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dc.contributor.authorZheng, Jianyu
dc.contributor.authorHuang, Xin
dc.contributor.authorSangondi, Supriya
dc.contributor.authorWang, Jianwu
dc.contributor.authorZhang, Zhibo
dcterms.creatorhttps://orcid.org/0000-0003-3886-7913en_US
dcterms.creatorhttps://orcid.org/0000-0002-9933-1170en_US
dcterms.creatorhttps://orcid.org/0000-0001-9491-1654en_US
dc.date.accessioned2022-05-03T14:19:10Z
dc.date.available2022-05-03T14:19:10Z
dc.date.issued2021-09-06
dc.description.abstractMODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument onboard NASA’s Terra (launched in 1999) and Aqua (launched in 2002) satellite missions as part of the more extensive Earth Observation System (EOS). By measuring the reflection and emission by the Earth-Atmosphere system in 36 spectral bands from the visible to thermal infrared with near-daily global coverage and high-spatial-resolution (250 m ~ 1 km at nadir), MODIS is playing a vital role in developing validated, global, interactive Earth system models. MODIS products are processed into three levels, i.e., Level-1 (L1), Level-2 (L2) and Level-3 (L3). To shift the current static and “one-size-fits-all” data provision method of MODIS products, in this paper, we propose a service-oriented flexible and efficient MODIS aggregation framework. Using this framework, users only need to get aggregated MODIS L3 data based on their unique requirements and the aggregation can run in parallel to achieve a speedup. The experiments show that our aggregation results are almost identical to the current MODIS L3 products and our parallel execution with 8 computing nodes can work 88.63 times faster than a serial code execution on a single node.en_US
dc.description.sponsorshipThis work is supported by the NASA CMAC program (Grant No. 80NSSC18K0796) and the NSF CyberTraining program (Grant No. OAC-1730250). The computational resources are provided by the UMBC High Performance Computing Facility (HPCF) which was supported by the U.S. National Science Foundation through the MRI program (Grant Nos. CNS–0821258, CNS–1228778, and OAC–1726023) and the SCREMS program (Grant No. DMS–0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). See hpcf.umbc.edu for more information on HPCF and the projects using its resources.en_US
dc.description.urihttps://www.mdpi.com/2072-4292/13/17/3541en_US
dc.format.extent17 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2wwja-3ohk
dc.identifier.citationZheng, J.; Huang, X.;Sangondimath, S.;Wang, J.; Zhang, Z. Efficient and Flexible Aggregationand Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Framework. Remote Sens. 2021, 13,3541. https://doi.org/10.3390/rs13173541en_US
dc.identifier.urihttps://doi.org/10.3390/rs13173541
dc.identifier.urihttp://hdl.handle.net/11603/24665
dc.language.isoen_USen_US
dc.publisherMDPIen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Information Systems Department
dc.relation.ispartofUMBC Physics Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.titleEfficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Frameworken_US
dc.typeTexten_US


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This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
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