R. Gibb, M. Purss, Z. Sabeur, P. Strobl, Tengteng Qu
{"title":"Global Reference Grids for Big Earth Data","authors":"R. Gibb, M. Purss, Z. Sabeur, P. Strobl, Tengteng Qu","doi":"10.1080/20964471.2022.2113037","DOIUrl":null,"url":null,"abstract":"The emerging field of Discrete Global Grid Systems (DGGS) provides a way to organise, store and analyse spatio-temporal data at multiple resolutions and scales (from near global scales down to microns). DGGS partition the entire planet into a discrete hierarchy of global tessellations of progressively finer resolution zones (or cells). Data integration, decomposition and aggregation are optimised by assigning a unique spatio-temporal identifier to each zone. These identifiers are encodings of both the zone’s location and its resolution. As a result, complex multi-dimensional, multi-resolution spatio-temporal operations are simplified into sets of 1D array and filter operations. DGGS are therefore particularly suited for efficient multi-source data processing, storage, discovery, transmis-sion, visualisation, computation, analysis, and modelling. DGGS are supported by both the Open Geospatial Consortium (OGC) and the International Organization for Standardization (ISO) TC211 standards (OGC Abstract Specification – Topic 21 1 , ISO 19170-1 2 ). These published specifications support 2D equal-area DGGS of the Earth’s surface. Current work led through both OGC and ISO/TC-211 is drafting standards to specify 3D (3D & equi-volume) 3 , 4D (spatio-temporal) 4 and axis-aligned 5 DGGS, as well as OGC API DGGS 6 , 7 interface encodings for DGGS infrastructures. The continued effort to develop international standards for DGGS will support the implementation of standardised interoper-able Global Reference Grid Infrastructures that can support efficient and scalable integration of Big Earth Data across multiple organisations around the world. we global","PeriodicalId":8765,"journal":{"name":"Big Earth Data","volume":"10 1","pages":"251 - 255"},"PeriodicalIF":4.2000,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Earth Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/20964471.2022.2113037","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 4
Abstract
The emerging field of Discrete Global Grid Systems (DGGS) provides a way to organise, store and analyse spatio-temporal data at multiple resolutions and scales (from near global scales down to microns). DGGS partition the entire planet into a discrete hierarchy of global tessellations of progressively finer resolution zones (or cells). Data integration, decomposition and aggregation are optimised by assigning a unique spatio-temporal identifier to each zone. These identifiers are encodings of both the zone’s location and its resolution. As a result, complex multi-dimensional, multi-resolution spatio-temporal operations are simplified into sets of 1D array and filter operations. DGGS are therefore particularly suited for efficient multi-source data processing, storage, discovery, transmis-sion, visualisation, computation, analysis, and modelling. DGGS are supported by both the Open Geospatial Consortium (OGC) and the International Organization for Standardization (ISO) TC211 standards (OGC Abstract Specification – Topic 21 1 , ISO 19170-1 2 ). These published specifications support 2D equal-area DGGS of the Earth’s surface. Current work led through both OGC and ISO/TC-211 is drafting standards to specify 3D (3D & equi-volume) 3 , 4D (spatio-temporal) 4 and axis-aligned 5 DGGS, as well as OGC API DGGS 6 , 7 interface encodings for DGGS infrastructures. The continued effort to develop international standards for DGGS will support the implementation of standardised interoper-able Global Reference Grid Infrastructures that can support efficient and scalable integration of Big Earth Data across multiple organisations around the world. we global