EASE-DGGS:a hybrid discrete global grid system for Earth sciences

查看全文 作　　者：Jeffery [1,2]A.Thompson;Mary [3]J.Brodzik;Kevin [1,2]A.T.Silverstein;Mason [2]A.Hurley;Nathan [1]L.Carlson

机构地区：[1]Minnesota Supercomputing Institute,University of Minnesota,Minneapolis,MN,USA;[2]GEMS Informatics Initiative,University of Minnesota,Minneapolis,MN,USA;[3]National Snow and Ice Data Center,Cooperative Institute for Research in Environmental Sciences,University of Colorado,Boulder,CO,USA

出　　处：《Big Earth Data》索引2022年第6卷第3期,共18页

摘　　要：Although we live in an era of unprecedented quantities and access to data,deriving actionable information from raw data is a hard problem.Earth observation systems(EOS)have experienced rapid growth and uptake in recent decades,and the rate at which we obtain remotely sensed images is increasing.While significant effort and attention has been devoted to designing systems that deliver analytics ready imagery faster,less attention has been devoted to developing analytical frameworks that enable EOS to be seamlessly integrated with other data for quantitative analysis.Discrete global grid systems(DGGS)have been proposed as one potential solution that addresses the challenge of geospatial data integration and interoperability.Here,we propose the systematic extension of EASE-Grid in order to provide DGGS-like characteristics for EOS data sets.We describe the extensions as well as present implementation as an application programming interface(API),which forms part of the University of Minnesota’s GEMS(Genetic x Environment x Management x Socioeconomic)Informatics Center’s API portfolio. 关键词：Discrete global grid systems DGGS EASE Grid coordinate reference systems

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EASE-DGGS:a hybrid discrete global grid system for Earth sciences

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