This code is related to the publication "Assessing the environmental impacts of soil compaction in Life Cycle Assessment" by Stoessel et al. (2018), available at https://www.sciencedirect.com/science/article/pii/S0048969718306211.
The output as well as an prepared input file for the soil clay content can be found at https://doi.org/10.3929/ethz-b-000253177.
The code is written to use the provided folder structure.
Data should be downloaded and saved accordingly (see 4).
People familiar with python environments may use the py36_gis.yml or the requirements.txt file.
Others may follow the instructions below.
- Installing Python
- Creating Conda environment
- Starting Jupyter Notebook and run the code
- Data Download
Python has been installed with the Miniconda installer: http://conda.pydata.org/miniconda.html
- conda version: 4.3.22
- python version: 3.5.2.final.0
- requests version: 2.12.4
The virtual environment used for all the calculations has been set up the following way:
Create environment with Python 3.6:
conda create -n 'environment_name' python=3.6
Activate environment:
(source) activate 'environment_name'
Install packages:
from conda-forge channel (conda install -c conda-forge 'package'):
- rasterstats
- geopandas
- netcdf4
from conda (conda install 'package'):
- (nb_conda_kernels (in root environment, i.e. without having the environment activated))
- (ipykernel (to make nb_conda_kernels work))
- xlrd
- openpyxl
These packages should have come with the ones above:
- numpy
- scipy
- matplotlib
- pandas
- type
jupyter notebookin your command line - head to the folder with the code (or do this in the command line before typing "jupyter notebook")
- run notebooks in order of numbering
download data from the sources provided in the first notebook into the folder structure