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Autonomous detection of cryospheric change with hyperion on-board Earth Observing-1

机译:Hyperion机载Earth Observing-1自动检测冰冻圈变化

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On-board detection of cryospheric change in sea ice, lake ice, and snow cover is being conducted as part of the Autonomous Sciencecraft Experiment (ASE), using classifiers developed for the Hyperion hyper-spectral visible/infrared spectrometer on-board the Earth Observing-1 (EO-I) spacecraft. This classifier development was done with consideration for the novel limitations of on-board processing, data calibration, spacecraft targeting error and the spectral range of the instrument. During on-board tests, these algorithms were used to measure the extent of cloud, snow, and ice cover at a global suite of targets. Coupled with baseline imaging, uploaded thresholds were used to detect cryospheric changes such as the freeze and thaw of lake ice and the formation and break-up of sea ice. These thresholds were used to autonomously trigger follow-up observations, demonstrating the capability of the technique for future planetary missions where downlink is a constrained resource and there is high interest in data covering dynamic events, including cryospheric change. Before upload classifier performance was assessed with an overall accuracy of 83.3% as measured against manual labeling of 134 scenes. Performance was further assessed against field mapping conducted at Lake Mendota, Wisconsin as well as with labeling of scenes that were classified during on-board tests. (c) 2006 Elsevier Inc. All rights reserved.
机译:作为自主科学技术实验(ASE)的一部分,正在使用机载的海冰,湖冰和积雪的冰冻圈变化进行机载探测,该机使用为地球观测仪上的Hyperion高光谱可见/红外光谱仪开发的分类器-1(EO-I)航天器。考虑到机载处理,数据校准,航天器瞄准误差和仪器光谱范围的新颖局限性,完成了该分类器的开发。在机载测试期间,这些算法用于测量全球目标套件中的云,雪和冰盖的程度。结合基线成像,使用上载的阈值来检测冰冻圈变化,例如湖冰的冻结和融化以及海冰的形成和破裂。这些阈值用于自主触发后续观察,从而证明了该技术在未来的行星飞行任务中的能力,在这些任务中,下行链路是资源受限的领域,人们对涵盖冰冻圈变化等动态事件的数据非常感兴趣。上载分类器之前,对134个场景进行人工标记后,评估的总体准确性为83.3%。根据威斯康星州门多塔湖(Lake Mendota)进行的野外制图以及在机载测试中分类的场景标签,进一步评估了性能。 (c)2006 Elsevier Inc.保留所有权利。

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