DGGS.jl is a Julia Package for scalable geospatial analysis using Discrete Global Grid Systems (DGGS), which tessellate the surface of the earth with hierarchical cells of equal area, minimizing distortion and loading time of large geospatial datasets, which is crucial in spatial statistics and building Machine Learning models.

This project is currently under intensive development. The API is not considered stable yet. There may be errors in some outputs. We do not take any warranty for that. Please test this package with caution. Bug reports and feature requests are welcome. Please create a new issue for this.

DGGS.jl currently only officially supports Julia 1.9 running on a 64bit Linux machine. This package can be installed in Julia with the following commands:

using Pkg
Pkg.add(url="https://github.com/danlooo/DGGS.jl.git")

using DGGS
p1 = open_dggs_pyramid("https://s3.bgc-jena.mpg.de:9000/dggs/datasets/example-ccsm3")

DGGSPyramid
DGGS: DGGRID ISEA4H Q2DI ⬢
Levels: Integer[5, 4, 6, 2, 3]
Non spatial axes:
  Time CFTime.DateTimeNoLeap
  plev Float64
Arrays: 
  tas air_temperature (:Time) K Union{Missing, Float32} aggregated
  ua eastward_wind (:plev, :Time) m s-1 Union{Missing, Float32} aggregated
  pr precipitation_flux (:Time) kg m-2 s-1 Union{Missing, Float32} aggregated
  area meter2 Union{Missing, Float32} 

Get temperature in Kelvin at the first time point of a hexagonal center cell and its 6 direct neighbors around a given coordinate at spatial resolution level 6:

p1[level=6, id=:tas, Time=1, lon=11.586, lat=50.927, radii=1:2] |> collect

7-element Vector{Union{Missing, Float32}}:
 282.60416f0
 282.3016f0
 282.34818f0
 281.85855f0
 281.90802f0
 282.06424f0
 282.39597f0

Create a DGGS based on a synthetic data in a geographical grid:

using DimensionalData
lon_range = X(-180:180)
lat_range = Y(-90:90)
level = 6
data = [exp(cosd(lon)) + 3(lat / 90) for lon in lon_range, lat in lat_range]
raster = DimArray(data, (lon_range, lat_range))
p2 = to_dggs_pyramid(raster, level)

[ Info: Step 1/2: Transform coordinates
[ Info: Step 2/2: Re-grid the data
DGGSPyramid
DGGS: DGGRID ISEA4H Q2DI ⬢
Levels: Integer[5, 4, 6, 2, 3]
Non spatial axes:
Arrays: 
  layer  Union{Missing, Float64} 

Write DGGS data to disk and load them back:

write_dggs_pyramid("example.dggs", p2)
p2a = open_dggs_pyramid("example.dggs")

Access individual layers and arrays:

highest_layer = p1[6]
air_temperature = highest_layer.tas
temperature_map = collect(p1[level=2, id=:tas, Time=1])

Visualization:

using GLMakie
plot(p1[6].tas)
plot(p1[6].tas; type=:map, longitudes=-180:180, latitudes=-90:90)

This project is based on DGGRID.

This project has received funding from the Open-Earth-Monitor Cyberinfrastructure project that is part of European Union's Horizon Europe research and innovation programme under grant agreement No. 101059548.