Conceptualizing the analysis-readiness for the next-generation SDI through the Open Geospatial Engine (OGE).
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| Title: | Conceptualizing the analysis-readiness for the next-generation SDI through the Open Geospatial Engine (OGE). |
|---|---|
| Authors: | Yue, Peng1,2,3 (AUTHOR) pyue@whu.edu.cn, Wu, Haoru1,4,5 (AUTHOR), Liu, Ruixiang1 (AUTHOR), Gong, Jianya1 (AUTHOR), Xiang, Longgang6 (AUTHOR), Wang, Kaixuan1 (AUTHOR), Teng, Baoxin1 (AUTHOR) |
| Source: | International Journal of Remote Sensing. Apr2026, Vol. 47 Issue 7, p2962-2996. 35p. |
| Subjects: | Spatial data infrastructures, Geospatial data, Remote sensing, Cloud computing |
| Abstract: | The rapid advancement of Earth Observation (EO) technologies has led to an unprecedented surge in geospatial big data. This motivates an efficient infrastructure for storage, processing, and analysis of geospatial big data. There are two promising ways for approaching this, data readiness and infrastructure readiness. The former one is the notably existing Analysis-ready Data (ARD) effort. The other is the analysis-ready SDI (Spatial Data Infrastructure) proposed in this paper. The paper conceptualizes an analysis-ready SDI following a four-layer readiness framework – GeoData, GeoComputation, GeoAI, and GeoService. It involves traditional SDI into a spatiotemporal big data infrastructure that integrates data, algorithms, and computing power into a distributed framework for intelligent geospatial services. The conceptualization is approached through OGE (Open Geospatial Engine), which is a cloud-native platform that integrates storage, distributed computing, AI-driven geospatial inference, and standardized services. It helps establish a next-generation SDI ready for analysing massive Earth spatiotemporal data. The applicability is demonstrated through a series of applications in global data analysis, quantitative remote sensing analysis, GeoAI inference, 3D analysis, etc. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Remote Sensing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 192728784 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Conceptualizing the analysis-readiness for the next-generation SDI through the Open Geospatial Engine (OGE). – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yue%2C+Peng%22">Yue, Peng</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> pyue@whu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Haoru%22">Wu, Haoru</searchLink><relatesTo>1,4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Ruixiang%22">Liu, Ruixiang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gong%2C+Jianya%22">Gong, Jianya</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xiang%2C+Longgang%22">Xiang, Longgang</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Kaixuan%22">Wang, Kaixuan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Teng%2C+Baoxin%22">Teng, Baoxin</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Remote+Sensing%22">International Journal of Remote Sensing</searchLink>. Apr2026, Vol. 47 Issue 7, p2962-2996. 35p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Spatial+data+infrastructures%22">Spatial data infrastructures</searchLink><br /><searchLink fieldCode="DE" term="%22Geospatial+data%22">Geospatial data</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The rapid advancement of Earth Observation (EO) technologies has led to an unprecedented surge in geospatial big data. This motivates an efficient infrastructure for storage, processing, and analysis of geospatial big data. There are two promising ways for approaching this, data readiness and infrastructure readiness. The former one is the notably existing Analysis-ready Data (ARD) effort. The other is the analysis-ready SDI (Spatial Data Infrastructure) proposed in this paper. The paper conceptualizes an analysis-ready SDI following a four-layer readiness framework – GeoData, GeoComputation, GeoAI, and GeoService. It involves traditional SDI into a spatiotemporal big data infrastructure that integrates data, algorithms, and computing power into a distributed framework for intelligent geospatial services. The conceptualization is approached through OGE (Open Geospatial Engine), which is a cloud-native platform that integrates storage, distributed computing, AI-driven geospatial inference, and standardized services. It helps establish a next-generation SDI ready for analysing massive Earth spatiotemporal data. The applicability is demonstrated through a series of applications in global data analysis, quantitative remote sensing analysis, GeoAI inference, 3D analysis, etc. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Remote Sensing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/01431161.2026.2625516 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 35 StartPage: 2962 Subjects: – SubjectFull: Spatial data infrastructures Type: general – SubjectFull: Geospatial data Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Cloud computing Type: general Titles: – TitleFull: Conceptualizing the analysis-readiness for the next-generation SDI through the Open Geospatial Engine (OGE). Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yue, Peng – PersonEntity: Name: NameFull: Wu, Haoru – PersonEntity: Name: NameFull: Liu, Ruixiang – PersonEntity: Name: NameFull: Gong, Jianya – PersonEntity: Name: NameFull: Xiang, Longgang – PersonEntity: Name: NameFull: Wang, Kaixuan – PersonEntity: Name: NameFull: Teng, Baoxin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 01431161 Numbering: – Type: volume Value: 47 – Type: issue Value: 7 Titles: – TitleFull: International Journal of Remote Sensing Type: main |
| ResultId | 1 |
