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J.L. Vazquez-Poletti, M.P. Velasco, S. Jimenez, D. Usero, I.M. Llorente, L. Vazquez, O. Korablev, D. Belyaev, M.V. Patsaeva, I. V. Khatuntsev. Public "Cloud" Provisioning for Venus Express VMC Image Processing. Communications on Applied Mathematics and Computation, 1(2):253-261, March 2019.


In this paper, we consider the implementation of the "cloud" computing strategy to study data sets associated to the atmospheric exploration of the planet Venus. More concretely, the Venus Monitoring Camera (VMC) onboard Venus Express orbiter provided the largest and the longest so far set of ultraviolet (UV), visible and near-IR images for investigation of the atmospheric circulation. To our best knowledge, this is the first time where the analysis of data from missions to Venus is integrated in the context of the "cloud" computing. The followed path and protocols can be extended to more general cases of space data analysis, and to the general framework of the big data analysis


[ Tin2015-65469-p ] [ Cloud ]


Jose Luis Vazquez-Poletti
Ignacio M. Llorente

BibTex Reference

   Author = {Vazquez-Poletti, J.L. and Velasco, M.P. and Jimenez, S. and Usero, D. and Llorente, I.M. and Vazquez, L. and Korablev, O. and Belyaev, D. and Patsaeva, M.V. and V. Khatuntsev, I.},
   Title = {Public "Cloud" Provisioning for Venus Express VMC Image Processing},
   Journal = {Communications on Applied Mathematics and Computation},
   Volume = {1},
   Number = {2},
   Pages = {253--261},
   Month = {March},
   Year = {2019}

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