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MODIS Science Algorithms and Data Systems Lessons Learned

机译:MODIS科学算法和数据系统的经验教训

摘要

For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.
机译:近十年来,NASA的地球观测系统(EOS)的两个中等分辨率成像光谱仪(MODIS)传感器的全球标准产品在全球范围内用于地球科学研究和应用。本文讨论了开发科学算法和数据系统所需的经验教训,这些算法和数据系统是为地球科学界生产这些高质量数据产品所必需的。强大的科学团队领导和沟通能力,可扩展且可扩展的数据系统以及质量保证和验证活动的集中协调使该数据系统从最初的启动系统到当前系统都可以增长两个数量级,从而能够从这两个系统重新处理数据在不到一年的时间内完成了Terra和Aqua任务。从MODIS汲取的许多教训已被应用于后续任务。

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