Instructions for installation are below

DOI of this repository:

This repository enables you to perform the calculations shown in the manuscript: "Comin soon"

Contact: [email protected]

ORCIDs of authors:
M. Ohmer: 0000-0002-2322-335X
F. Doll: 0009-0003-5455-7162
T. Liesch: 0000-0001-8648-5333

For a detailed description please refer to the publication. Please adapt all absolute loading/saving and software paths within the scripts to make them running, you need Python software for a successful application.

To use the code and scripts in this repository, you'll need to install the required libraries and dependencies. You can do this by creating a virtual environment and using the requirements.txt file. Here are the steps:

1. Create a virtual environment (optional but recommended):

python -m venv spatialinfo

2. Activate the virtual environment:

source spatialinfo/bin/activate # On Unix/Linux
spatialinfo\Scripts\activate # On Windows

3. Install the required libraries from the requirements.txt file:

pip install -r requirements.txt

This repository includes the following main Python scripts:

• RF.py: The main script for conducting spatial analysis and prediction using Random Forest.
• general_functions.py: Contains general utility functions.
• plotting_functions.py: Contains functions for data visualization.
• spatial_feature_functions.py: Contains functions for extracting spatial features.

To run the analysis, you can use the RF.py script as follows: python RF.py

Please refer to the script documentation and comments for more details on how to use them effectively.

Contributions to this project are welcome! If you find issues, have suggestions, or want to contribute new features, please open an issue or submit a pull request.

Feel free to contact us with any questions or feedback.