DGGS pilot. Currently implements only rHealPix 3x3 DGGS.
Features:
- Raster storage using hdf5
- Conversion from GeoTiff (or any format GDAL supports)
- Shapefile polygons -> list of addresses
- This was only tested with conda
- Needs python 3.6+ (uses format strings in some places)
On Mac or Linux:
conda env create -f env.yaml
source activate dggs
pip install --no-deps -e .
./launch-jupyter.sh
On Windows
conda env create -f env.yaml
activate dggs
pip install --no-deps -e .
launch-jupyter.bat
Sample data is not included in the repository, some of it might be sensitive, other might have re-distribution constraints. Data is distributed separately on request.
Extract password protected dggs-sample-data.zip
using provided password. Move files from data/*
to data/
folder in this repository.
First run these notebooks
io-convert-cbr
io-convert-abs
This will convert some test data to DGGS. You can review by running these notebooks
io-h5-read-cbr
io-h5-read-abs
Then run
nexis-dataset