Earth observation analytics have the potential to transform many sectors. However, due to limited ground connections, it currently takes hours to days to download and analyze Earth observation data, diminishing the value of data for time-sensitive applications like disaster monitoring or search-and-rescue. To enable real-time analytics, we propose OrbitChain, an in-orbit multi-satellite Earth analytics framework. OrbitChain uses a pipelined design to decompose workflows into analytics functions, and orchestrates constellation-wide resources to finish real-time analytics tasks. It provides timely insights to Earth sensing applications and enables advanced workflows like in-orbit tip-and-cue. Hardware-in-the-loop experiments show that OrbitChain can deliver analytics results in minutes, supports up to 60% more analytics workload than existing frameworks, and reduces inter-satellite communication overhead by up to 45%.

翻译：地球观测分析具有变革众多领域的潜力。然而，由于地面连接有限，目前下载和分析地球观测数据需要数小时至数天，这降低了数据在灾害监测或搜救等时效性应用中的价值。为实现实时分析，我们提出了OrbitChain，一种在轨多卫星地球分析框架。OrbitChain采用流水线设计将工作流分解为分析功能，并通过编排整个星座的资源来完成实时分析任务。它为地球传感应用提供及时洞察，并支持在轨提示与引导等高级工作流。硬件在环实验表明，OrbitChain可在数分钟内交付分析结果，比现有框架多支持高达60%的分析负载，并将星间通信开销降低达45%。