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• W2560339400 abstract "High-resolution data products from Earth observing satellites facilitate continuous monitoring of the physical, chemical, and biological processes of the Earth system. With the plethora of data made available from the foreseen dense halo of Earth observing satellites, it is of utmost importance to produce the best estimate of the Earth system state for diverse applications. This is achieved using data assimilation, which carefully considers the measurement process, its associated errors, governing equations of the system, and the expected errors in these equations. In data assimilation, sampling techniques serve as an effective means to propagate information from data-rich regions to data-poor regions. This is essential to overcome the limited spatial and temporal sampling of satellite information. Both scientists and researchers have followed various sampling schemes. This chapter summarizes some of the prominent sampling strategies, which have evolved with respect to analyzing data from Earth observing satellites. The applicability of bootstrap and Latin hypercube techniques in assessing sampling errors of Tropical Rainfall Measuring Mission orbital data are discussed as a case study." @default.
• W2560339400 created "2016-12-16" @default.
• W2560339400 creator A5018594651 @default.
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• W2560339400 date "2017-01-01" @default.
• W2560339400 modified "2023-09-28" @default.
• W2560339400 title "Making the Most of the Earth Observation Data Using Effective Sampling Techniques" @default.
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• W2560339400 doi "https://doi.org/10.1016/b978-0-12-803011-0.00013-6" @default.
• W2560339400 hasPublicationYear "2017" @default.
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