This open-source snakemake workflow can be used to analyse environmental risks to infrastructure networks using global open data. It is a work in progress.
Goals:
- Automated pipeline for reproducible analysis anywhere in the world
- Maps per-country and of larger areas
- Charts/stats of exposure per admin region, per hazard type, scenario, epoch
- Consider transport, electricity, water, communications systems
- Consider river flooding, storm surge coastal flooding, tropical cyclones
- Estimate direct damages to physical networks
- Estimate indirect effects of disruption - people affected, economic activity disrupted
Non-goals:
- Using closed data, which may be appropriate for other projects or use-cases
- Detailed operational/engineering level simulation
- Long-term planning
Install open-gira
by cloning the repository:
git clone https://github.com/nismod/open-gira.git
The repository comes with a environment.yml
file describing the conda
and
PyPI
packages required to run open-gira
. The open-gira
developers
recommend using either micromamba
or mamba to install and
manage these conda
packages.
Having installed one of the suggested package managers, to create the
open-gira
conda environment:
micromamba create -f environment.yml -y
And to activate the environment:
micromamba activate open-gira
Some rules use the wget
utility to download files.
On Linux or MacOS, you may already have the wget
utility available. If not,
it should be possible to install with your usual package manager (e.g. apt,
MacPorts, brew), or else using micromamba:
micromamba install wget
On Windows, you may have it already if you have a MinGW or Cygwin installation.
If not, you can access binaries at eternallybored.org.
Download the standalone exe and place it for example in C:\Users\username\bin
or somewhere on your PATH.
exactextract
is used for zonal statistics in the tropical cyclones /
electricity grid analysis. It is not available via the conda
package
management ecosystem and so must be installed separately. Please see
installation instructions here.
You are now ready to request result files, triggering analysis jobs in the process.
Note that all subsequent commands given in the documentation assume that the
open-gira
environment is already activated.
Workflow steps are tested using small sample datasets.
To run the tests:
python -m pytest tests
open-gira
is comprised of a set of snakemake
rules which call scripts and
library code to request data, process it and produce results.
The key idea of snakemake
is similar to make
in that the workflow is
determined from the end (the files users want) to the beginning (the files
users have, if any) by applying general rules with pattern matching on file and
folder names.
A example invocation looks like:
snakemake --cores 2 -- results/wales-latest_filter-road-primary/edges.gpq
Here, we ask snakemake
to use up to 2 CPUs to produce a target file, in this
case, the edges of the Welsh road network. snakemake
pattern matches
wales-latest
as the OSM dataset name and road-primary
as the network
type we want to filter for, picking up the filter expressions as defined in config/osm_filters/road-primary.txt
.
To check what work we're going to request before commencing, use the -n
flag:
snakemake -n --cores 2 -- results/wales-latest_filter-road-primary/edges.gpq
This will explain which rules will be required to run to produce the target file. It may be helpful to visualise which rules are expected to run, too.
The workflow configuration details are in config/config.yml
. You can edit
this to set the target OSM infrastructure datasets, number of spatial slices, and
hazard datasets.
See the documentation and config/README.md for more details on usage in general and on configuration.
Documentation is written using the mdbook
format, using markdown files in the ./docs
directory.
Follow the installation instructions
to get the mdbook
command-line tool.
To build the docs locally:
cd docs
mdbook build
open book/index.html
Or run mdbook serve
to run a server and rebuild the docs as you make changes.
Two libraries have been developed in tandem with open-gira
and provide some
key functionality.
The open-source Python library snail is used for vector-raster intersection, e.g. identifying which road segments might be affected by a set of flood map hazard rasters.
The snkit library is used for network cleaning and assembly.
This research received funding from the FCDO Climate Compatible Growth Programme. The views expressed here do not necessarily reflect the UK government's official policies.
This research has also been supported by funding from the World Bank Group, and the UK Natural Environment Research Council (NERC) through the UK Centre for Greening Finance and Investment (CGFI).