Scalable and Interoperable Datacube Framework for Advanced Geospatial Data Analysis

This study introduces a scalable and integrated datacube framework for efficient geospatial data processing and analysis. Leveraging the advanced cloud infrastructure of the National Center for High-Performance Computing (NCHC), the framework combines the openEO API and OGC services to address challenges in managing multidimensional datasets. By ensuring interoperability, security, and high-performance computing, the framework provides a reliable solution for researchers and practitioners to tackle complex geospatial challenges.

Framework Architecture

The framework architecture integrates advanced tools and services, focusing primarily on the openEO API and OGC standard services (e.g., Web Coverage Service and Web Coverage Processing Service). The openEO API provides a unified interface supporting multiple programming languages, allowing users to design and execute customized workflows and enabling batch processing.

openEO integration
The openEO API plays a central role in the framework, performing the following functions:

• Unified Data Access and Processing Interface: openEO offers a standardized access and processing layer for Earth observation data, abstracting underlying complexities and enabling users to uniformly access multidimensional data from various sources, such as satellite imagery and terrain datasets.
• Process Graphs and User-Defined Processes: openEO supports User-Defined Processes and Process Graphs, enabling users to create tailored data processing pipelines based on specific analytical requirements. This is particularly valuable for advanced analyses like temporal change detection or spatial statistics.
• Seamless Integration with OGC Services: openEO works seamlessly with OGC services (e.g., WCS and WCPS) in the framework, enhancing its ability to handle multi-source data. While openEO provides high-level data access and analytical capabilities, OGC services ensure interoperability and standardization at the data layer.

API Proxy Architecture Design

The API proxy is a critical component of the framework, bridging the openEO API and the backend infrastructure to ensure efficient, secure, and stable interactions between users and the system. Its main functions include authentication, authorization management, traffic control, and caching. With the API proxy, openEO can provide a simplified user experience while ensuring optimal utilization of backend data and resources.

Application Scenarios

1. Terrain Analysis
By transforming digital terrain models (DTMs) into multidimensional structures, the framework significantly improves the processing speed and accuracy of large-scale datasets. openEO’s role includes providing a unified interface for data access, enabling users to quickly retrieve and process data for custom slope calculations, visibility analyses, and more. Simultaneously, API proxy security layers ensure strict management of data access and usage.

2. Temporal Analysis Using Landsat Imagery
Temporal analysis of Landsat imagery involves handling large volumes of time-series data. Here, openEO acts as the analytical hub, allowing users to submit analysis requests (e.g., calculating the Normalized Difference Water Index (NDWI)) via the API. The framework then automatically invokes OGC services for data processing and result generation.

Conclusion

The proposed datacube framework successfully integrates openEO API and OGC services, offering a scalable, interoperable, and high-performance solution. As a unified data access and analytical interface, openEO provides flexible and robust tools that significantly simplify complex data processing workflows. By lowering technical barriers and enhancing analytical accessibility, the framework delivers unprecedented convenience for geospatial data analysis, making it a key tool in research and decision-making processes.