GeoPOINT – Synthetic Point Generator for Geospatial Applications

GeoPOINT is a Python-based tool for generating synthetic 3D points to support geospatial, geodetic, and computational experiments.
It allows users to simulate ideal point distributions, add measurement noise, and apply geodetic distortion models, followed by transformations into local reference frames.
The tool is implemented as a Jupyter Notebook (GeoPOINT_generator.ipynb).

Key Features

• Synthetic point generation on a spherical surface in a fixed (global) coordinate frame.
  Three modes are supported:

  1. Ideal points (noise-free) – purely mathematical coordinates uniformly distributed on a sphere.
     
  2. Points with Gaussian noise – adds random errors to simulate stochastic measurement noise.
     
  3. Points with geodetic distortion – combines Gaussian noise with systematic EDM (Electronic Distance Meter) and angular errors, simulating real Total Station observations.
     

• Transformation of coordinates into a local (body) frame:

  • Translation along X, Y, Z axes.
    
  • Rotation (roll, pitch, yaw) specified in gradians and internally converted to radians.
    
  • Optional scaling for dimensional adjustments.
    

• Configurable error and transformation parameters via a central configuration dictionary.

• Export to Excel (.xlsx) using pandas and openpyxl – both fixed and transformed coordinate sets are saved.

• Visualization and statistics of generated and transformed datasets:

  • 3D scatter plots and wireframe reference sphere.
    
  • Comparison between datasets (ideal vs. noisy vs. distorted).
    
  • Error vectors illustrating displacements between point sets.
    
  • Export of figures as .jpg images.
    

Installation

The repository provides an environment.yml file for Conda.
To set up the environment:

```bash

Clone the repository

git clone https://github.com/Baltic-Coastal-Monitoring-Team/GeoPOINT.git cd GeoPOINT

Create environment

conda env create -f environment.yml

Activate environment

conda activate geopoint ```

This environment includes: - Python 3.11 - numpy, pandas, matplotlib, scipy, sympy - openpyxl (Excel export) - jupyterlab (for running the notebook) - torch (optional numerical extensions)

Quick Start

1. Launch JupyterLab:

bash jupyter lab

1. Open the GeoPOINT_generator.ipynb notebook.
   
2. Configure parameters in the config dictionary, e.g.:

```python config = { "npoints": 50, # Number of synthetic points "radius": 50.0, # Sphere radius [m]

# Geodetic error model
"A": 0.005,             # Constant EDM error [m]
"B": 7.0,               # Distance-dependent EDM error [ppm]
"angle_noise_arcsec": 1.0,  # Angular precision [arcseconds]

# Rotation parameters [grads]
"roll": 5,
"pitch": 5,
"yaw": 40,

# Translation parameters [m]
"dx": 10.0,
"dy": 10.0,
"dz": 2.0,

# Noise added to transformed points [m]
"gaussian_std": 0.01,
"bias": 0.002

} ```

1. Run the generation cells to create ideal, noisy, or distorted points.
   
2. Transform coordinates into the local body frame.
   
3. Export results to Excel and plots to .jpg images.

Repository Structure

GeoPOINT/ ├─ GeoPOINT_generator.ipynb # main notebook with generator code ├─ environment.yml # conda environment file ├─ exports_excel/ # results in XLSX format ├─ exports_img/ # results in jpg format └─ README.md # project documentation

Documentation and Instructions

All instructions, detailed explanations, and usage notes are provided directly in the Jupyter Notebook (GeoPOINT_generator.ipynb).
Code comments further clarify each computational step, configuration parameter, and transformation method.
Users are encouraged to explore the notebook to fully understand the workflow and adapt it to their specific applications.

Example Applications

• Testing geodetic instrument error models (EDM, angular precision).
  
• Benchmarking coordinate transformation workflows.
  
• Teaching and demonstration of geodetic concepts (roll/pitch/yaw, local frames).
  
• Producing synthetic datasets for algorithm validation.
  

Contributing

Contributions are welcome:
- Bug fixes and improvements.
- Additional error models or transformation options.
- Examples of usage in geodetic or geospatial projects.

Citation

If you use GeoPOINT in your research or publications, please cite:

License

MIT License – see LICENSE file.