Evaluation of the carbon sequestration for the canton of Vaud

Citation: Jaligot, R., Chenal, J. & Bosch, M. "Assessing spatial temporal patterns of ecosystem services in Switzerland". Landscape Ecol (2019): 1-16. https://doi.org/10.1007/s10980-019-00850-7

Analysis DAG

Given how the Swiss Land Statistics datasets are provided (see this for more info), we work with "LandDataFrames", i.e., tables where each row correspond to an (x, y) geo-referenced pixel, and columns provide categorical information, such as the land use/land cover, elevation, production regions and organic soil. This information is used to compute the carbon stock with the InVEST's carbon model.

The results are displayed in invest_carbon.ipynb

Instructions to reproduce the repository

Preparing the environment

1. Create the conda environment

    # the environment's name will be `carbonseq_vaud`
    conda env create -f environment.yml
   

2. Configure your S3 profile (credentials, region and endpoint URL)

3. Enter the fresh environment

    conda activate carbonseq_vaud
   

4. Already within the environment, make it available as a jupyter kernel as in:

    python -m ipykernel install --user --name carbonseq_vaud --display-name "Python (carbonseq_vaud)"
   

Reproducing

1. From the repository's root, create a folder named papermill_outputs

2. Pull the data from the dvc remote

    dvc pull
   

3. Reproduce the land data frame

    dvc repro data/vaud_ldf.csv.dvc
   

Now you can execute the Notebook invest.ipynb