https://github.com/martibosch/pylandstats-swiss-forests

Analysis with PyLandStats of the evolution of the Swiss forests for the YoMos 2020 workshop
https://github.com/martibosch/pylandstats-swiss-forests

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Analysis with PyLandStats of the evolution of the Swiss forests for the YoMos 2020 workshop

• Host: GitHub
• URL: https://github.com/martibosch/pylandstats-swiss-forests
• Owner: martibosch
• License: gpl-3.0
• Created: 2020-05-28T08:56:53.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-06-02T06:39:24.000Z (over 4 years ago)
• Last Synced: 2024-06-11T16:31:25.559Z (7 months ago)
• Language: Jupyter Notebook
• Homepage: https://www.yomos.org
• Size: 3.11 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
[![GitHub license](https://img.shields.io/github/license/martibosch/pylandstats-swiss-forests.svg)](https://github.com/martibosch/pylandstats-swiss-forests/blob/master/LICENSE)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/martibosch/pylandstats-swiss-forests/master?filepath=notebooks)

# PyLandStats Swiss forests

Analysis with PyLandStats of forest evolution in the Swiss cantons of Bern, Fribourg, Neuchatel and Vaud.

![](figure.png)

This repository is part of the [YoMos 2020](https://www.yomos.org) workshop.

## Instructions to execute

### Option 1: via MyBinder

Click the badge below, which will use [MyBinder](https://mybinder.org/) to launch a server with a Jupyter executable environment:

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/martibosch/pylandstats-swiss-forests/master?filepath=notebooks)

### Option 2: locally

1. If you do not have `conda` in your computer, [download and install it](https://docs.conda.io/projects/conda/en/latest/user-guide/install/download.html).

2. Clone the repository and change directory to the repository's root:

```bash

git clone https://github.com/martibosch/pylandstats-swiss-forests

cd pylandstats-swiss-forests

```

3. Create the environment and activate it:

```bash

conda env create -f environment.yml

# the above command creates a conda environment named `pylandstats-swiss-forests`

conda activate pylandstats-swiss-forests

```

4. Register the IPython kernel of the `pylandstats-swiss-forests` environment:

```bash

python -m ipykernel install --user --name pylandstats-swiss-forests --display-name \

    "Python (pylandstats-swiss-forests)"

```

5. You can test that the installation worked by running the following command:

```bash

python -c 'import pylandstats as pls ;  pls.Landscape("data/raw/AS18_17.tif") ; print("OK")'

```

6. Run a local jupyter notebook server and you can now exectue [the notebooks of this repository](https://github.com/martibosch/pylandstats-swiss-forests/blob/notebooks):

```bash

jupyter-notebook --notebook-dir=notebooks

```

## Acknowledgements

* The land use/land cover data has been extracted from the [Swiss Land Statistics datasets from the Swiss Federal Statistical Office (SFSO)](https://www.bfs.admin.ch/bfs/fr/home/services/geostat/geodonnees-statistique-federale/sol-utilisation-couverture/statistique-suisse-superficie.html) (link in French) with the [swisslandstats-geopy](https://github.com/martibosch/swisslandstats-geopy) library.

* The digital elevation model has been extracted from the [free version of the digital height model of Switzerland by the Swiss Federal Office of Topography (swisstopo)](https://shop.swisstopo.admin.ch/en/products/height_models/dhm25200).

* Project based on the [cookiecutter data science project template](https://drivendata.github.io/cookiecutter-data-science). #cookiecutterdatascience