Dr. Jennifer L. Dungan Profile

Dr. Jennifer L. Dungan

Scientist at NASA Ames Research Ctr

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Proceedings Article | 4 November 2004 Paper

Specifying EO satellite campaign requests to meet science goals

Jennifer Dungan, Robert Morris

Proceedings Volume 5570, (2004) https://doi.org/10.1117/12.570286

KEYWORDS: Sensors, Satellites, Earth observing sensors, Data acquisition, Earth sciences, Vegetation, Databases, Clouds, Computer architecture, MODIS

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In the past decade, the number of Earth observation satellites has burgeoned. EO missions have been conceived to study different aspects and interacting pieces of the Earth system and scientists are designing increasingly complex, interdisciplinary campaigns to exploit multiple EO assets. In general, each EO mission has its own observation scheduling system, leading to a diverse array of specialized scheduling systems each tailored to a mission's unique requirements and characteristics. There is therefore the opportunity to allow planning and scheduling algorithms to assist a scientist requesting a set of observations, optimized over multiple sensors, to meet a science goal. This paper addresses the formal specification of a request to allow such algorithms to be exploited. The most basic parameters of a campaign request include the list of sensors required or desired in combination with the time frames or intervals and geographic regions for which the observation(s) are needed. Temporal and geographic parameters may be dependent on exogenous events, such as the occurrence of a fire, hurricane, volcanic eruption, or seasonal event. The scientist would also like to specify constraints on the needed quality of observations (e.g. cloud cover) and may have dependencies between parameters. Fulfilling preferences (e.g. new data are preferable to older data) may improve the quality of subsequent scientific analysis. The cost of the set of observations will also be an important contraint. In this paper, we propose a structure for expressing these parameters and constraints. We use a fire emissions model validation campaign as illustration.

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