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FICORO_GNSS: An open-source Python software package for filtering, combining and rotating GNSS velocity fields

Authors: Nicolás Castro-Perdomo;

FICORO_GNSS: An open-source Python software package for filtering, combining and rotating GNSS velocity fields

Abstract

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.

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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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