是通过对总体流向进行过滤来完成的，而该过滤是基于全局河面遮罩数据集进行的。在所有，