https://github.com/computationalgeography/opengeohub2021

https://github.com/computationalgeography/opengeohub2021

Repository

https://github.com/computationalgeography/opengeohub2021/blob/master/

# Geosimulation using fields and agents


This repository holds a Jupyter notebook demonstrating the Daisyworld model implementation in Campo,
a YAML file to create the Python environment required to run the model,
and necessary scripts for pre- and postprocessing.

More information will be given in the [OpenGeoHub Summer School 2021](https://www.opengeohub.org/summer_school_2021) lecture on September 2nd at 2pm CEST.

## How to install

A few steps are required to run the Jupyter notebook.
General information on Jupyter notebooks and manuals can be found [here](https://jupyter.readthedocs.io/en/latest/).
The user guide and short reference on Conda can be found [here](https://docs.conda.io/projects/conda/en/latest/user-guide/cheatsheet.html).

 1. You will need a working Python environment, we recommend to install Miniconda. Follow their instructions given at:

    [https://docs.conda.io/en/latest/miniconda.html](https://docs.conda.io/en/latest/miniconda.html)

 2. Open a terminal (Linux/macOS) or Miniconda command prompt (Windows) and browse to a location where you want to store the course contents.

 3. Clone this repository, or download and uncompress the zip file. Afterwards change to the `opengeohub2021` folder.

 4. Create the required Python environment:

    Linux/macOS:

    `conda env create -f environment/course_environment.yaml`

    Windows:

    `conda env create -f environment\course_environment.yaml`


The environment file will create a environment named *fieldagents* using Python 3.9. In case you prefer a different name or Python version you need to edit the environment file.


## How to run

Activate the environment in the command prompt:

`conda activate fieldagents`

Then change to the `notebook` folder.
You can now start the Jupyter notebook from the command prompt. The notebook will open in your browser:

`jupyter-notebook course.ipynb`


## Further reading

Background on DaisyWorld:

  [https://en.wikipedia.org/wiki/Daisyworld](https://en.wikipedia.org/wiki/Daisyworld)
	
Scientific literature about Campo and LUE:

  M.P. de Bakker, K. de Jong, O. Schmitz, D. Karssenberg (2017). Design and demonstration of a data model to integrate agent-based and field-based modelling. Environmental Modelling & Software, 89, 172-189, DOI: [10.1016/j.envsoft.2016.11.016](https://doi.org/10.1016/j.envsoft.2016.11.016). 
	
  K. de Jong, D. Karssenberg (2019). A physical data model for spatio-temporal objects. Environmental Modelling & Software, 122, 104553, DOI: [10.1016/j.envsoft.2019.104553](https://doi.org/10.1016/j.envsoft.2019.104553).
	
  K. de Jong, D. Panja, M. van Kreveld, D. Karssenberg (2021). An environmental modelling framework based on asynchronous many-tasks: Scalability and usability. Environmental Modelling & Software, 139, 104998, DOI: [10.1016/j.envsoft.2021.104998](https://doi.org/10.1016/j.envsoft.2021.104998).
	

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