
FICORO_GNSS v1.0.0: Initial release This initial release provides essential tools for filtering, combining and rotating GNSS velocity fields 🔍 Key features: Filter GNSS data: Remove GNSS velocity outliers based on velocity uncertainty distribution and spatial coherence of velocities Combine velocity fields: Combine GNSS velocity fields from multiple geodetic studies into a unified velocity field. Rotate to multiple reference frames: Rotate velocity fields to different reference frames using GAMIT/GLOBK integration. Manage duplicate stations: Identify and handle collocated stations with minor coordinate discrepancies across different datasets. User-friendly interface: Use Jupyter Notebook for interactive and streamlined data processing. 📂 Included in this release: Main notebook: FICORO_GNSS.ipynb – Orchestrates the data processing workflow. Input folder: raw_input/ – Contains example GNSS velocity fields in .raw format. Scripts folder: scripts/ – Houses Python scripts for automated filtering and combining processes. Manual filter folder: manual_filter/ – Includes a CSV template for defining geographic coordinates and radii for outlier removal. Documentation: Comprehensive README.md with usage instructions. Example combined velocity field: The package includes a combined GNSS velocity field for the Alpine Himalayan belt. 🚧 Future enhancements: Python-based rotation and alignment modules: Eliminating the dependency on GAMIT/GLOBK in upcoming releases. Enhanced documentation: Providing more detailed tutorials and examples. Community contributions: Encouraging contributions to expand functionalities. Modular code structure: Making the code more modular by bundling common functions into modules, enhancing maintainability and scalability.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
