Free developer tool
H3 Index Finder
Convert latitude and longitude into an H3 cell. Choose a resolution, inspect the cell boundary on the map, and see its neighbouring cells.
The H3 cell is outlined on the map.
What is H3?
H3 is a hierarchical hexagonal spatial index. Instead of working with raw latitude and longitude pairs, you assign each location to a cell at a chosen resolution and use the cell ID for grouping, joining and analysis.
Why use H3?
Clustering, heatmaps, geofencing, territory analysis, demand aggregation and large-scale mobility data all become simple group-by operations on a cell ID. Changing the resolution trades spatial precision for fewer, larger cells.
Frequently asked questions
What resolution should I use?
Lower numbers are larger cells. Resolution 0 cells are continent-sized, resolution 6 is roughly city-district scale, and resolution 15 is under a square metre. Pick the coarsest resolution that still answers your question.
What is the difference between a cell and its neighbours?
Each H3 cell has six neighbours (five for the twelve pentagon cells). The API returns their cell IDs, which is handy for proximity and smoothing queries.
Can I convert a cell back to coordinates?
Yes. Every response includes the cell centre and its boundary as a GeoJSON polygon.
API
Get an H3 cell with the API
GET /v1/h3?lat=48.8584&lon=2.2945&res=6curl -H "X-API-Key: YOUR_MAPSI_API_KEY" \
"https://mapsi.dev/v1/h3?lat=48.8584&lon=2.2945&res=6"const response = await fetch(
"https://mapsi.dev/v1/h3?lat=48.8584&lon=2.2945&res=6",
{ headers: { "X-API-Key": "YOUR_MAPSI_API_KEY" } }
);
const data = await response.json();
console.log(data.cell); // "861fb4677ffffff"import requests
response = requests.get(
"https://mapsi.dev/v1/h3",
params={"lat": 48.8584, "lon": 2.2945, "res": 6},
headers={"X-API-Key": "YOUR_MAPSI_API_KEY"},
)
data = response.json()
print(data){
"success": true,
"cell": "861fb4677ffffff",
"resolution": 6,
"centre": { "lat": 48.83959144969481, "lon": 2.317106432748451 },
"boundary": {
"type": "Polygon",
"coordinates": [[[2.326380543704421, 48.87113406305762], ...]]
},
"neighbours": [
"861fb462fffffff",
"861fb460fffffff",
"861fb4657ffffff",
"861fb4647ffffff",
"861fb4667ffffff",
"861fb475fffffff"
]
}