07 ease

Working with EASE-DGGS in Vgrid DGGS¶

Full Vgrid DGGS documentation is available at vgrid document.

To work with Vgrid DGGS directly in GeoPandas and Pandas, please use vgridpandas. Full Vgridpandas DGGS documentation is available at vgridpandas document.

To work with Vgrid DGGS in QGIS, install the Vgrid Plugin.

To visualize DGGS in Maplibre GL JS, try the vgrid-maplibre library.

For an interactive demo, visit the Vgrid Homepage.

Install vgrid¶

Uncomment the following line to install vgrid.

In [1]:

# %pip install vgrid --upgrade

# %pip install vgrid --upgrade

latlon2ease¶

In [2]:

from vgrid.conversion.latlon2dggs import latlon2ease

lat = 10.775276
lon = 106.706797
res = 4
ease_id = latlon2ease(lat, lon, res)
ease_id

from vgrid.conversion.latlon2dggs import latlon2ease lat = 10.775276 lon = 106.706797 res = 4 ease_id = latlon2ease(lat, lon, res) ease_id

Out[2]:

'L4.165767.02.02.22.45'

EASE to Shapely Polygon¶

In [3]:

from vgrid.conversion.dggs2geo.ease2geo  import ease2geo

ease_geo = ease2geo(ease_id)
ease_geo

from vgrid.conversion.dggs2geo.ease2geo import ease2geo ease_geo = ease2geo(ease_id) ease_geo

Out[3]:

EASE to GeoJSON¶

In [4]:

from vgrid.conversion.dggs2geo.ease2geo import ease2geojson
ease_geojson = ease2geojson(ease_id)
ease_geojson

from vgrid.conversion.dggs2geo.ease2geo import ease2geojson ease_geojson = ease2geojson(ease_id) ease_geojson

Out[4]:

{'type': 'FeatureCollection',
 'features': [{'type': 'Feature',
   'geometry': {'type': 'Polygon',
    'coordinates': (((106.70643153526966, 10.774742521949035),
      (106.70746887966799, 10.774742521949035),
      (106.70746887966799, 10.77597404904263),
      (106.70643153526966, 10.77597404904263),
      (106.70643153526966, 10.774742521949035)),)},
   'properties': {'ease': 'L4.165767.02.02.22.45',
    'resolution': 4,
    'center_lat': 10.7753583,
    'center_lon': 106.7069502,
    'avg_edge_len': 124.838,
    'cell_area': 15455.022,
    'cell_perimeter': 499.354}}]}

Vector to EASE¶

In [5]:

from vgrid.conversion.vector2dggs.vector2ease import vector2ease

file_path = (
    "https://raw.githubusercontent.com/opengeoshub/vopendata/main/shape/polygon.geojson"
)
vector_to_ease  = vector2ease(file_path, resolution=3, compact=False, 
                                predicate = "intersects",output_format="gpd" )
# Visualize the output
vector_to_ease.plot(edgecolor="white")

from vgrid.conversion.vector2dggs.vector2ease import vector2ease file_path = ( "https://raw.githubusercontent.com/opengeoshub/vopendata/main/shape/polygon.geojson" ) vector_to_ease = vector2ease(file_path, resolution=3, compact=False, predicate = "intersects",output_format="gpd" ) # Visualize the output vector_to_ease.plot(edgecolor="white")

Processing features: 100%|██████████| 4/4 [00:00<00:00, 18.56it/s]

Out[5]:

<Axes: >

EASE Compact¶

In [6]:

from vgrid.conversion.dggscompact.easecompact import easecompact

ease_compacted = easecompact(vector_to_ease, output_format="gpd")
ease_compacted.plot(edgecolor="white")

from vgrid.conversion.dggscompact.easecompact import easecompact ease_compacted = easecompact(vector_to_ease, output_format="gpd") ease_compacted.plot(edgecolor="white")

Out[6]:

<Axes: >

EASE Expand¶

In [7]:

from vgrid.conversion.dggscompact import easeexpand

ease_expanded = easeexpand(vector_to_ease, resolution=4, output_format="gpd")
ease_expanded.plot(edgecolor="white")

from vgrid.conversion.dggscompact import easeexpand ease_expanded = easeexpand(vector_to_ease, resolution=4, output_format="gpd") ease_expanded.plot(edgecolor="white")

Out[7]:

<Axes: >

EASE Generator¶

In [8]:

from vgrid.generator.easegrid import easegrid
ease_grid = easegrid(resolution=3,bbox=[106.699007, 10.762811, 106.717674, 10.778649],output_format="gpd")
ease_grid.plot(edgecolor="white")

from vgrid.generator.easegrid import easegrid ease_grid = easegrid(resolution=3,bbox=[106.699007, 10.762811, 106.717674, 10.778649],output_format="gpd") ease_grid.plot(edgecolor="white")

Generating EASE DGGS: 100%|██████████| 4/4 [00:00<00:00, 274.51 cells/s]

Out[8]:

<Axes: >

EASE Inspect¶

In [9]:

from vgrid.stats.easestats import easeinspect
resolution = 0
ease_inspect = easeinspect(resolution)
ease_inspect.head()

from vgrid.stats.easestats import easeinspect resolution = 0 ease_inspect = easeinspect(resolution) ease_inspect.head()

Generating EASE DGGS: 100%|██████████| 391384/391384 [09:07<00:00, 715.06 cells/s] 

Out[9]:

	ease	resolution	center_lat	center_lon	avg_edge_len	cell_area	cell_perimeter	geometry	crossed	norm_area	ipq	zsc
0	L0.000000	0	83.631975	-179.813278	27069.75	2.290566e+08	108278.999	POLYGON ((-180 83.4103, -179.62656 83.4103, -1...	False	0.142283	0.245507	0.495487
1	L0.000001	0	83.631975	-179.439834	27069.75	2.290566e+08	108278.999	POLYGON ((-179.62656 83.4103, -179.25311 83.41...	False	0.142283	0.245507	0.495487
2	L0.000002	0	83.631975	-179.066390	27069.75	2.290566e+08	108278.999	POLYGON ((-179.25311 83.4103, -178.87967 83.41...	False	0.142283	0.245507	0.495487
3	L0.000003	0	83.631975	-178.692946	27069.75	2.290566e+08	108278.999	POLYGON ((-178.87967 83.4103, -178.50622 83.41...	False	0.142283	0.245507	0.495487
4	L0.000004	0	83.631975	-178.319502	27069.75	2.290566e+08	108278.999	POLYGON ((-178.50622 83.4103, -178.13278 83.41...	False	0.142283	0.245507	0.495487

Distribution of EASE Area Distortions¶

In [10]:

from vgrid.stats.easestats import ease_norm_area
ease_norm_area(ease_inspect)

from vgrid.stats.easestats import ease_norm_area ease_norm_area(ease_inspect)

Distribution of EASE IPQ Compactness¶

In [11]:

from vgrid.stats.easestats import ease_compactness
ease_compactness(ease_inspect)

from vgrid.stats.easestats import ease_compactness ease_compactness(ease_inspect)

EASE Statistics¶

In [1]:

from vgrid.stats.easestats import easestats
easestats('km')

from vgrid.stats.easestats import easestats easestats('km')

Out[1]:

	resolution	number_of_cells	avg_edge_len_km	avg_cell_area_km2
0	0	391384	36.032221	1298.320939
1	1	6262144	9.008055	81.145059
2	2	56359296	3.002685	9.016118
3	3	507233664	1.000895	1.001791
4	4	50723366400	0.100090	0.010018
5	5	5072336640000	0.010009	0.000100
6	6	507233664000000	0.001001	0.000001