06 isea3h

Working with Open-EAGGR ISEA3H 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

latlon2isea3h¶

In [2]:

from vgrid.conversion.latlon2dggs import latlon2isea3h

lat = 10.775276
lon = 106.706797
res = 12
isea3h_id = latlon2isea3h(lat, lon, res)
isea3h_id

from vgrid.conversion.latlon2dggs import latlon2isea3h lat = 10.775276 lon = 106.706797 res = 12 isea3h_id = latlon2isea3h(lat, lon, res) isea3h_id

Out[2]:

'1312279,-13'

ISEA3H to Shapely Polygon¶

In [3]:

from vgrid.conversion.dggs2geo.isea3h2geo  import isea3h2geo

isea3h_geo = isea3h2geo(isea3h_id)
print (isea3h_geo)

from vgrid.conversion.dggs2geo.isea3h2geo import isea3h2geo isea3h_geo = isea3h2geo(isea3h_id) print (isea3h_geo)

POLYGON ((106.76780196296323 10.753216594914733, 106.71642146930662 10.789347853370606, 106.66515419768183 10.773755839870532, 106.66526892069197 10.722102655480096, 106.71664140460638 10.686051924943438, 106.76790720591094 10.701573739220004, 106.76780196296323 10.753216594914733))

ISEA3H to GeoJSON¶

In [4]:

from vgrid.conversion.dggs2geo.isea3h2geo import isea3h2geojson

isea3h_geojson = isea3h2geojson(isea3h_id)
isea3h_geojson

from vgrid.conversion.dggs2geo.isea3h2geo import isea3h2geojson isea3h_geojson = isea3h2geojson(isea3h_id) isea3h_geojson

Out[4]:

{'type': 'FeatureCollection',
 'features': [{'type': 'Feature',
   'geometry': {'type': 'Polygon',
    'coordinates': (((106.76780196296323, 10.753216594914733),
      (106.71642146930662, 10.789347853370606),
      (106.66515419768183, 10.773755839870532),
      (106.66526892069197, 10.722102655480096),
      (106.71664140460638, 10.686051924943438),
      (106.76790720591094, 10.701573739220004),
      (106.76780196296323, 10.753216594914733)),)},
   'properties': {'isea3h': '1312279,-13',
    'resolution': 12,
    'center_lat': 10.737684,
    'center_lon': 106.7165319,
    'avg_edge_len': 6157.358,
    'cell_area': 96171100.113}}]}

Vector to ISEA3H¶

In [5]:

from vgrid.conversion.vector2dggs.vector2isea3h import vector2isea3h

file_path = (
    "https://raw.githubusercontent.com/opengeoshub/vopendata/main/shape/polygon.geojson"
)
vector_to_isea3h = vector2isea3h(file_path, resolution=20, compact=False, 
                                predicate = "intersects",output_format="gpd")
# Visualize the output
vector_to_isea3h.plot(edgecolor="white")

from vgrid.conversion.vector2dggs.vector2isea3h import vector2isea3h file_path = ( "https://raw.githubusercontent.com/opengeoshub/vopendata/main/shape/polygon.geojson" ) vector_to_isea3h = vector2isea3h(file_path, resolution=20, compact=False, predicate = "intersects",output_format="gpd") # Visualize the output vector_to_isea3h.plot(edgecolor="white")

Processing features: 100%|██████████| 4/4 [00:02<00:00,  1.59it/s]

Out[5]:

<Axes: >

ISEA3H Compact¶

In [6]:

from vgrid.conversion.dggscompact.isea3hcompact  import isea3hcompact

isea3h_compacted = isea3hcompact( vector_to_isea3h, output_format="gpd")
isea3h_compacted.plot(edgecolor="white")

from vgrid.conversion.dggscompact.isea3hcompact import isea3hcompact isea3h_compacted = isea3hcompact( vector_to_isea3h, output_format="gpd") isea3h_compacted.plot(edgecolor="white")

Out[6]:

<Axes: >

ISEA3H Expand¶

In [7]:

from vgrid.conversion.dggscompact.isea3hcompact import isea3hexpand

isea3h_expanded = isea3hexpand(
    vector_to_isea3h, resolution=20, output_format="gpd"
)
isea3h_expanded.plot(edgecolor="white")

from vgrid.conversion.dggscompact.isea3hcompact import isea3hexpand isea3h_expanded = isea3hexpand( vector_to_isea3h, resolution=20, output_format="gpd" ) isea3h_expanded.plot(edgecolor="white")

Out[7]:

<Axes: >

ISEA3H Generator¶

In [8]:

from vgrid.generator.isea3hgrid import isea3hgrid

isea3h_grid = isea3hgrid(resolution=0,output_format="gpd")
isea3h_grid.plot(edgecolor='white')

from vgrid.generator.isea3hgrid import isea3hgrid isea3h_grid = isea3hgrid(resolution=0,output_format="gpd") isea3h_grid.plot(edgecolor='white')

Generating ISEA3H DGGS: 100%|██████████| 20/20 [00:00<00:00, 637.94 cells/s]

Out[8]:

<Axes: >

ISEA3H Inspect¶

In [9]:

from vgrid.stats.isea3hstats import isea3hinspect
resolution = 3
isea3h_inspect = isea3hinspect(resolution)
isea3h_inspect.head()

from vgrid.stats.isea3hstats import isea3hinspect resolution = 3 isea3h_inspect = isea3hinspect(resolution) isea3h_inspect.head()

Generating ISEA3H DGGS: 100%|██████████| 2220/2220 [00:05<00:00, 417.64 cells/s]

Out[9]:

	isea3h	resolution	center_lat	center_lon	avg_edge_len	cell_area	cell_perimeter	geometry	crossed	norm_area	ipq	zsc
0	00030,0	3	52.796491	-144.000000	859534.472	1.927693e+12	5157206.834	POLYGON ((-131.28474 52.37359, -136.05347 59.1...	False	1.017849	0.910791	0.952553
1	0003-1,0	3	38.976164	-144.000000	853461.321	1.893931e+12	5120767.924	POLYGON ((-134.70124 38.65144, -138.77139 45.8...	False	1.000022	0.907620	0.950924
2	00030,1	3	57.699020	-121.162465	852569.447	1.889909e+12	5115416.685	POLYGON ((-108 54.85114, -108 62.05445, -124.6...	False	0.997898	0.907588	0.950912
3	00031,0	3	65.610319	-144.000000	854256.213	1.895550e+12	5125537.275	POLYGON ((-124.68962 64.8145, -131.10399 71.49...	False	1.000877	0.906706	0.950444
4	00030,-1	3	57.699020	-166.837535	1120016.239	1.889909e+12	6720097.437	MULTIPOLYGON (((-180 54.85114, -168.87861 50.6...	False	0.997898	0.525896	0.723845

Distribution of ISEA3H Area Distortions¶

In [10]:

from vgrid.stats.isea3hstats import isea3h_norm_area
isea3h_norm_area(isea3h_inspect)

from vgrid.stats.isea3hstats import isea3h_norm_area isea3h_norm_area(isea3h_inspect)

Distribution of ISEA3H IPQ Compactness¶

In [11]:

from vgrid.stats.isea3hstats import isea3h_compactness
isea3h_compactness(isea3h_inspect)

from vgrid.stats.isea3hstats import isea3h_compactness isea3h_compactness(isea3h_inspect)

ISEA3H Statistics¶

In [12]:

from vgrid.stats.isea3hstats import isea3hstats
isea3hstats('km')

from vgrid.stats.isea3hstats import isea3hstats isea3hstats('km')

Out[12]:

	resolution	number_of_cells	avg_edge_len_km	avg_cell_area_km2
0	0	20	7.674458e+03	2.550328e+07
1	1	140	1.184195e+03	3.643326e+06
2	2	980	4.475835e+02	5.204751e+05
3	3	6860	1.691707e+02	7.435359e+04
4	4	48020	6.394050e+01	1.062194e+04
5	5	336140	2.416724e+01	1.517420e+03
6	6	2352980	9.134357e+00	2.167743e+02
7	7	16470860	3.452462e+00	3.096776e+01
8	8	115296020	1.304908e+00	4.423966e+00
9	9	807072140	4.932089e-01	6.319951e-01
10	10	5649504980	1.864154e-01	9.028501e-02
11	11	39546534860	7.045841e-02	1.289786e-02
12	12	276825744020	2.663078e-02	1.842551e-03
13	13	1937780208140	1.006549e-02	2.632216e-04
14	14	13564461456980	3.804397e-03	3.760309e-05
15	15	94951230198860	1.437927e-03	5.371870e-06
16	16	664658611392020	5.434853e-04	7.674099e-07
17	17	4652610279744140	2.054181e-04	1.096300e-07
18	18	32568271958208980	7.764075e-05	1.566143e-08
19	19	227977903707462860	2.934545e-05	2.237347e-09
20	20	1595845325952240020	1.109154e-05	3.196210e-10
21	21	11170917281665680140	4.192206e-06	4.566014e-11
22	22	78196420971659760980	1.584505e-06	6.522877e-12
23	23	547374946801618326860	5.988866e-07	9.318396e-13
24	24	3831624627611328288020	2.263579e-07	1.331199e-13
25	25	26821372393279298016140	8.555523e-08	1.901713e-14
26	26	187749606752955086112980	3.233684e-08	2.716733e-15
27	27	1314247247270685602790860	1.222218e-08	3.881048e-16
28	28	9199730730894799219536020	4.619548e-09	5.544354e-17
29	29	64398115116263594536752140	1.746025e-09	7.920505e-18
30	30	450786805813845161757264980	6.599355e-10	1.131501e-18
31	31	3155507640696916132300854860	2.494322e-10	1.616430e-19
32	32	22088553484878412926105984020	9.427650e-11	2.309185e-20
33	33	154619874394148890482741888140	3.563317e-11	3.298836e-21
34	34	1082339120759042233379193216980	1.346807e-11	4.712623e-22
35	35	7576373845313295633654352518860	5.090452e-12	6.732319e-23
36	36	53034616917193069435580467632020	1.924010e-12	9.617598e-24
37	37	371242318420351486049063273424140	7.272075e-13	1.373943e-24
38	38	2598696228942460402343442913968980	2.748586e-13	1.962775e-25
39	39	18190873602597222816404100397782860	1.038868e-13	2.803964e-26
40	40	127336115218180559714828702784480020	3.926551e-14	4.005663e-27