EOPF-Sample-Service/eopf-sample-notebooks
Jul 2025 – Jul 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Cloud Data AccessCloud StorageCloud Storage (S3)Data AccessData ExplorationData Reprojection
Peter Zellner
PROFILE
Peter Zellner
Peter Zellner developed two core features for the EOPF-Sample-Service/eopf-sample-notebooks repository, focusing on efficient handling and exploration of Sentinel-2 L1C MSI data. He implemented direct data access for both .zarr and .SAFE formats from HTTP and S3 sources, enabling seamless multi-location data loading and supporting reproducible workflows. Using Python, Jupyter Notebooks, and xarray, Peter created a notebook that visualizes, plots, and encodes Sentinel-2 data, including RGB rendering and band statistics. His work emphasized performance optimization and reliability, accelerating exploratory analysis for remote sensing teams. The features addressed data access challenges and improved usability across cloud storage backends.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
4,194
Activity Months1
Work History
July 2025
4 Commits • 2 Features
Jul 1, 2025July 2025 — EOPF-Sample-Service/eopf-sample-notebooks: Delivered two key features for Sentinel-2 L1C MSI data handling in EOPF Zarr format, with direct HTTP/S3 data access. No critical bugs reported. Impact: accelerates exploratory analysis and reproducibility across storage backends; supports rapid visualization, encoding, and statistics of Sentinel-2 data, enabling data-driven insights for users and teams. Technologies/skills demonstrated include xarray, Jupyter Notebooks, zarr/SAFE formats, and multi-source data loading patterns.
4 Commits • 2 Features
Jul 1, 2025July 2025 — EOPF-Sample-Service/eopf-sample-notebooks: Delivered two key features for Sentinel-2 L1C MSI data handling in EOPF Zarr format, with direct HTTP/S3 data access. No critical bugs reported. Impact: accelerates exploratory analysis and reproducibility across storage backends; supports rapid visualization, encoding, and statistics of Sentinel-2 data, enabling data-driven insights for users and teams. Technologies/skills demonstrated include xarray, Jupyter Notebooks, zarr/SAFE formats, and multi-source data loading patterns.
July 2025
Activity
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Quality Metrics
Correctness70.0%
Maintainability70.0%
Architecture70.0%
Performance75.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Cloud Data AccessCloud StorageCloud Storage (S3)Data AccessData ExplorationData ReprojectionData VisualizationEarth ObservationJupyter NotebooksPerformance OptimizationRemote SensingRemote Sensing DataSAFE formatSentinel-2 DataXarray
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