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RINX 2.0: A Containerized Climate Raster Information Extraction System on OpenShift Cloud Environment

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Pubblicato in:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences vol. X-G-2025 (2025), p. 391
Autore principale: Jain, Devika
Altri autori: Blossom, Jeff, Hayes, Jack, Gibson, Heike, Rifas-Shimann, Sheryl, Gold, Diane R
Pubblicazione:
Copernicus GmbH
Soggetti:
Data management
Datasets
Environmental health
Raster
Environmental research
Climatic data
Real time
Information retrieval
Massive data points
Cloud computing
Data points
Childrens health
Software packages
Humidity
Remote sensing
Photogrammetry
Software services
Data analysis
Automation
High performance computing
Efficiency
Case studies
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Abstract:RINX (Raster INformation eXtraction) 2.0 is an advanced solution for efficiently extracting climate data from large raster datasets in a cloud computing environment. Building upon the original RINX 1.0, which utilized high-performance computing clusters, RINX 2.0 leverages cloud technologies such as OpenShift and PostGIS to handle massive datasets and automate the extraction process. The system supports large-scale spatiotemporal raster extractions, processing over 158 million data points from the 15TB PRISM climate dataset. Here, we describe the architecture, methods, and tools used in RINX 2.0, including containerized environments, automated data pipelines, and integration with the New England Research Cloud. The system was deployed for the Environmental influences on Child Health Outcomes (ECHO) project, providing valuable insights into environmental health research. We present performance statistics, data management strategies, and the development of a user interface for real-time querying and visualization of results.
ISSN:2194-9042
2194-9050
DOI:10.5194/isprs-annals-X-G-2025-391-2025
Fonte:Engineering Database