Open-data Risk Analysis of Global Mobile Broadband Infrastructure
This repository contains a codebase for assessing the global vulnerability of mobile infrastructure via OpenCelliD data.
- Oughton, E.J., Russell, T., Oh, J., Ballan, S., Hall, J.W., 2023. Global vulnerability assessment of mobile telecommunications infrastructure to climate hazards using crowdsourced open data. https://doi.org/10.48550/arXiv.2311.04392
The recommended approach to using open-rigbi
is via conda.
First, create a conda environment as follows:
conda create --name rigbi-env
Then activate it:
conda activate rigbi-env
Finally, install the necessary packages, such as geopandas
:
conda env update --file environment_linux.yaml # If on Linux
conda env update --file environment_windows.yaml # If on Windows
If you add a python=
argument to either of the two commands above, you can constrain the version of Python that Anaconda uses. By default, this project requires Python 3.9 and that is the version installed by running the env update command.
The scripts involved can be broadly summarized as follows:
dl.py
downloads all necessary scenario hazard data layers.preprocess.py
preprocesses all boundaries, cell data and flood hazard layers for each country.coastal_lut.py
generates a lookup table of coastal regions.process.py
processes all results.