Cloud-native geospatial data cube workflows with open-source tools

This work contains educational modules designed to reduce barriers to interacting with large, complex, cloud-hosted remote sensing datasets using open-source computational tools and software.The goal of these materials is to demonstrate and promote the rigorous investigation of n-dimensional multi-sensor satellite imagery datasets through scientific programming.These tutorials feature publicly available satellite imagery with global coverage and commonly used sensors such as optical and synthetic aperture radar data with different levels of processing.We include thorough discussions of specific data formats and demonstrate access patterns for two popular cloud infrastructure platforms (Amazon Web Services and Microsoft Planetary Computer) as well as public cloud computational resources for remote sensing data processing at Alaska Satellite Facility (ASF).

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Publication Details

Journal
Journal of Open Source Education
Published
2025-07-04
DOI
https://doi.org/10.21105/jose.00267
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Cloud-native geospatial data cube workflows with open-source tools

Deepak Cherian, Scott Henderson, R. R. Forster, Jessica Scheick et al.
Journal of Open Source Education
Data Management and Algorithms
article

Cloud-native geospatial data cube workflows with open-source tools

Deepak Cherian, Scott Henderson, R. R. Forster, Jessica Scheick, Emma Marshall
article en

Abstract

This work contains educational modules designed to reduce barriers to interacting with large, complex, cloud-hosted remote sensing datasets using open-source computational tools and software.The goal of these materials is to demonstrate and promote the rigorous investigation of n-dimensional multi-sensor satellite imagery datasets through scientific programming.These tutorials feature publicly available satellite imagery with global coverage and commonly used sensors such as optical and synthetic aperture radar data with different levels of processing.We include thorough discussions of specific data formats and demonstrate access patterns for two popular cloud infrastructure platforms (Amazon Web Services and Microsoft Planetary Computer) as well as public cloud computational resources for remote sensing data processing at Alaska Satellite Facility (ASF).

Journal of Open Source EducationVol. 8(89)
University of New Hampshire at Manchester (US), University of Washington (US), University of Utah (US)
National Aeronautics and Space Administration, University of Utah
Openalex Percentile: Top 81%
Data Management and Algorithms
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