fusedio/udfs
May 2025 – May 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
API IntegrationCloud ComputingGDALGeoPandasGeospatial Data ProcessingParallel Processing
Harald Kristen
PROFILE
Harald Kristen
Developed two geospatial user-defined functions for the fusedio/udfs repository, focusing on streamlining satellite imagery workflows. The first UDF automated downloading satellite imagery from ArcGIS ImageServer for specified bounding boxes using REST APIs, while the second converted standard TIFF files into Cloud Optimized GeoTIFFs to enhance storage efficiency and cloud processing performance. Leveraged Python, GDAL, and Rasterio to handle raster data and parallel processing, ensuring scalable and efficient data handling. The work addressed the end-to-end workflow from data acquisition to optimized storage, enabling faster downstream analysis and improved accessibility for customers working with large geospatial datasets in cloud environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
744
Activity Months1
Your Network
18 peopleWork History
May 2025
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on business value and technical achievements. Highlights: - Delivered two geospatial UDFs to streamline satellite imagery acquisition and processing, enabling faster data availability for downstream analyses and customers. - Implemented a TIFF-to-COG converter to optimize storage and performance for large TIFF datasets, facilitating efficient cloud-based processing. - Contributed public UDFs with a single commit addressing end-to-end workflow from ArcGIS ImageServer to COG conversion (#879).
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on business value and technical achievements. Highlights: - Delivered two geospatial UDFs to streamline satellite imagery acquisition and processing, enabling faster data availability for downstream analyses and customers. - Implemented a TIFF-to-COG converter to optimize storage and performance for large TIFF datasets, facilitating efficient cloud-based processing. - Contributed public UDFs with a single commit addressing end-to-end workflow from ArcGIS ImageServer to COG conversion (#879).
May 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
API IntegrationCloud ComputingGDALGeoPandasGeospatial Data ProcessingParallel ProcessingPythonRaster Data HandlingRasterioRequests
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